[{"id":617587,"date":"2026-08-11T17:11:44","date_gmt":"2026-08-11T22:11:44","guid":{"rendered":"https:\/\/www.logicmonitor.com\/?p=617587"},"modified":"2026-08-11T17:11:45","modified_gmt":"2026-08-11T22:11:45","slug":"observability-isnt-about-the-tool-its-about-the-truth","status":"publish","type":"post","link":"https:\/\/www.logicmonitor.com\/fr\/blog\/observability-isnt-about-the-tool-its-about-the-truth","title":{"rendered":"L'observabilit\u00e9 n'est pas une question d'outil. C'est une question de v\u00e9rit\u00e9."},"content":{"rendered":"<?xml encoding=\"UTF-8\"><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50 rtc-text-content--no-top-pad\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-book-open\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xs fs-md-text-display-sm fs-lg-text-display-md font-medium text-core-blue-900\">\n        Le t\u00e9l\u00e9chargement rapide :      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900 headline-is-quote\">\n        <p>When API latency crosses company boundaries, traditional APM tools lose visibility, and Internet Performance Monitoring becomes the only way to pinpoint the root cause.<\/p>\n      <\/div>\n    \n                  <ul class=\"rtc-text-content__bullet-list\">\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Traditional APM, RUM, and logging tools only monitor what&rsquo;s inside your own infrastructure, leaving a critical blind spot across the Internet path between your systems and your customers.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>In a real-world case, synthetic API testing from multiple ISPs and cities pinpointed backend application dependencies as the root cause in just three hours and 15 test runs.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Backend latency was cut nearly in half once teams had the data to direct their optimization efforts to the right layer of the stack.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Explore LM Internet Performance Monitoring to gain full-path visibility from user to origin across every layer of the Internet Stack.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p class=\"wp-block-paragraph\"><br>An enterprise client reports latency. Your dashboards say everything is fine. They blame you. You blame them. Nobody can prove it either way.<\/p><p class=\"wp-block-paragraph\">This is where most monitoring efforts hit a wall. The conversation gets stuck on dashboards and tools instead of the one thing that actually matters: getting to the root cause, fast.<\/p><p class=\"wp-block-paragraph\">Observability should give you the ability to pinpoint problems quickly when your reputation and revenue are on the line. But most tools only see what&rsquo;s happening inside your own infrastructure. When the issue lives somewhere between your systems and your customer&rsquo;s systems, you&rsquo;re flying blind.<\/p><h2 id=\"h-what-happens-when-two-companies-see-the-same-issue-differently\" class=\"wp-block-heading\">What happens when two companies see the same issue differently?<\/h2><p class=\"wp-block-paragraph\">A leading financial services provider (let&rsquo;s call them Company A) was under pressure. A key enterprise client, Company B, reported delays of 3 to 6 seconds when hitting APIs embedded in their customer-facing apps.<\/p><ul class=\"wp-block-list\">\n<li>Company B: &ldquo;Your APIs are slow. It&rsquo;s impacting our customer experience.&rdquo;<\/li>\n\n\n\n<li>Company A (relying on <strong>Datadog<\/strong> APM): &ldquo;Everything looks fine on our side.&rdquo;<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">A stalemate, and a textbook case of observability failure.<\/p><h2 id=\"h-why-couldnt-datadog-find-the-issue\" class=\"wp-block-heading\">Why couldn&rsquo;t Datadog find the issue?<\/h2><p class=\"wp-block-paragraph\">Datadog is an excellent Application Performance Monitoring (APM) tool, but it wasn&rsquo;t built to see beyond your own infrastructure.<\/p><p class=\"wp-block-paragraph\">Even though Company A had robust APM and logging, they couldn&rsquo;t see anything outside their own walls. They couldn&rsquo;t install agents in Company B&rsquo;s infrastructure, and they couldn&rsquo;t drop Real User Monitoring (RUM) scripts into someone else&rsquo;s codebase.<\/p><p class=\"wp-block-paragraph\">Here&rsquo;s what each tool can (and can&rsquo;t) do:<\/p><ul class=\"wp-block-list\">\n<li><strong>APM (like Datadog)<\/strong>: Great inside the app, once traffic arrives.<\/li>\n\n\n\n<li><strong>RUM<\/strong>: Excellent for frontend insights, but only if you own the app.<\/li>\n\n\n\n<li><strong>Logs<\/strong>: Useful for what already happened, but not where packets got stuck in transit.<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">The common denominator: none of them can see what&rsquo;s happening <em>between<\/em> systems. Here&rsquo;s why.<\/p><h2 id=\"h-why-do-apis-create-blind-spots-between-companies\" class=\"wp-block-heading\">Why do APIs create blind spots between companies?<\/h2><p class=\"wp-block-paragraph\">APIs are the interface between companies. Just like you don&rsquo;t walk into a restaurant kitchen to talk to the chef, companies don&rsquo;t peek behind each other&rsquo;s firewalls. They interact through APIs, exchanging structured requests and responses without seeing what&rsquo;s happening on the other side.<\/p><p class=\"wp-block-paragraph\">That&rsquo;s where blind spots show up.<\/p><p class=\"wp-block-paragraph\">When two systems communicate through APIs, neither has visibility into the other&rsquo;s inner workings. The moment a request leaves your infrastructure, it enters the black box of &ldquo;someone else&rsquo;s problem,&rdquo; including infrastructure, networks, and dependencies you don&rsquo;t own and can&rsquo;t instrument.<\/p><p class=\"wp-block-paragraph\">The core problem is that the Internet isn&rsquo;t instrumentable. You can&rsquo;t deploy agents or RUM scripts across networks and infrastructure you don&rsquo;t control. That&rsquo;s why traditional observability tools stop at the edge. Beyond that, you&rsquo;re guessing.<\/p><p class=\"wp-block-paragraph\">But delivering a great digital experience depends on multiple networks, protocols, agents, and sub-systems working together. These dependencies form what&rsquo;s known as the Internet Stack.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"2475\" height=\"1370\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack.png\" alt=\"\" class=\"wp-image-614721\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack.png 2475w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-300x166.png 300w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-1024x567.png 1024w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-768x425.png 768w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-1536x850.png 1536w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-2048x1134.png 2048w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-18x10.png 18w\" sizes=\"auto, (max-width: 2475px) 100vw, 2475px\"><\/figure><p class=\"wp-block-paragraph\"><em>The Internet Stack<\/em><\/p><p class=\"wp-block-paragraph\">The Internet Stack is the collection of technologies, systems, and services that make possible and impact every digital user experience, from the core Internet systems like BGP, network technologies like TCP\/IP, security technologies like SASE, protocols like QUIC or POP, cloud services, third party dependencies including APIs and web services, and SaaS applications. The term refers to all IP-based networks including the public Internet, private networks, and everything in between.<\/p><p class=\"wp-block-paragraph\">When performance breaks down somewhere in that chain, it doesn&rsquo;t matter if it&rsquo;s your fault or not. Your customers still feel it. APIs were designed for efficiency, not visibility.<\/p><p class=\"wp-block-paragraph\">This is where <a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\">LM Internet Performance Monitoring<\/a> (IPM) becomes essential. IPM gives you deep visibility into every layer of the Internet that can impact your service. Think of it as APM for the Internet Stack, purpose-built for the systems you don&rsquo;t own but still rely on.<\/p><h2 id=\"h-how-do-you-get-to-the-truth-when-apm-falls-short\" class=\"wp-block-heading\">How do you get to the truth when APM falls short?<\/h2><p class=\"wp-block-paragraph\">When traditional observability tools couldn&rsquo;t explain the latency, Internet Performance Monitoring filled the gap. Instead of guessing, Company A used IPM to run <a href=\"https:\/\/www.logicmonitor.com\/deep-dive\/api-monitoring-tools\/api-performance-testing\">synthetic API tests<\/a> across real-world networks:<\/p><ul class=\"wp-block-list\">\n<li>From user ISPs: major U.S. carriers and fiber providers<\/li>\n\n\n\n<li>From backbone and enterprise vantage points<\/li>\n\n\n\n<li>From inside Company A&rsquo;s own infrastructure<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">Each test simulated actual API calls, complete with traceable request IDs and timestamps. The results were clear.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1312\" height=\"391\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image.jpeg\" alt=\"\" class=\"wp-image-617588\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image.jpeg 1312w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-18x5.jpeg 18w\" sizes=\"auto, (max-width: 1312px) 100vw, 1312px\"><\/figure><p class=\"wp-block-paragraph\">This diagram maps the full path of an API call, from the client through Akamai, to internal proxy infrastructure and upstream systems. It shows where latency accumulates:<\/p><ul class=\"wp-block-list\">\n<li>DNS, connect, and SSL times are negligible.<\/li>\n\n\n\n<li>Akamai&rsquo;s edge processing is fast (~48ms).<\/li>\n\n\n\n<li>Major delays occur during origin fetch (3,143ms) and proxy fetch (2,364ms), both inside the server infrastructure.<\/li>\n\n\n\n<li>This confirms the problem isn&rsquo;t with the client or CDN, but deep in the backend.<\/li>\n<\/ul><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1503\" height=\"694\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-1.jpeg\" alt=\"\" class=\"wp-image-617591\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-1.jpeg 1503w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-1-18x8.jpeg 18w\" sizes=\"auto, (max-width: 1503px) 100vw, 1503px\"><\/figure><p class=\"wp-block-paragraph\"><em>Latency breakdown across cities<\/em><\/p><p class=\"wp-block-paragraph\">This chart tracks average response and wait times across major U.S. cities. The key insight:<\/p><ul class=\"wp-block-list\">\n<li>Latency patterns are remarkably consistent across geography.<\/li>\n\n\n\n<li>A single spike appears across multiple regions, ruling out a location-specific issue.<\/li>\n\n\n\n<li>This supports the conclusion that the bottleneck lives within the origin infrastructure, not in external networks.<\/li>\n<\/ul><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1475\" height=\"696\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-2.jpeg\" alt=\"\" class=\"wp-image-617592\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-2.jpeg 1475w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-2-18x8.jpeg 18w\" sizes=\"auto, (max-width: 1475px) 100vw, 1475px\"><\/figure><p class=\"wp-block-paragraph\"><em>ISP breakdown<\/em><\/p><p class=\"wp-block-paragraph\">Here, performance is analyzed by ISP (e.g., AT&amp;T, Comcast, Verizon):<\/p><ul class=\"wp-block-list\">\n<li>Despite some noise, the pattern is stable across providers, with no single ISP showing consistently worse performance.<\/li>\n\n\n\n<li>This helps eliminate ISP-side routing or congestion as a root cause.<\/li>\n\n\n\n<li>The brief AT&amp;T spike aligns with the same moment seen in city-level data.<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\"><strong>The result:<\/strong> Consistent 3 to 6 second latency, both internally and externally.<\/p><p class=\"wp-block-paragraph\">With that data, they could rule out the usual suspects:<\/p><ul class=\"wp-block-list\">\n<li>It wasn&rsquo;t the ISP.<\/li>\n\n\n\n<li>It wasn&rsquo;t the CDN.<\/li>\n\n\n\n<li>It wasn&rsquo;t DNS.<\/li>\n\n\n\n<li>It wasn&rsquo;t the proxy (Envoy).<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">The process of elimination worked like a proper diagnostic: isolate each layer, eliminate what&rsquo;s clean, and close in on the source. Parsing response headers like x-envoy-upstream-service-time confirmed the latency was occurring further upstream, deep within Company A&rsquo;s own service environment. This pointed engineers in the right direction without them needing to sift through endless log lines. Trace IDs and timestamps were shared with internal teams to help pinpoint issues around application dependencies, which were confirmed as the root cause.<\/p><p class=\"wp-block-paragraph\">This methodical approach, including initial discussion and setup, took just three hours and about 15 test runs. No guesswork, just clarity.<\/p><p class=\"wp-block-paragraph\">After internal validation, teams began work on the improvements, which are still ongoing but already measurable where it matters most.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"975\" height=\"422\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-49.png\" alt=\"\" class=\"wp-image-617590\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-49.png 975w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-49-18x8.png 18w\" sizes=\"auto, (max-width: 975px) 100vw, 975px\"><\/figure><p class=\"wp-block-paragraph\">Backend latency has dropped significantly: both upstream service time and overall wait time have been cut nearly in half. These gains reflect steady optimization efforts that are clearly moving in the right direction.<\/p><h2 id=\"h-what-ipm-delivers-that-apm-cant\" class=\"wp-block-heading\">What IPM delivers that APM can&rsquo;t<\/h2><p class=\"wp-block-paragraph\">Datadog, New Relic, and Dynatrace are strong at what they do inside your infrastructure. But they weren&rsquo;t designed to monitor the Internet itself.<\/p><p class=\"wp-block-paragraph\">Internet Performance Monitoring was built for exactly that. Here&rsquo;s how:<\/p><p class=\"wp-block-paragraph\"><strong>A global agent network<\/strong><\/p><ul class=\"wp-block-list\">\n<li>3,000+ agents across last-mile, backbone, cloud, enterprise, and on-prem environments<\/li>\n\n\n\n<li>Real-user network emulation, not cloud-only testbeds<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><strong>Full synthetic coverage<\/strong><\/p><ul class=\"wp-block-list\">\n<li>HTTP\/S, APIs, Browser, DNS, SSL, BGP, MQTT, QUIC, Custom scripts<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><strong>Advanced diagnostics<\/strong><\/p><ul class=\"wp-block-list\">\n<li>Packet loss, jitter, path tracing, hop analysis<\/li>\n\n\n\n<li>Region-specific degradation detection<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><strong>Frontend visibility<\/strong><\/p><ul class=\"wp-block-list\">\n<li>WebPageTest for in-depth frontend performance analysis<\/li>\n\n\n\n<li>Browser + mobile RUM SDKs for teams who can instrument the frontend<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><strong>Connectivit\u00e9 transparente<\/strong><\/p><ul class=\"wp-block-list\">\n<li>Feeds directly into Datadog, Splunk, New Relic, Dynatrace<\/li>\n\n\n\n<li>Enhances existing observability stacks without replacing them<\/li>\n\n\n\n<li>Provides end-to-end visibility across the Internet Stack via a real-time dependency map<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">And because <a href=\"https:\/\/www.logicmonitor.com\/fr\/logicmonitor-catchpoint\">Catchpoint is part of the LogicMonitor platform<\/a> \u00e0 c\u00f4t\u00e9 <a href=\"https:\/\/www.logicmonitor.com\/fr\/infrastructure-monitoring\">LM Envision<\/a> et<a href=\"https:\/\/www.logicmonitor.com\/fr\/edwin-ai\"> Edwin AI<\/a>, teams get a unified view from user to code. Internet performance data flows into the same telemetry pipeline and context graph that covers infrastructure, cloud, and applications, giving operations teams a single system to detect, understand, and act on issues across the full digital path.<\/p><h2 id=\"h-why-teams-cling-to-familiar-tools-even-when-theyre-not-fit-for-purpose\" class=\"wp-block-heading\">Why teams cling to familiar tools even when they&rsquo;re not fit for purpose<\/h2><p class=\"wp-block-paragraph\">Familiar tools are comfortable. They&rsquo;re deployed, widely understood, and politically safe. But comfort sometimes wins out over capability, especially in large, mature organizations where tooling decisions are influenced by inertia rather than fitness for purpose. When seconds matter and customers are impacted, you need <strong>clarity<\/strong>, not comfort.<\/p><h2 id=\"h-who-takes-the-blame-when-apis-are-slow\" class=\"wp-block-heading\">Who takes the blame when APIs are slow?<\/h2><p class=\"wp-block-paragraph\">In this case, Company B blamed Company A. Company A blamed Company B. Neither had data to prove their case.<\/p><p class=\"wp-block-paragraph\">Meanwhile, users just saw a slow experience.<\/p><p class=\"wp-block-paragraph\">End users don&rsquo;t know an API call is crossing company boundaries. They only see the brand they&rsquo;re interacting with. If it&rsquo;s slow, they assume that brand is to blame. Solving performance issues quickly is about more than technical hygiene. It&rsquo;s about protecting business relationships and customer trust.<\/p><h2 id=\"h-the-real-job-of-observability\" class=\"wp-block-heading\">The real job of observability<\/h2><p class=\"wp-block-paragraph\">Observability should get you to the truth, fast. And often, the truth lives outside your four walls.<\/p><p class=\"wp-block-paragraph\">In an AI-driven world, data powers decisions. But if your data is incomplete or your telemetry is limited to your own infrastructure, your AI models are working with partial information.<\/p><p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\">LM Internet Performance Monitoring<\/a> gives teams the ability to:<\/p><ul class=\"wp-block-list\">\n<li>Validate performance from the outside in<\/li>\n\n\n\n<li>Prove or disprove internal assumptions with independent data<\/li>\n\n\n\n<li>Pinpoint root causes in minutes, not days<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">The point of observability is getting to the answer. LM Internet Performance Monitoring makes that possible across the full Internet path, not just inside your own environment.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-calendar-check\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xxs fs-md-text-display-xs fs-lg-text-display-sm font-medium text-core-blue-900\">\n        See where your APIs lose time across the Internet Stack.      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900\">\n        <p>LM Internet Performance Monitoring gives your team full-path visibility from user to origin, so you can resolve latency issues in hours, not days. Pair it with LM Envision and Edwin AI for a unified view across your entire digital path.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/catchpoint-demo\" class=\"btn btn-link\" target=\"_self\">\n        Demander une d\u00e9monstration          <span class=\"icon-end\"><svg class=\"\" width=\"20px\" height=\"20px\" style=\"fill: #060F4B\">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-arrow-right\"><\/use>\n    <\/svg><\/span>\n      <\/a>\n        <\/div>\n            <\/div>\n<\/div><h4 id=\"h-faqs\" class=\"wp-block-heading\">FAQ<\/h4><div class=\"accordion-block accordion-block--light\">\n      <div class=\"accordion-block__items\">\n              <div class=\"accordion-block__item active\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-does-internet-performance-monitoring-differ-from-apm\">\n            How does Internet Performance Monitoring differ from APM?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer active\">\n            <p>APM monitors application performance inside your own infrastructure. Internet Performance Monitoring extends visibility to the networks, ISPs, CDNs, and DNS layers between your systems and your users. Together, they provide full-path observability from code to customer.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-can-lm-internet-performance-monitoring-work-alongside-existing-tools-like-datadog-or-new-relic\">\n            Can LM Internet Performance Monitoring work alongside existing tools like Datadog or New Relic?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>Yes. LM Internet Performance Monitoring integrates directly with Datadog, Splunk, New Relic, and Dynatrace. It enhances your existing observability stack by adding external network visibility without replacing any current tooling.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-quickly-can-internet-performance-monitoring-identify-the-root-cause-of-cross-boundary-latency\">\n            How quickly can Internet Performance Monitoring identify the root cause of cross-boundary latency?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>In the case study described in this article, the team identified the root cause in approximately three hours using about 15 synthetic test runs. The structured diagnostic approach eliminates guesswork by systematically ruling out each layer of the Internet Stack.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div>","protected":false},"excerpt":{"rendered":"<p>Les outils APM s'arr\u00eatent \u00e0 la limite de votre infrastructure. La surveillance des performances Internet r\u00e9v\u00e8le la cause r\u00e9elle de la latence des API sur les r\u00e9seaux que vous ne contr\u00f4lez pas.<\/p>","protected":false},"author":16,"featured_media":621538,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[5035],"tags":[7886,5348,7850,7867,7910,7907,7863,6677,7866,7868],"industry":[7513],"role":[7843],"lm_strategic_tags":[],"topic":[7842],"class_list":["post-617587","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-financial-services","role-sre","topic-internet-performance-monitoring"],"acf":{"page_language":"english","translated_pages":"","updated_date":null,"author_section_checkbox":true,"author_image":617027,"author_linkedin":"https:\/\/www.linkedin.com\/in\/denton-chikura-422186201\/","author_name":"Denton Chikura","author_job_title":"Technical Writer","author_dept":"","author_bio":"Denton Chikura is a technical writer and longtime observability advocate focused on helping site reliability engineers and engineering teams discover the tools and capabilities that strengthen internet resilience. He works at the intersection of monitoring, performance, and infrastructure to make complex systems more understandable and usable, bridging the gap between deep technical detail and real\u2011world operations. His goal is to help teams build faster, detect issues earlier, and recover smarter, ultimately making the internet a better, more reliable place for everyone.","reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.2 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Observability isn\u2019t about the tool. It\u2019s about the truth | LogicMonitor<\/title>\n<meta name=\"description\" content=\"Traditional APM tools stop at the boundary of what you control. To find the truth when performance breaks down across the Internet, teams need observability beyond their walls.\" \/>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Observability Isn\u2019t About the Tool. It\u2019s About the Truth\" \/>\n<meta property=\"og:description\" content=\"Traditional APM tools stop at the boundary of what you control. To find the truth when performance breaks down across the Internet, teams need observability beyond their walls.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.logicmonitor.com\/fr\/blog\/observability-isnt-about-the-tool-its-about-the-truth\" \/>\n<meta property=\"og:site_name\" content=\"LogicMonitor\" \/>\n<meta property=\"article:published_time\" content=\"2026-08-11T22:11:44+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-08-11T22:11:45+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/Blog_Observability-Isnt-About-the-Tool.-Its-About-the-Truth_Meta-1600x900px.png\" \/>\n\t<meta property=\"og:image:width\" content=\"2400\" \/>\n\t<meta property=\"og:image:height\" content=\"1350\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"destiny.setzer@logicmonitor.com\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"8 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/blog\\\/observability-isnt-about-the-tool-its-about-the-truth#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/blog\\\/observability-isnt-about-the-tool-its-about-the-truth\"},\"author\":{\"name\":\"destiny.setzer@logicmonitor.com\",\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/#\\\/schema\\\/person\\\/bfbb8cb00c9595482098c66aa78b9def\"},\"headline\":\"Observability Isn\u2019t About the Tool. 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la Source au Bord : Les Six Types d'Agents que Vous Ne Pouvez Pas Ignorer"},"content":{"rendered":"<?xml encoding=\"UTF-8\"><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50 rtc-text-content--no-top-pad\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-book-open\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xs fs-md-text-display-sm fs-lg-text-display-md font-medium text-core-blue-900\">\n        Le t\u00e9l\u00e9chargement rapide :      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900 headline-is-quote\">\n        <p>Monitoring from a single vantage point guarantees blind spots across the Internet&rsquo;s thousands of independent networks.<\/p>\n      <\/div>\n    \n                  <ul class=\"rtc-text-content__bullet-list\">\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Backbone, cloud, wireless, last-mile, enterprise, and BGP agents each cover a distinct layer of the Internet Stack, revealing problems invisible to the others.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Over 96% of backbone agents use single-homed Tier 1\/Tier 2 connectivity for path consistency, making anomalies easier to detect and attribute.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>BGP route collectors process real-time routing data from 1,700+ agents; Catchpoint&rsquo;s private collector infrastructure alone spans 330+ agents across 100 unique networks, catching hijacks and leaks in real time.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Map your monitoring to the full Internet Stack today so you find issues at the source, not from a customer complaint.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p class=\"wp-block-paragraph\"><br>Teams running Internet-dependent services know the frustration: an outage hits a specific ISP, a BGP hijack reroutes traffic in one region, or a CDN degrades for users on certain networks. If you&rsquo;re only monitoring from a cloud provider or a handful of data centers, you won&rsquo;t see it until customers start complaining.&nbsp;<\/p><p class=\"wp-block-paragraph\">That delay costs real money. It triggers finger-pointing between cloud, CDN, and ISP teams while users churn. Synthetic checks from a single cloud region can&rsquo;t catch what&rsquo;s happening across the thousands of independent networks your traffic actually traverses.<\/p><p class=\"wp-block-paragraph\">The root cause is structural. The Internet is a patchwork of thousands of independent networks (ISPs, data centers, backbones, wireless carriers, and more), all connected through peering and transit agreements. Monitoring from just one layer of that stack leaves blind spots across the rest. That layered architecture is what we call the Internet Stack.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"2475\" height=\"1370\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack.png\" alt=\"\" class=\"wp-image-614721\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack.png 2475w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-300x166.png 300w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-1024x567.png 1024w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-768x425.png 768w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-1536x850.png 1536w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-2048x1134.png 2048w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/06\/FIGURE-1_-The-Internet-Stack-18x10.png 18w\" sizes=\"auto, (max-width: 2475px) 100vw, 2475px\"><\/figure><p class=\"wp-block-paragraph\"><em>The layers of the Internet Stack<\/em><\/p><p class=\"wp-block-paragraph\">The Internet Stack is the collection of technologies, systems, and services that make possible and impact every digital user experience, from the core Internet systems like BGP, network technologies like TCP\/IP, security technologies like SASE, protocols like QUIC or POP, cloud services, third party dependencies including APIs and web services, and SaaS applications. The term refers to all IP-based networks including the public Internet, private networks, and everything in between.<\/p><p class=\"wp-block-paragraph\">This article breaks down the six types of synthetic monitoring agents (backbone, public cloud, wireless, last-mile, enterprise, and BGP), where each one sits in the Internet Stack, and why each matters for catching problems that single-vantage-point monitoring misses. It&rsquo;s also why <a href=\"https:\/\/www.logicmonitor.com\/fr\/logicmonitor-catchpoint\">Catchpoint, a LogicMonitor company<\/a>, built a Global Agent Network spanning <a href=\"https:\/\/www.logicmonitor.com\/platform\/synthetic-monitoring\">3,000+ agents across 395 providers in 105 countries and 346 cities<\/a>: covering every layer requires that kind of reach. First, let&rsquo;s look at how the Internet actually connects end to end.<\/p><p class=\"wp-block-paragraph\">Within the LogicMonitor platform, this Internet-layer visibility connects directly to the rest of the stack. Internet Performance Monitoring and the Global Agent Network cover the path between users and your services. LM Envision provides the infrastructure and cloud context. Edwin AI ties those signals together with correlation and AI-assisted triage. The result is user-to-code visibility across every layer, from backbone transit to application code.<\/p><h2 id=\"h-why-multiple-vantage-points-are-key\" class=\"wp-block-heading\">Why multiple vantage points are key<\/h2><p class=\"wp-block-paragraph\">The Internet isn&rsquo;t a single cloud. You can&rsquo;t just tap into one place and see it all. It&rsquo;s tens of thousands of independent networks (ISPs, data centers, wireless carriers) stitched together by peering and transit deals. In a peering arrangement, two networks exchange traffic for free. In a transit relationship, one network pays another to carry its traffic. Peering keeps traffic local; transit carries it farther afield.<\/p><p class=\"wp-block-paragraph\">Because each network makes its own choices about peering and transit, you need monitoring agents at many points to see what&rsquo;s happening. A performance hiccup in one ISP&rsquo;s peering location might not show up at a different ISP&rsquo;s vantage point. That&rsquo;s why we place agents in dozens of key networks, so you won&rsquo;t miss an issue that affects only a slice of the Internet.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"920\" height=\"860\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-47.png\" alt=\"\" class=\"wp-image-617585\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-47.png 920w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-47-13x12.png 13w\" sizes=\"auto, (max-width: 920px) 100vw, 920px\"><\/figure><p class=\"wp-block-paragraph\"><em>A map of how thousands of networks (Autonomous Systems) peer and buy transit around the world.<\/em><a href=\"https:\/\/www.caida.org\/projects\/as-core\/2020\/#poster\"> <em>Source<\/em><\/a><\/p><h2 id=\"h-why-tiers-matter\" class=\"wp-block-heading\">Why tiers matter<\/h2><p class=\"wp-block-paragraph\">All those peering and transit agreements naturally sort networks into tiers:<\/p><ul class=\"wp-block-list\">\n<li><strong>Tier 1:<\/strong> These are large global networks that peer with each other and don&rsquo;t need to buy any transit to reach any corner of the Internet. They&rsquo;re considered the backbone of the Internet, as they typically carry long-distance traffic. While the networks in this group have changed since the beginning of the Internet, the group has remained relatively stable, including providers such as Lumen, AT&amp;T, Cogent, Verizon, Orange, GTT, NTT, and Telxius. This category includes large traditional telecom providers that have served their domestic markets for many years.<\/li>\n\n\n\n<li><strong>Tier 2:<\/strong> Regional providers that both peer and buy transit. The scale of operations and the type of services they provide (IP transit, Ethernet, or dark fiber wavelengths) dictate the number of peering connections and transit providers. Most networks fall into this category if they peer at one or more Internet exchange points and have two or more upstream providers.<\/li>\n\n\n\n<li><strong>Tier 3:<\/strong> Smaller, local ISPs (often single-homed) that feed to an upstream provider. They show you what your end users see on a residential or localized network.<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">Putting agents in each tier matters because a Tier 1 network will have more visibility into global events (total or partial outages, backbone congestion, etc.) compared to a regional Tier 2 or a local Tier 3 network. On the other hand, localized outages affecting a limited number of providers in a particular geographic area won&rsquo;t be easily observed unless you have visibility from one of the affected networks.<\/p><h2 id=\"h-why-single-homed-tier-1-tier-2-connectivity-matters\" class=\"wp-block-heading\">Why single-homed Tier 1\/Tier 2 connectivity matters<\/h2><p class=\"wp-block-paragraph\">Now that we know how networks sort into tiers, let&rsquo;s look at how those tiers influence the way we connect our agents.<\/p><p class=\"wp-block-paragraph\">Many data centers, hosting providers, and managed service providers typically use multiple upstream ISPs (Tier 1 and Tier 2) to create a single, aggregated connection to the Internet. This connectivity, normally offered as a service, is often called blended bandwidth or multihoming.<\/p><p class=\"wp-block-paragraph\">Multihoming improves redundancy because traffic can be rerouted if one ISP goes down or has packet loss or congestion. It also improves performance because different ISPs may offer better latency to different geographies.<\/p><p class=\"wp-block-paragraph\">Pour <a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\">Supervision des performances Internet<\/a> (IPM), however, using multihomed agents instead of single-homed Tier 1\/Tier 2 carriers introduces variability in your monitoring data, making it harder to identify and troubleshoot the issues affecting performance.<\/p><p class=\"wp-block-paragraph\">Here&rsquo;s why more than 96% of our backbone agents use single-homed Tier 1\/Tier 2 connectivity instead of blended bandwidth:<\/p><ul class=\"wp-block-list\">\n<li><strong>Path consistency:<\/strong> A consistent Tier 1 upstream path reduces variability, making anomalies and degradations easier to detect and attribute.<\/li>\n\n\n\n<li><strong>Backbone visibility:<\/strong> Tier 1 visibility is essential to observe how the core Internet behaves in relation to routing anomalies, BGP hijacks, or backbone congestion.<\/li>\n\n\n\n<li><strong>Performance stability:<\/strong> With blended connectivity, routes may change dynamically based on load-balancing or pricing strategies (for example, BGP-based traffic engineering), affecting performance results.<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">Now that you understand how and why we choose single-homed Tier 1\/Tier 2 connectivity, let&rsquo;s look at each of our five synthetic agent types. We&rsquo;ll explain where we place them, how we build them, and what visibility each one gives you.<\/p><h2 id=\"h-backbone-agents\" class=\"wp-block-heading\">Backbone agents<\/h2><p class=\"wp-block-paragraph\"><em>Backbone agents give you a &ldquo;core-of-Internet&rdquo; vantage point to catch global outages, BGP hijacks, and CDN-level issues no other agent can see.<\/em><\/p><p class=\"wp-block-paragraph\">We place backbone agents in Tier 1 or Tier 2 ISPs worldwide, selecting carriers by:<\/p><ul class=\"wp-block-list\">\n<li><strong>Geography and market importance<\/strong> (global connectivity hubs)<\/li>\n\n\n\n<li><a href=\"https:\/\/asrank.caida.org\/\"><strong>CAIDA ASRank<\/strong><\/a><strong> &amp;<\/strong><a href=\"https:\/\/stats.labs.apnic.net\/aspop\"><strong> <\/strong><strong>APNIC eyeball data<\/strong><\/a> (to cover the most interconnected networks)<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">Each backbone agent runs as a server cluster in a carrier-neutral data center with dedicated IP transit. Carrier neutrality ensures multiple international and domestic carriers via cross-connects, while colocating servers in one facility reduces colocation costs. In emerging markets (for example, parts of Africa or China) where neutral data centers are scarce, we may host clusters in carrier-owned facilities as a last resort.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"924\" height=\"752\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-45.png\" alt=\"\" class=\"wp-image-617583\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-45.png 924w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-45-15x12.png 15w\" sizes=\"auto, (max-width: 924px) 100vw, 924px\"><\/figure><p class=\"wp-block-paragraph\"><em>Connectivity diagram of backbone agents at a data center facility<\/em><\/p><p class=\"wp-block-paragraph\">Measuring performance and availability from backbone agents is critical for:<\/p><ul class=\"wp-block-list\">\n<li><strong>Experience Level Objective (XLO) measurements:<\/strong> Validate service performance when source and target share the same ISP.<\/li>\n\n\n\n<li><strong>CDN performance and validation:<\/strong> Ensure fast, reliable content delivery across the backbone.<\/li>\n\n\n\n<li><strong>Competitive benchmarking:<\/strong> Compare your service to peers in the same Tier 1\/2 networks.<\/li>\n\n\n\n<li><strong>Peering and ISP monitoring:<\/strong> Detect routing changes, BGP anomalies, or unexpected transit behavior.<\/li>\n\n\n\n<li><strong>Geo-based DNS validation:<\/strong> Confirm DNS resolution speed and correctness from the core network.<\/li>\n<\/ul><h2 id=\"h-public-cloud-agents\" class=\"wp-block-heading\">Public cloud agents<\/h2><p class=\"wp-block-paragraph\"><em>Cloud agents give you visibility right inside public-cloud data centers, so you can catch platform-specific issues before they impact users.<\/em><\/p><p class=\"wp-block-paragraph\">To date, Catchpoint runs 280+ cloud agents across every key availability region in AWS, Azure, Google, Oracle, Alibaba, Tencent, Akamai Compute, and OVH.<\/p><p class=\"wp-block-paragraph\">Measuring performance and availability to and from cloud agents is essential if you&rsquo;re hosting applications in the cloud or using any of their computing products. Cloud agents allow your SRE teams to preemptively detect performance degradations on public clouds that can affect how your users experience your applications and services.<\/p><h2 id=\"h-wireless-agents\" class=\"wp-block-heading\">Wireless agents<\/h2><p class=\"wp-block-paragraph\"><em>Wireless agents simulate real-world cellular conditions, giving you a true picture of how your applications perform on 3G\/4G\/5G networks.<\/em><\/p><p class=\"wp-block-paragraph\">We place wireless agents using AWS Wavelength and independent carriers in the US, Canada, Japan, Germany, Korea, India, and the UK (for example, Verizon, KDDI, BT, T-Mobile 5G, AT&amp;T 5G).<\/p><p class=\"wp-block-paragraph\">Running wireless tests alongside backbone tests lets you compare mobile experience to core-network performance, so you can spot issues like packet loss or DNS slowdowns that only affect cellular users.<\/p><h2 id=\"h-last-mile-agents\" class=\"wp-block-heading\">Last-mile agents<\/h2><p class=\"wp-block-paragraph\"><em>Last-mile agents live in real homes, giving you a true end-user view of broadband performance.<\/em><\/p><p class=\"wp-block-paragraph\">Our last-mile agents run on small customer-premise devices that connect to a residential ISP. Use these agents to troubleshoot ISP-specific issues (like throttling, DNS failures, or regional outages) that only affect subscribers on a particular network.<\/p><h2 id=\"h-enterprise-agents\" class=\"wp-block-heading\">Enterprise agents<\/h2><p class=\"wp-block-paragraph\"><em>Enterprise agents give you visibility into your own network, from branch offices to data centers to edge locations.<\/em><\/p><p class=\"wp-block-paragraph\">Enterprise agents are deployed within your organization&rsquo;s infrastructure. That includes office networks, private data centers, retail locations, or edge devices. These agents help you monitor internal applications, APIs, and services with the same level of granularity you get for external traffic. Combined with our Global Agent Network, enterprise agents complete the picture, giving you visibility from both outside-in and inside-out.<\/p><h2 id=\"h-bgp-agents\" class=\"wp-block-heading\">BGP agents<\/h2><p class=\"wp-block-paragraph\"><em>BGP agents watch the real-time routing table, so you can catch hijacks, leaks, or unexpected path changes that threaten your service.<\/em><\/p><p class=\"wp-block-paragraph\">We maintain a route collector infrastructure that processes real-time routing data from 1,700+ BGP agents with the goal of monitoring BGP activity and detecting issues such as route hijacks and leaks.<\/p><p class=\"wp-block-paragraph\">In addition to using RIPE RIS and RouteViews datasets, we operate our own private collector infrastructure, which includes agreements to receive data from 330+ BGP agents from 100 unique networks.<\/p><p class=\"wp-block-paragraph\">If you share your own BGP sessions with our private collectors, you&rsquo;ll gain even deeper insights in your portal, so you see exactly how routing anomalies affect your prefixes.<\/p><h2 id=\"h-choosing-the-right-agent-for-the-job\" class=\"wp-block-heading\">Choosing the right agent for the job<\/h2><p class=\"wp-block-paragraph\">Each agent type covers a different layer of the Internet Stack. Here&rsquo;s a quick reference for matching agent types to your monitoring objectives:<\/p><figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td>Type d'agent<\/td><td>Best For<\/td><td>Key Outcome<\/td><\/tr><tr><td>Backbone<\/td><td>Global outages, BGP hijacks, CDN validation, peering issues<\/td><td>Isolate backbone and transit problems before they cascade<\/td><\/tr><tr><td>Public Cloud<\/td><td>Cloud-hosted app performance, provider-specific degradation<\/td><td>Detect cloud platform issues before users feel them<\/td><\/tr><tr><td>Sans fil<\/td><td>Mobile\/cellular experience, 3G\/4G\/5G performance<\/td><td>Identify mobile-only issues like packet loss or DNS delays<\/td><\/tr><tr><td>Last-Mile<\/td><td>Residential ISP performance, end-user broadband quality<\/td><td>Catch ISP-specific throttling, DNS failures, or regional outages<\/td><\/tr><tr><td>Entreprise<\/td><td>Internal apps, branch offices, private data centers, edge<\/td><td>Complete inside-out visibility alongside outside-in Internet monitoring<\/td><\/tr><tr><td>BGP<\/td><td>Route hijacks, leaks, path changes, prefix monitoring<\/td><td>Detect routing anomalies that threaten service reachability<\/td><\/tr><\/tbody><\/table><\/figure><h2 id=\"h-wrapping-it-up\" class=\"wp-block-heading\">Wrapping it up<\/h2><p class=\"wp-block-paragraph\">When we&rsquo;re asked, &ldquo;Why build a network of over 3,000 agents in 105 countries and 346 cities?&rdquo; the simple answer is that today&rsquo;s Internet isn&rsquo;t one giant cloud but a patchwork quilt of independent networks.<\/p><p class=\"wp-block-paragraph\">By spreading our agents across every layer of the Internet Stack, we can reveal problems at the moment they start, whether it&rsquo;s a routing change in a distant backbone, a subtle slowdown in a public cloud region, or a local ISP hiccup affecting a handful of homes.<\/p><p class=\"wp-block-paragraph\">This broad visibility matters because whenever something goes wrong, you know exactly where to look. The effort we put into building and maintaining such a diverse network is what helps prevent those 3 a.m. wake-up calls, keeps war rooms from spinning up, and protects your users&rsquo; experience no matter where they connect.<\/p><p class=\"wp-block-paragraph\">LogicMonitor&rsquo;s unified platform brings together <a href=\"https:\/\/www.logicmonitor.com\/fr\/infrastructure-monitoring\">LM Envision<\/a> for infrastructure observability, <a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\">LM Internet Performance Monitoring<\/a> for Internet-layer visibility, and <a href=\"https:\/\/www.logicmonitor.com\/fr\/edwin-ai\">Edwin AI<\/a> for intelligence and action. Together, they give teams the context they need to move from reactive troubleshooting to proactive, autonomous operations.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-calendar-check\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xxs fs-md-text-display-xs fs-lg-text-display-sm font-medium text-core-blue-900\">\n        See how six agent types cover every layer of the Internet Stack.      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900\">\n        <p>LogicMonitor&rsquo;s platform boasts 3,100+ agents across 105 countries to detect issues at every layer, from backbone to last mile. Start monitoring the full stack now.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/catchpoint-demo\" class=\"btn btn-link\" target=\"_self\">\n        Demandez une d\u00e9mo          <span class=\"icon-end\"><svg class=\"\" width=\"20px\" height=\"20px\" style=\"fill: #060F4B\">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-arrow-right\"><\/use>\n    <\/svg><\/span>\n      <\/a>\n        <\/div>\n            <\/div>\n<\/div><h4 id=\"h-faqs\" class=\"wp-block-heading\">FAQ<\/h4><div class=\"accordion-block accordion-block--light\">\n      <div class=\"accordion-block__items\">\n              <div class=\"accordion-block__item active\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-why-do-backbone-agents-use-single-homed-connectivity-instead-of-blended-bandwidth\">\n            Why do backbone agents use single-homed connectivity instead of blended bandwidth?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer active\">\n            <p>Single-homed Tier 1 or Tier 2 connectivity provides consistent upstream paths, which reduces variability in monitoring data. This makes it significantly easier to detect anomalies, attribute degradations, and observe backbone-level events like BGP hijacks or congestion.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-do-last-mile-agents-differ-from-cloud-agents-in-terms-of-visibility\">\n            How do last-mile agents differ from cloud agents in terms of visibility?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>Cloud agents run inside public-cloud data centers (AWS, Azure, Google, and others) and detect platform-specific issues. Last-mile agents run on devices connected to residential ISPs, revealing problems like throttling, DNS failures, or regional outages that only affect broadband subscribers on a specific network.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-what-role-do-bgp-agents-play-in-preventing-outages\">\n            What role do BGP agents play in preventing outages?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>BGP agents monitor real-time routing tables to detect route hijacks, leaks, and unexpected path changes. Catchpoint&rsquo;s route collector infrastructure processes data from 1,700+ BGP agents overall, with its private collector spanning 330+ agents across 100 unique networks, giving teams early warning before routing anomalies affect end users.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div>","protected":false},"excerpt":{"rendered":"<p>D\u00e9couvrez pourquoi les agents de backbone, cloud, sans fil, de dernier kilom\u00e8tre, d'entreprise et BGP sont essentiels pour identifier les probl\u00e8mes \u00e0 chaque couche de la pile Internet.<\/p>","protected":false},"author":16,"featured_media":621535,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[5035],"tags":[7888,7865,7850,7867,7859,7907,7900,7863,7854,7018],"industry":[7523],"role":[7843],"lm_strategic_tags":[],"topic":[7842],"class_list":["post-617581","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-technology","role-sre","topic-internet-performance-monitoring"],"acf":{"page_language":"english","translated_pages":"","updated_date":null,"author_section_checkbox":true,"author_image":617027,"author_linkedin":"https:\/\/www.linkedin.com\/in\/denton-chikura-422186201\/","author_name":"Denton Chikura","author_job_title":"Technical Writer","author_dept":"","author_bio":"Denton Chikura is a technical writer and longtime observability advocate focused on helping site reliability engineers and engineering teams discover the tools and capabilities that strengthen internet resilience. He works at the intersection of monitoring, performance, and infrastructure to make complex systems more understandable and usable, bridging the gap between deep technical detail and real\u2011world operations. His goal is to help teams build faster, detect issues earlier, and recover smarter, ultimately making the internet a better, more reliable place for everyone.","reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.2 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Six Synthetic Agent Types for Full Internet Visibility | LogicMonitor<\/title>\n<meta name=\"description\" content=\"Discover why having diverse monitoring agents\u2014backbone, cloud, wireless, last-mile, enterprise, and BGP\u2014is essential to detect and resolve issues before users notice\" \/>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"From the Source to the Edge: The Six Agent Types You Can&#039;t Ignore\" \/>\n<meta property=\"og:description\" content=\"Discover why having diverse monitoring agents\u2014backbone, cloud, wireless, last-mile, enterprise, and BGP\u2014is essential to detect and resolve issues before users notice\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.logicmonitor.com\/fr\/blog\/from-the-source-to-the-edge-the-six-agent-types-you-cant-ignore\" \/>\n<meta property=\"og:site_name\" content=\"LogicMonitor\" \/>\n<meta property=\"article:published_time\" content=\"2026-08-11T22:10:27+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-08-11T22:10:28+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/Blog_From-the-Source-to-the-Edge-The-Six-Agent-Types-You-Cant-Ignore_Meta-1600x900px.png\" \/>\n\t<meta property=\"og:image:width\" content=\"2400\" \/>\n\t<meta property=\"og:image:height\" content=\"1350\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"destiny.setzer@logicmonitor.com\" \/>\n<meta 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\u00e0 l'\u00e8re d'Internet : DEM, IPM et APM : ce que vous devez savoir"},"content":{"rendered":"<?xml encoding=\"UTF-8\"><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50 rtc-text-content--no-top-pad\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-book-open\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xs fs-md-text-display-sm fs-lg-text-display-md font-medium text-core-blue-900\">\n        Le t\u00e9l\u00e9chargement rapide :      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900 headline-is-quote\">\n        <p>IPM fills the critical blind spot between DEM and APM, giving IT teams visibility into the Internet layer that traditional monitoring misses.<\/p>\n      <\/div>\n    \n                  <ul class=\"rtc-text-content__bullet-list\">\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>DEM measures user experience and APM tracks application internals, but neither monitors the Internet infrastructure (DNS, BGP, CDNs, ISPs) that connects users to applications.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>IPM uses thousands of real-world vantage points across backbone, wireless, last-mile, and enterprise networks to benchmark performance where users actually are.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>LogicMonitor unifies all three disciplines (LM Envision + Catchpoint + Edwin AI) into a single platform with shared telemetry, context, and AI-powered correlation.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Assess whether your current monitoring stack covers the full user-to-code path, or whether Internet-layer blind spots are slowing your triage and resolution times.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p class=\"wp-block-paragraph\"><br>La <a href=\"https:\/\/www.logicmonitor.com\/resources\/gartner-magic-quadrant-dem\">Gartner Magic Quadrant for Digital Experience Monitoring<\/a> marked a turning point. DEM is no longer an emerging practice buried inside APM suites. It&rsquo;s a category of its own, with dedicated evaluation criteria and a growing list of vendors competing for enterprise attention.<\/p><p class=\"wp-block-paragraph\">That recognition matters, but it also raises a harder question for IT operations leaders: if DEM, APM, and Internet Performance Monitoring (IPM) each solve different parts of the visibility problem, how do you bring them together without drowning in tool sprawl?<\/p><p class=\"wp-block-paragraph\">This article breaks down what each category covers, where the gaps are, and how a unified approach that connects user experience, Internet dependencies, and application behavior changes the way IT teams detect and resolve issues.<\/p><h2 id=\"h-what-dem-actually-measures-and-where-it-stops\" class=\"wp-block-heading\">What DEM Actually Measures, and Where It Stops<\/h2><p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.logicmonitor.com\/fr\/blog\/digital-experience-monitoring-what-it-is-and-why-it-matters\">Digital Experience Monitoring (DEM)<\/a> focuses on the user&rsquo;s side of the equation. It measures the availability, performance, and quality of what people experience when they interact with applications and digital services. DEM combines Real User Monitoring (RUM), synthetic monitoring, and endpoint monitoring to give IT teams a picture of experience quality from the outside in.<\/p><p class=\"wp-block-paragraph\">That&rsquo;s a meaningful shift from <a href=\"https:\/\/www.logicmonitor.com\/fr\/platform\/application-performance-monitoring\">Application Performance Monitoring (APM)<\/a>, which focuses on what&rsquo;s happening inside the application: code execution, backend transactions, service dependencies, error rates. APM tells you whether the application is working correctly. DEM tells you whether users are getting a good experience.<\/p><p class=\"wp-block-paragraph\">Both matter. But DEM, as most vendors implement it today, has two significant blind spots.<\/p><p class=\"wp-block-paragraph\">First, most DEM tools run synthetic tests from cloud datacenters. That means they&rsquo;re measuring performance from a hyperscaler&rsquo;s infrastructure, not from the locations where real users actually are: mobile networks, home ISPs, enterprise LANs, and last-mile connections across different geographies. A synthetic test originating from a datacenter in Virginia tells you little about the experience of a user on a wireless network in Jakarta.<\/p><p class=\"wp-block-paragraph\">Second, DEM and APM tools treat the Internet between users and applications as a black box. DNS resolution, ISP routing, CDN behavior, BGP path changes, third-party API latency: none of these show up in a typical DEM dashboard. When something goes wrong in that middle layer, DEM tools can tell you there&rsquo;s a problem, but they can&rsquo;t tell you where in the Internet path it&rsquo;s happening or why.<\/p><p class=\"wp-block-paragraph\">These gaps aren&rsquo;t theoretical. They show up regularly in incidents where the root cause turns out to be an ISP routing change, a CDN misconfiguration, or a DNS propagation issue that no internal monitoring tool caught. The user experience degraded, but nothing inside the application or infrastructure looked wrong.<\/p><h2 id=\"h-how-ipm-closes-the-visibility-gap\" class=\"wp-block-heading\">How IPM Closes the Visibility Gap<\/h2><p class=\"wp-block-paragraph\">This is the problem that <a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\">Internet Performance Monitoring (IPM)<\/a> was built to solve.<\/p><p class=\"wp-block-paragraph\">IPM is the practice of analyzing performance across network infrastructure and services that sit outside an organization&rsquo;s direct control but directly affect the health and performance of Internet-delivered applications. That includes BGP routing, CDN behavior, DNS resolution, ISP performance, and the many layers of connectivity between users and the services they depend on.<\/p><p class=\"wp-block-paragraph\">Where DEM monitors the endpoints (the user&rsquo;s experience and the application&rsquo;s behavior), IPM monitors everything in between. It provides visibility into the <a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\">Internet Stack<\/a>: the full set of protocols, services, and infrastructure that applications traverse on the way to users.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"2360\" height=\"933\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/FIGURE-1_-IPM-requires-capabilities-that-most-APM-and-DEM-platforms-dont-offer_.png\" alt=\"\" class=\"wp-image-621533\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/FIGURE-1_-IPM-requires-capabilities-that-most-APM-and-DEM-platforms-dont-offer_.png 2360w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/FIGURE-1_-IPM-requires-capabilities-that-most-APM-and-DEM-platforms-dont-offer_-18x7.png 18w\" sizes=\"auto, (max-width: 2360px) 100vw, 2360px\"><\/figure><p class=\"wp-block-paragraph\">IPM requires capabilities that most APM and DEM platforms don&rsquo;t offer:<\/p><ul class=\"wp-block-list\">\n<li><strong>Thousands of real-world vantage points.<\/strong> Backbone, wireless, last-mile, and enterprise nodes that reflect where users actually connect, not where cloud providers host their infrastructure.<\/li>\n\n\n\n<li><strong>Specialized protocol monitoring.<\/strong> Dedicated tools for BGP, DNS, and protocols like MQTT, HTTP\/3, and ECN that affect performance at different layers of the Internet Stack.<\/li>\n\n\n\n<li><strong>Full-stack Internet visibility.<\/strong> Coverage from ISPs and CDNs to BGP networks, with insight into how performance varies across geographies and network conditions.<\/li>\n<\/ul><p class=\"wp-block-paragraph\">In practice, IPM encompasses DEM while extending visibility deeper into the Internet layer. It doesn&rsquo;t replace synthetic monitoring or RUM. It adds the context that those tools miss: what&rsquo;s happening in the network path between the application and the user, and how those conditions affect the experience.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1200\" height=\"600\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-43.png\" alt=\"\" class=\"wp-image-617577\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-43.png 1200w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-43-18x9.png 18w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\"><\/figure><h3 id=\"h-what-a-strong-ipm-platform-enables\" class=\"wp-block-heading\">What a Strong IPM Platform Enables<\/h3><p class=\"wp-block-paragraph\">When IPM is done well, IT operations and SRE teams gain capabilities that neither APM nor DEM can deliver on their own:<\/p><ul class=\"wp-block-list\">\n<li><strong>Real-world experience benchmarking<\/strong> using single-homed vantage points across backbone, wireless, last-mile, and enterprise nodes, combined with front-end performance testing from a browser&rsquo;s perspective.<\/li>\n\n\n\n<li><strong>Proactive issue identification<\/strong> that catches Internet-layer problems before they reach users.<\/li>\n\n\n\n<li><strong>Faster triage and resolution<\/strong> through reduced Mean Time to Identify (MTTI) and Mean Time to Resolve (MTTR), because teams can pinpoint whether an issue is in the application, the infrastructure, or the Internet path.<\/li>\n\n\n\n<li><strong>Deep Internet layer visibility<\/strong> into every component from ISPs and CDNs to BGP networks, with performance data across geographies and network conditions.<\/li>\n\n\n\n<li><strong>AI-powered correlation<\/strong> through tools like <a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-health\">Internet Sonar<\/a>, which identifies root causes across Internet-layer signals.<\/li>\n\n\n\n<li><strong>User-to-code visibility<\/strong> in a single platform, connecting the full path from user experience through Internet dependencies to application and infrastructure behavior.<\/li>\n\n\n\n<li><strong>Experience Level Objectives (XLOs)<\/strong> that tie experience-level metrics to business expectations, helping match IT performance to the outcomes the organization cares about.<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">Gartner positioned Catchpoint as a Leader in the <a href=\"https:\/\/www.logicmonitor.com\/resources\/gartner-magic-quadrant-dem\">2025 Magic Quadrant for Digital Experience Monitoring<\/a> for the second consecutive year and recognized Catchpoint as the highest-ranked vendor for the ITOps Use Case.<\/p><h2 id=\"h-the-destination-autonomous-it\" class=\"wp-block-heading\">The Destination: Autonomous IT<\/h2><p class=\"wp-block-paragraph\">Bringing DEM, IPM, and APM together solves the visibility problem. But visibility alone doesn&rsquo;t close incidents faster or reduce the operational load on IT teams. The real goal is closing the loop from detection to resolution with intelligent automation.<\/p><p class=\"wp-block-paragraph\">That&rsquo;s the direction LogicMonitor is building toward with its Autonomous IT vision: three platform layers operating as one system.<\/p><ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.logicmonitor.com\/fr\/platform\"><strong>LM Envision<\/strong><\/a> provides hybrid infrastructure observability and APM, covering networks, servers, cloud, containers, applications, and distributed tracing.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\"><strong>LM Internet Performance Monitoring<\/strong><\/a>, powered by Catchpoint, provides Internet and experience visibility, including Real User Monitoring, synthetic monitoring, Session Replay, <a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-health\">Internet Sonar<\/a>, BGP Monitoring, and a global agent network spanning thousands of vantage points.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/fr\/edwin-ai\"><strong>Edwin AI<\/strong><\/a> provides the intelligence layer: anomaly detection, root cause analysis, alert noise reduction, and governed automation.<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">What makes this architecture different from stitching together separate tools is that all three layers share one telemetry pipeline, one context graph, and one intelligence layer. When Catchpoint detects a BGP route change affecting users in a specific region, that signal is available to Edwin AI alongside APM traces from LM Envision showing increased error rates in the same region. The correlation happens automatically, not through a human analyst manually pivoting between dashboards.<\/p><p class=\"wp-block-paragraph\">The practical outcomes matter more than the architecture:<\/p><ul class=\"wp-block-list\">\n<li><strong>Faster triage.<\/strong> When an incident fires, teams see the full path from user experience through Internet dependencies to application and infrastructure behavior, all in one view. They don&rsquo;t spend the first 30 minutes figuring out which tool to open.<\/li>\n\n\n\n<li><strong>Less tool sprawl.<\/strong> One platform replaces the patchwork of point solutions for infrastructure monitoring, APM, synthetic monitoring, RUM, and Internet visibility.<\/li>\n\n\n\n<li><strong>Reduced alert fatigue.<\/strong> Edwin AI deduplicates events, correlates related signals, and surfaces what matters. Teams respond to incidents, not noise.<\/li>\n\n\n\n<li><strong>Governed automation.<\/strong> Remediation workflows come with approvals, audit trails, and rollback capabilities built in. Automation that&rsquo;s production-ready, not just demo-ready.<\/li>\n<\/ul><h2 id=\"h-what-comes-next\" class=\"wp-block-heading\">What Comes Next<\/h2><p class=\"wp-block-paragraph\">The convergence of DEM, IPM, and APM within an AI-first platform represents where IT operations is heading. The monitoring categories that Gartner and the industry defined separately are merging into a unified discipline: understanding the full digital path from user to code, applying intelligence to that data, and acting on it with speed and confidence.<\/p><p class=\"wp-block-paragraph\">LogicMonitor&rsquo;s approach, combining LM Envision, Catchpoint, and Edwin AI into one system, is built for that convergence. It gives IT teams the visibility, intelligence, and governed automation to move from reactive firefighting toward resilient, increasingly autonomous operations.<\/p><p class=\"wp-block-paragraph\">The technology is here. The question for IT leaders is whether their current monitoring stack can get them there, or whether the fragmentation they&rsquo;re managing today is the thing holding them back.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-calendar-check\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xxs fs-md-text-display-xs fs-lg-text-display-sm font-medium text-core-blue-900\">\n        See the Full Path from User Experience to Application Code      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900\">\n        <p>LogicMonitor combines infrastructure observability, Internet performance monitoring, and AI-driven intelligence in one platform. Stop pivoting between dashboards and start resolving incidents faster.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/catchpoint-demo\" class=\"btn btn-link\" target=\"_self\">\n        Demander une d\u00e9monstration          <span class=\"icon-end\"><svg class=\"\" width=\"20px\" height=\"20px\" style=\"fill: #060F4B\">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-arrow-right\"><\/use>\n    <\/svg><\/span>\n      <\/a>\n        <\/div>\n            <\/div>\n<\/div><h4 id=\"h-faqs\" class=\"wp-block-heading\">FAQ<\/h4><div class=\"accordion-block accordion-block--light\">\n      <div class=\"accordion-block__items\">\n              <div class=\"accordion-block__item active\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-what-is-the-difference-between-dem-apm-and-ipm\">\n            What is the difference between DEM, APM, and IPM?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer active\">\n            <p>DEM measures the quality of user experience through synthetic tests, real user monitoring, and endpoint monitoring. APM focuses on application internals like code execution, backend transactions, and error rates. IPM monitors the Internet layer between users and applications, covering DNS, BGP routing, CDN performance, and ISP behavior that neither DEM nor APM can see.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-why-do-dem-tools-miss-internet-layer-problems\">\n            Why do DEM tools miss Internet-layer problems?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>Most DEM tools run synthetic tests from cloud datacenters, which only reflect hyperscaler performance rather than real user conditions on mobile networks, home ISPs, or enterprise LANs. They also treat the Internet path as a black box, so issues like ISP routing changes, CDN misconfigurations, or DNS propagation failures go undetected.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-does-logicmonitor-unify-dem-ipm-and-apm\">\n            How does LogicMonitor unify DEM, IPM, and APM?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>LogicMonitor brings together LM Envision for hybrid infrastructure and APM, Catchpoint-powered IPM for Internet and experience visibility, and Edwin AI for anomaly detection and root cause analysis. All three layers share one telemetry pipeline and context graph, enabling automatic correlation across user experience, Internet dependencies, and application behavior.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div>","protected":false},"excerpt":{"rendered":"<p>D\u00e9couvrez comment l'IPM comble le foss\u00e9 entre la DEM et l'APM, offrant aux \u00e9quipes informatiques une visibilit\u00e9 compl\u00e8te, de l'exp\u00e9rience utilisateur et des d\u00e9pendances Internet jusqu'au code des applications.<\/p>","protected":false},"author":16,"featured_media":621531,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[5035],"tags":[7865,7850,7867,7851,7859,7864,7907,7752,7863,7018],"industry":[7523],"role":[6786],"lm_strategic_tags":[],"topic":[7842],"class_list":["post-617575","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-technology","role-itops","topic-internet-performance-monitoring"],"acf":{"page_language":"english","translated_pages":"","updated_date":null,"author_section_checkbox":true,"author_image":617027,"author_linkedin":"https:\/\/www.linkedin.com\/in\/denton-chikura-422186201\/","author_name":"Denton Chikura","author_job_title":"Technical Writer","author_dept":"","author_bio":"Denton Chikura is a technical writer and longtime observability advocate focused on helping site reliability engineers and engineering teams discover the tools and capabilities that strengthen internet resilience. He works at the intersection of monitoring, performance, and infrastructure to make complex systems more understandable and usable, bridging the gap between deep technical detail and real\u2011world operations. His goal is to help teams build faster, detect issues earlier, and recover smarter, ultimately making the internet a better, more reliable place for everyone.","reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.2 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>DEM, IPM, and APM: A Guide to Modern IT Monitoring | LogicMonitor<\/title>\n<meta name=\"description\" content=\"Discover how IPM enhances digital experience monitoring, filling gaps left by traditional APM and DEM to ensure Internet Resilience.\" \/>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Monitoring in the Age of the Internet: DEM, IPM, and APM: What You Need to Know\" \/>\n<meta property=\"og:description\" content=\"Discover how IPM enhances digital experience monitoring, filling gaps left by traditional APM and DEM to ensure Internet Resilience.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.logicmonitor.com\/fr\/blog\/monitoring-in-the-age-of-the-internet-dem-ipm-and-apm-what-you-need-to-know\" \/>\n<meta property=\"og:site_name\" content=\"LogicMonitor\" \/>\n<meta property=\"article:published_time\" content=\"2026-08-11T22:09:43+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-08-11T22:09:44+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/Blog_Monitoring-in-the-Age-of-the-Internet-DEM-IPM-and-APM-What-You-Need-to-Know_Meta-1600x900px.png\" \/>\n\t<meta property=\"og:image:width\" content=\"2400\" \/>\n\t<meta property=\"og:image:height\" content=\"1350\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"destiny.setzer@logicmonitor.com\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" 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minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.logicmonitor.com\/fr\/blog\/monitoring-in-the-age-of-the-internet-dem-ipm-and-apm-what-you-need-to-know#article","isPartOf":{"@id":"https:\/\/www.logicmonitor.com\/fr\/blog\/monitoring-in-the-age-of-the-internet-dem-ipm-and-apm-what-you-need-to-know"},"author":{"name":"destiny.setzer@logicmonitor.com","@id":"https:\/\/www.logicmonitor.com\/fr\/#\/schema\/person\/bfbb8cb00c9595482098c66aa78b9def"},"headline":"Monitoring in the Age of the Internet: DEM, IPM, and APM: What You Need to Know","datePublished":"2026-08-11T22:09:43+00:00","dateModified":"2026-08-11T22:09:44+00:00","mainEntityOfPage":{"@id":"https:\/\/www.logicmonitor.com\/fr\/blog\/monitoring-in-the-age-of-the-internet-dem-ipm-and-apm-what-you-need-to-know"},"wordCount":1346,"image":{"@id":"https:\/\/www.logicmonitor.com\/fr\/blog\/monitoring-in-the-age-of-the-internet-dem-ipm-and-apm-what-you-need-to-know#primaryimage"},"thumbnailUrl":"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/Blog_Monitoring-in-the-Age-of-the-Internet-DEM-IPM-and-APM-What-You-Need-to-Know_940x600_Featured-Image.png","keywords":["BGP Monitoring","Catchpoint","CDN Monitoring","DNS Monitoring","Endpoint Monitoring","Internet Sonar","ISP Performance","LM Envision","Network Path Analysis","synthetics"],"articleSection":["Blog"],"inLanguage":"fr-FR"},{"@type":"WebPage","@id":"https:\/\/www.logicmonitor.com\/fr\/blog\/monitoring-in-the-age-of-the-internet-dem-ipm-and-apm-what-you-need-to-know","url":"https:\/\/www.logicmonitor.com\/fr\/blog\/monitoring-in-the-age-of-the-internet-dem-ipm-and-apm-what-you-need-to-know","name":"DEM, IPM, and APM: A Guide to Modern IT Monitoring | LogicMonitor","isPartOf":{"@id":"https:\/\/www.logicmonitor.com\/fr\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.logicmonitor.com\/fr\/blog\/monitoring-in-the-age-of-the-internet-dem-ipm-and-apm-what-you-need-to-know#primaryimage"},"image":{"@id":"https:\/\/www.logicmonitor.com\/fr\/blog\/monitoring-in-the-age-of-the-internet-dem-ipm-and-apm-what-you-need-to-know#primaryimage"},"thumbnailUrl":"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/Blog_Monitoring-in-the-Age-of-the-Internet-DEM-IPM-and-APM-What-You-Need-to-Know_940x600_Featured-Image.png","datePublished":"2026-08-11T22:09:43+00:00","dateModified":"2026-08-11T22:09:44+00:00","author":{"@id":"https:\/\/www.logicmonitor.com\/fr\/#\/schema\/person\/bfbb8cb00c9595482098c66aa78b9def"},"description":"Discover how IPM enhances digital experience monitoring, filling gaps left by traditional APM and DEM to ensure Internet 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des pannes Wi-Fi manqu\u00e9es par les outils traditionnels : une \u00e9tude de cas"},"content":{"rendered":"<?xml encoding=\"UTF-8\"><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50 rtc-text-content--no-top-pad\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-book-open\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xs fs-md-text-display-sm fs-lg-text-display-md font-medium text-core-blue-900\">\n        Le t\u00e9l\u00e9chargement rapide :      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900 headline-is-quote\">\n        <p>Endpoint monitoring revealed the Wi-Fi blind spot that kept crashing a global airline&rsquo;s Google Meet calls.<\/p>\n      <\/div>\n    \n                  <ul class=\"rtc-text-content__bullet-list\">\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Catchpoint agents pinpointed 5GHz Channel 44 signal strength dropping to -80 dBm, well below the -70 dBm floor for reliable real-time communication.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Traditional tools (Splunk, ThousandEyes) confirmed the network was healthy, but couldn&rsquo;t instrument the last few meters between access points and user devices.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Correlating Wi-Fi telemetry with Google Meet response times gave the team direct proof of where and why performance degraded.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>If your users are reporting call quality issues and your network dashboards look clean, start measuring at the endpoint.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p class=\"wp-block-paragraph\"><br>The IT team at a global airline kept getting the same complaint: Google Meet calls were dropping, audio was cutting out, and nobody could figure out why. Network diagnostics came back clean. Their APM tool showed no anomalies along the network path. From every angle the team could measure, the infrastructure looked fine. But the complaints kept coming.<\/p><h2 id=\"h-the-complaint-nobody-could-explain\" class=\"wp-block-heading\">The Complaint Nobody Could Explain<\/h2><p class=\"wp-block-paragraph\">Dropped calls and degraded audio on Google Meet had become a recurring problem. The airline&rsquo;s IT team ran the standard playbook: check the network, check the infrastructure, look for congestion or packet loss. Nothing surfaced. Tools like Cisco&rsquo;s Splunk and ThousandEyes showed the broader network operating normally, but they couldn&rsquo;t see what was happening at the device level, specifically the Wi-Fi connection between a user&rsquo;s laptop and the nearest access point.<\/p><p class=\"wp-block-paragraph\">That gap left the team stuck. They knew something was wrong because users kept reporting it. They just couldn&rsquo;t see where.<\/p><h2 id=\"h-deploying-endpoint-agents\" class=\"wp-block-heading\">Deploying Endpoint Agents<\/h2><p class=\"wp-block-paragraph\">During a proof-of-concept, the team deployed Catchpoint <a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\">Supervision des performances Internet<\/a>, part of the LogicMonitor platform, installing endpoint agents across multiple machines. These agents collected Wi-Fi telemetry that traditional monitoring tools don&rsquo;t capture:<\/p><ul class=\"wp-block-list\">\n<li>Wi-Fi channel and band (2.4GHz vs. 5GHz)<\/li>\n\n\n\n<li>Signal strength in dBm<\/li>\n\n\n\n<li>Connection quality at the device level<\/li>\n\n\n\n<li>Google Meet response times tied to specific endpoints<\/li>\n<\/ul><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1204\" height=\"752\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-42.png\" alt=\"\" class=\"wp-image-617570\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-42.png 1204w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-42-18x12.png 18w\" sizes=\"auto, (max-width: 1204px) 100vw, 1204px\"><\/figure><p class=\"wp-block-paragraph\"><em>Catchpoint endpoint metrics including Wi-Fi signal strength, CPU usage, and system details at the device level.<\/em><\/p><p class=\"wp-block-paragraph\">The difference was granularity. Endpoint telemetry captured what was happening between the user and the access point, the one segment of the path that network-level tools don&rsquo;t instrument. That made it possible to correlate Wi-Fi conditions with the application performance users were actually experiencing.<\/p><h2 id=\"h-what-the-data-showed\" class=\"wp-block-heading\">What the Data Showed<\/h2><p class=\"wp-block-paragraph\">The endpoint data revealed a clear split between Wi-Fi bands. The 2.4GHz band consistently delivered stronger signal strength than 5GHz, pointing to environmental interference with the higher-frequency band.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1160\" height=\"624\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-40.png\" alt=\"\" class=\"wp-image-617568\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-40.png 1160w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-40-18x10.png 18w\" sizes=\"auto, (max-width: 1160px) 100vw, 1160px\"><\/figure><p class=\"wp-block-paragraph\"><em>Wi-Fi band signal strength comparison across endpoints.<\/em><\/p><p class=\"wp-block-paragraph\">Channel 44 on the 5GHz band stood out. Endpoints connected to that channel showed noticeably slower Google Meet response times. Meanwhile, endpoints on 2.4GHz channels had stronger signals and fewer user complaints.<\/p><h2 id=\"h-the-5ghz-problem\" class=\"wp-block-heading\">The 5GHz Problem<\/h2><p class=\"wp-block-paragraph\">Signal strength analysis made the issue concrete. Optimal Wi-Fi signal sits between -30 and -50 dBm. Below -70 dBm, performance degrades noticeably. Agents recorded signal strength dropping to -80 dBm on Channel 44 during the periods users were reporting problems.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1212\" height=\"604\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-41.png\" alt=\"\" class=\"wp-image-617569\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-41.png 1212w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-41-18x9.png 18w\" sizes=\"auto, (max-width: 1212px) 100vw, 1212px\"><\/figure><p class=\"wp-block-paragraph\"><em>Signal strength measurements showing the drop to -80 dBm on affected endpoints.<\/em><\/p><p class=\"wp-block-paragraph\">On the 24th, a specific user experiencing meeting disruptions recorded signal strength at -80 dBm, well below the threshold where real-time communication applications can maintain quality. The correlation was direct: the weaker the Wi-Fi signal on 5GHz Channel 44, the worse Google Meet performed.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1244\" height=\"404\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-39.png\" alt=\"\" class=\"wp-image-617567\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-39.png 1244w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-39-18x6.png 18w\" sizes=\"auto, (max-width: 1244px) 100vw, 1244px\"><\/figure><p class=\"wp-block-paragraph\"><em>Google Meet response time spike correlated with signal strength degradation.<\/em><\/p><p class=\"wp-block-paragraph\">This behavior is consistent with known 5GHz characteristics. Higher-frequency Wi-Fi signals have shorter range and are more susceptible to physical obstacles (walls, partitions, furniture). In an office environment with multiple barriers between users and access points, 5GHz connections can degrade significantly depending on location, something that only shows up when you&rsquo;re measuring at the endpoint.<\/p><h2 id=\"h-what-endpoint-monitoring-found-that-other-tools-missed\" class=\"wp-block-heading\">What Endpoint Monitoring Found That Other Tools Missed<\/h2><p class=\"wp-block-paragraph\">The root cause was a mismatch between the office&rsquo;s physical layout and its Wi-Fi infrastructure. Users connecting through 5GHz Channel 44 were too far from access points, or had too many obstacles in the path, for the higher-frequency band to maintain adequate signal strength. Traditional monitoring confirmed the network itself was healthy, which was accurate. The problem was in the last few meters between the access point and the user&rsquo;s device.<\/p><p class=\"wp-block-paragraph\">Catchpoint endpoint monitoring surfaced this because it measures at the device level: actual signal strength, the specific channel and band in use, and the application response times happening over that connection. That combination let the team draw a direct line from Wi-Fi conditions to the user experience problems they&rsquo;d been hearing about for weeks.<\/p><p class=\"wp-block-paragraph\">To be clear about scope: this investigation identified the root cause, not the fix. The data pointed to where the problem was and why it was happening. Remediation (access point repositioning, channel management, band steering) is a separate step that depends on the airline&rsquo;s infrastructure team and planning process. The value of endpoint monitoring here was pinpointing a problem that no other tool in their stack could see.<\/p><h2 id=\"h-what-it-teams-can-take-away\" class=\"wp-block-heading\">What IT Teams Can Take Away<\/h2><p class=\"wp-block-paragraph\">This case is a useful example of a common blind spot. When application performance degrades and network diagnostics come back clean, the issue may sit in the Wi-Fi layer between the device and the access point. Most enterprise monitoring stacks don&rsquo;t instrument that segment.<\/p><p class=\"wp-block-paragraph\">For teams dealing with similar complaints, a few practical points stand out:<\/p><ul class=\"wp-block-list\">\n<li><strong>Instrument the endpoint.<\/strong> Wi-Fi telemetry at the device level (signal strength, channel, band) fills the gap between application monitoring and network monitoring.<\/li>\n\n\n\n<li><strong>Set signal strength thresholds.<\/strong> Knowing that -70 dBm is the floor for reliable real-time communication gives teams a concrete number to alert on, rather than waiting for user complaints.<\/li>\n\n\n\n<li><strong>Correlate Wi-Fi data with application performance.<\/strong> Signal strength alone doesn&rsquo;t tell the full story. Tying it to response times for specific applications like Google Meet makes the data useful for diagnosis.<\/li>\n\n\n\n<li><strong>Factor Wi-Fi coverage into infrastructure planning.<\/strong> Access point placement decisions benefit from real usage data, specifically where 5GHz coverage falls short given the physical environment.<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">This kind of endpoint-to-application visibility is central to how LogicMonitor approaches IT operations. By connecting <a href=\"https:\/\/www.logicmonitor.com\/fr\/infrastructure-monitoring\">LM Envision<\/a>,<a href=\"https:\/\/www.logicmonitor.com\/fr\/logicmonitor-catchpoint\"> Point de rattrapage<\/a>, et <a href=\"https:\/\/www.logicmonitor.com\/fr\/edwin-ai\">Edwin AI<\/a> in one platform, LogicMonitor gives teams the context to see problems across the full path from user to infrastructure, including the segments that traditional tools miss.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50 rtc-text-content--no-top-pad\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-calendar-check\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xxs fs-md-text-display-xs fs-lg-text-display-sm font-medium text-core-blue-900\">\n        See the Wi-Fi blind spots your current monitoring stack can't reach.      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900\">\n        <p>LogicMonitor delivers device-level Wi-Fi telemetry correlated with application performance, so you can diagnose issues in minutes instead of weeks.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/catchpoint-demo\" class=\"btn btn-link\" target=\"_self\">\n        Demandez une d\u00e9mo          <span class=\"icon-end\"><svg class=\"\" width=\"20px\" height=\"20px\" style=\"fill: #060F4B\">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-arrow-right\"><\/use>\n    <\/svg><\/span>\n      <\/a>\n        <\/div>\n            <\/div>\n<\/div><h4 id=\"h-faqs\" class=\"wp-block-heading\">FAQ<\/h4><div class=\"accordion-block accordion-block--light\">\n      <div class=\"accordion-block__items\">\n              <div class=\"accordion-block__item active\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-why-cant-traditional-network-monitoring-tools-detect-wi-fi-signal-issues\">\n            Why can't traditional network monitoring tools detect Wi-Fi signal issues?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer active\">\n            <p>Tools like ThousandEyes and Splunk monitor network infrastructure at the path and node level. They confirm whether routers, switches, and links are healthy. However, they do not instrument the wireless connection between a user&rsquo;s device and the nearest access point, which is where signal strength, channel interference, and band-specific degradation occur.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-what-wi-fi-metrics-should-it-teams-monitor-for-real-time-communication-apps\">\n            What Wi-Fi metrics should IT teams monitor for real-time communication apps?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>Teams should track signal strength (in dBm), the specific Wi-Fi channel and band (2.4GHz vs. 5GHz), and connection quality at the device level. Correlating these metrics with application response times for tools like Google Meet provides actionable diagnostic data. Signal strength below -70 dBm typically degrades real-time communication quality.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-does-5ghz-wi-fi-differ-from-2-4ghz-in-office-environments\">\n            How does 5GHz Wi-Fi differ from 2.4GHz in office environments?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>5GHz Wi-Fi offers faster speeds but has shorter range and is more susceptible to physical obstacles such as walls, partitions, and furniture. In offices with multiple barriers between users and access points, 5GHz connections can degrade significantly depending on location, while 2.4GHz maintains stronger signal strength over longer distances.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div>","protected":false},"excerpt":{"rendered":"<p>Les appels Google Meet d'une compagnie a\u00e9rienne mondiale n'arr\u00eataient pas de couper. La surveillance des terminaux a r\u00e9v\u00e9l\u00e9 des pannes de signal Wi-Fi 5 GHz que les outils de r\u00e9seau traditionnels ne pouvaient pas d\u00e9tecter.<\/p>","protected":false},"author":16,"featured_media":621528,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[5035],"tags":[7850,7859,7863,7917,6677,7890,7084,7860,7838],"industry":[7524],"role":[6786],"lm_strategic_tags":[],"topic":[7842],"class_list":["post-617566","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-transportation-logistics","role-itops","topic-internet-performance-monitoring"],"acf":{"page_language":"english","translated_pages":"","updated_date":null,"author_section_checkbox":true,"author_image":617027,"author_linkedin":"https:\/\/www.linkedin.com\/in\/denton-chikura-422186201\/","author_name":"Denton Chikura","author_job_title":"Technical Writer","author_dept":"","author_bio":"Denton Chikura is a technical writer and longtime observability advocate focused on helping site reliability engineers and engineering teams discover the tools and capabilities that strengthen internet resilience. He works at the intersection of monitoring, performance, and infrastructure to make complex systems more understandable and usable, bridging the gap between deep technical detail and real\u2011world operations. His goal is to help teams build faster, detect issues earlier, and recover smarter, ultimately making the internet a better, more reliable place for everyone.","reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.2 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>How Endpoint Monitoring Solved Wi-Fi Issues Network Tools Missed | LogicMonitor<\/title>\n<meta name=\"description\" content=\"Discover how endpoint monitoring exposed Wi-Fi signal drops that disrupted Google Meet\u2014enabling fast fixes where traditional tools failed\" \/>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Diagnosing Wi-Fi Failures That Traditional Tools Miss: A Case Study\" \/>\n<meta property=\"og:description\" content=\"Discover how endpoint monitoring exposed Wi-Fi signal drops that disrupted Google Meet\u2014enabling fast fixes where traditional tools failed\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.logicmonitor.com\/fr\/blog\/diagnosing-wi-fi-failures-that-traditional-tools-miss-a-case-study\" \/>\n<meta property=\"og:site_name\" content=\"LogicMonitor\" \/>\n<meta property=\"article:published_time\" content=\"2026-08-11T22:08:22+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-08-11T22:08:23+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/Blog_Diagnosing-Wi-Fi-Failures-That-Traditional-Tools-Miss-A-Case-Study_Meta-1600x900px.png\" \/>\n\t<meta property=\"og:image:width\" content=\"2400\" \/>\n\t<meta property=\"og:image:height\" content=\"1350\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"destiny.setzer@logicmonitor.com\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" 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agentique : Puissante mais fragile \u2014 Ce que vous devez savoir"},"content":{"rendered":"<?xml encoding=\"UTF-8\"><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-book-open\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xs fs-md-text-display-sm fs-lg-text-display-md font-medium text-core-blue-900\">\n        Le t\u00e9l\u00e9chargement rapide :      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900 headline-is-quote\">\n        <p>Every new AI dependency is a new point of failure, and most teams can&rsquo;t see where the break is.<\/p>\n      <\/div>\n    \n                  <ul class=\"rtc-text-content__bullet-list\">\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Internet disruptions already cause significant revenue loss across industries, and agentic AI multiplies that exposure with every added dependency.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Failures can originate anywhere along the path from user device to AI model endpoint, including DNS, CDN, cloud infrastructure, and third-party APIs.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Teams that recover fastest have unified, end-to-end visibility across the full chain, from user to code.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Map your AI dependencies today and implement continuous monitoring before the next outage catches your team blind.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p class=\"wp-block-paragraph\"><br>Agentic AI marks a significant shift in how enterprises use artificial intelligence. Unlike traditional AI systems that assist human decision-making, <a href=\"https:\/\/www.logicmonitor.com\/blog\/what-is-an-ai-agent\">IA agentique<\/a> acts on its own, making decisions, handling tasks, and communicating with other systems without waiting for human input. It&rsquo;s already reshaping supply chains and customer experiences. But these autonomous agents depend on a web of third-party services, and&nbsp;when <a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-health\">one fails, everything stops<\/a>.<\/p><p class=\"wp-block-paragraph\">A <a href=\"https:\/\/www.logicmonitor.com\/resources\/forrester-opportunity-snapshot-increase-revenue-with-internet-performance-monitoring\">study of eCommerce companies<\/a> found that 88% of respondents lost more than $100,000 in a single month due to Internet disruptions. As agentic AI expands, each new dependency multiplies the chance of downtime. When AI fails, operations halt, revenues drop, and reputations suffer.<\/p><p class=\"wp-block-paragraph\">The path forward requires visibility, not just into your own systems, but across the full path from the end user&rsquo;s device, through Internet infrastructure (DNS, CDN, cloud providers), through your internal application stack, all the way to the third-party AI model endpoint. Without that kind of user-to-code visibility, diagnosing and recovering from failures is slow, costly, and frustrating for both teams and the customers who depend on those services.<\/p><h2 id=\"h-the-promise-of-autonomy\" class=\"wp-block-heading\">The Promise of Autonomy<\/h2><p class=\"wp-block-paragraph\">Traditional AI systems rely on human oversight for most decisions. Agentic AI goes further. These autonomous agents handle tasks, make decisions, and interact with external systems independently. From automating supply chains to personalizing customer service, the potential is significant.<\/p><p class=\"wp-block-paragraph\">But these agents depend on a network of external services, and even a small disruption in one can cascade across the entire workflow. When the chain breaks, the fallout is immediate.<\/p><h2 id=\"h-the-hidden-pitfalls-of-agentic-ai\" class=\"wp-block-heading\">The Hidden Pitfalls of Agentic AI<\/h2><p class=\"wp-block-paragraph\">Recent AI outages have shown how fragile interconnected technology can be. Agentic AI agents pull data from multiple external services, each of which introduces a new point of failure. When something goes wrong, pinpointing the issue requires<a href=\"https:\/\/www.logicmonitor.com\/blog\/what-is-agentic-observability\"> end-to-end observability across agent workflows<\/a> that most monitoring tools can&rsquo;t provide. Without it, teams are left diagnosing the problem while operations grind to a halt.<\/p><p class=\"wp-block-paragraph\">The core challenge is that failures can originate at any point along a complex path: from the end user&rsquo;s device, through DNS resolution and CDN routing, through cloud infrastructure and internal services, all the way to a third-party AI model endpoint. Most monitoring tools only see part of that path. Teams that recover fastest are the ones with visibility across the full chain, from user to code.<\/p><p class=\"wp-block-paragraph\">Consider a financial services firm relying on AI-powered agents to handle customer inquiries about transactions and investments. The customer-facing chatbot calls an internal API gateway, which in turn calls a payment processor, a portfolio data service, and an LLM inference endpoint. That LLM endpoint depends on a third-party model provider API, which relies on a specific CDN and DNS resolution chain.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1536\" height=\"1024\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-35.png\" alt=\"\" class=\"wp-image-617231\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-35.png 1536w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-35-18x12.png 18w\" sizes=\"auto, (max-width: 1536px) 100vw, 1536px\"><\/figure><p class=\"wp-block-paragraph\"><em>A single user request triggers a complex chain of dependencies<\/em><\/p><p class=\"wp-block-paragraph\">When the CDN provider has a routing issue, the LLM endpoint times out, the chatbot returns errors, and the firm&rsquo;s customer portal goes down. The operations team sees the chatbot failing but can&rsquo;t immediately tell whether the problem is in their own infrastructure, at the model provider, or somewhere in the Internet path between them. In an industry like financial services, every minute of that uncertainty erodes customer trust and pushes clients toward competitors.<\/p><p class=\"wp-block-paragraph\">Without a unified view of AI agent dependencies, recovery is slow and costly. Teams end up in inefficient war-room sessions, cycling through possible causes while frustration builds internally and among customers who rely on seamless service.<\/p><h2 id=\"h-building-resilient-agentic-ai-capabilities-and-practical-steps\" class=\"wp-block-heading\">Building Resilient Agentic AI: Capabilities and Practical Steps<\/h2><p class=\"wp-block-paragraph\">Protecting your agentic AI systems from disruptions requires proactive monitoring across the full technology stack. That means understanding your AI dependencies and being able to identify where failures emerge, from internal services to external APIs to the Internet layers in between.<\/p><p class=\"wp-block-paragraph\">Five capabilities matter most:<\/p><ol class=\"wp-block-list\">\n<li><strong>Map your AI dependencies<\/strong><strong><br><\/strong> Start by<a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-stack-map\"> mapping all the dependencies your AI agents rely on<\/a>. Visualize every microservice, API, content delivery network (CDN), and DNS route in an interactive, real-time map. Internet Stack Map gives you a live view of the entire ecosystem your AI depends on, so you can immediately identify issues that affect performance and improve both Mean Time to Identify (MTTI) and Mean Time to Repair (MTTR).<\/li>\n<\/ol><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1179\" height=\"766\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-33.png\" alt=\"\" class=\"wp-image-617229\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-33.png 1179w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-33-18x12.png 18w\" sizes=\"auto, (max-width: 1179px) 100vw, 1179px\"><\/figure><p class=\"wp-block-paragraph\"><em>Carte de la pile Internet<\/em><\/p><ol start=\"2\" class=\"wp-block-list\">\n<li><strong>Monitor continuously<br><\/strong> Keep your AI systems performing well by implementing continuous<a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\"> Internet performance monitoring<\/a>. With real-time, proactive monitoring, you can simulate user journeys and detect anomalies before they escalate. This covers every layer of the Internet Stack, the collection of technologies, systems, and services that make possible and impact every digital user experience, from the core Internet systems like BGP, network technologies like TCP\/IP, security technologies like SASE, protocols like QUIC or POP, cloud services, third party dependencies including APIs and web services, and SaaS applications.<\/li>\n<\/ol><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"2475\" height=\"1370\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/FIGURE-3_-Internet-Stack.png\" alt=\"\" class=\"wp-image-621526\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/FIGURE-3_-Internet-Stack.png 2475w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/FIGURE-3_-Internet-Stack-18x10.png 18w\" sizes=\"auto, (max-width: 2475px) 100vw, 2475px\"><\/figure><p class=\"wp-block-paragraph\"><em>The Internet Stack<\/em><\/p><p class=\"wp-block-paragraph\">By staying ahead of potential disruptions, you can quickly pinpoint problems and maintain optimal service availability, minimizing downtime and improving the user experience.<\/p><ol start=\"3\" class=\"wp-block-list\">\n<li><strong>Leverage automation tools for end-to-end workflow testing<\/strong><strong><br><\/strong> Use automation tools like<a href=\"https:\/\/www.logicmonitor.com\/platform\/synthetic-monitoring\"> Playwright<\/a> to simulate real user interactions across complete workflows. This includes tasks such as adding products to a cart, completing checkout, and engaging with AI-powered agents. By scripting these processes, you can verify that AI performs as expected and identify friction points or performance issues before they reach users.<\/li>\n<\/ol><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1260\" height=\"635\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-32.png\" alt=\"\" class=\"wp-image-617228\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-32.png 1260w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-32-18x9.png 18w\" sizes=\"auto, (max-width: 1260px) 100vw, 1260px\"><\/figure><p class=\"wp-block-paragraph\"><em>End-to-end testing workflow with Playwright<\/em><\/p><ol start=\"4\" class=\"wp-block-list\">\n<li><strong>Correlate signals with AI-driven root cause analysis<br><\/strong> You&rsquo;ve mapped dependencies and you&rsquo;re monitoring continuously. But when an incident hits, you still need to correlate thousands of signals across internal infrastructure, Internet dependencies, and third-party services to find the root cause.<a href=\"https:\/\/www.logicmonitor.com\/fr\/edwin-ai\"> Edwin A<\/a>I is the intelligence layer that makes sense of all that monitoring data, automatically correlating signals across domains, identifying root cause, and recommending next steps so teams can resolve issues in minutes instead of hours.<a href=\"https:\/\/www.logicmonitor.com\/fr\/agentic-aiops-guide\"><br><\/a><\/li>\n\n\n\n<li><strong>Plan for failover and review performance regularly<\/strong><strong><br><\/strong> If a critical AI service fails, you need a fallback plan. Whether it&rsquo;s switching to a backup model or queuing tasks until service is restored, a well-defined failover strategy is essential for minimizing the impact of outages. Pair that with routine performance reviews of your AI dependencies to spot patterns (such as increasing response times or occasional timeouts) that may signal underlying problems before they escalate.<\/li>\n<\/ol><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">LogicMonitor brings together<a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\"> LM Internet Performance Monitoring<\/a>, LM Envision, and<a href=\"https:\/\/www.logicmonitor.com\/fr\/edwin-ai\"> Edwin AI<\/a> into one platform, giving teams the unified visibility they need to stay ahead of disruptions. By combining these capabilities, you can keep your agentic AI systems resilient, proactive, and capable of minimizing downtime. With a clear understanding of your AI workflows, continuous monitoring, and<a href=\"https:\/\/www.logicmonitor.com\/blog\/ai-observability\"> AI observability<\/a> in place, you&rsquo;ll be prepared to manage disruptions and keep your services running smoothly.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-calendar-check\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xxs fs-md-text-display-xs fs-lg-text-display-sm font-medium text-core-blue-900\">\n        See the full dependency chain behind your AI agents before the next outage hits.      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900\">\n        <p>LogicMonitor delivers unified visibility from user to code, so your team can detect, diagnose, and resolve AI disruptions in minutes.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/catchpoint-demo\" class=\"btn btn-link\" target=\"_self\">\n         Demander une d\u00e9monstration          <span class=\"icon-end\"><svg class=\"\" width=\"20px\" height=\"20px\" style=\"fill: #060F4B\">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-arrow-right\"><\/use>\n    <\/svg><\/span>\n      <\/a>\n        <\/div>\n            <\/div>\n<\/div><h4 id=\"h-faqs\" class=\"wp-block-heading\">FAQ<\/h4><div class=\"accordion-block accordion-block--light\">\n      <div class=\"accordion-block__items\">\n              <div class=\"accordion-block__item active\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-why-are-agentic-ai-systems-more-vulnerable-to-outages-than-traditional-ai\">\n            Why are agentic AI systems more vulnerable to outages than traditional AI?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer active\">\n            <p>Agentic AI operates autonomously and relies on chains of external services (APIs, CDNs, DNS, model endpoints) to complete tasks. Each dependency is a potential point of failure, and because the agent acts without human oversight, a single disruption can cascade across an entire workflow before anyone notices.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-what-kind-of-monitoring-do-i-need-for-agentic-ai\">\n            What kind of monitoring do I need for agentic AI?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>You need end-to-end observability that covers the full path from the end user&rsquo;s device through Internet infrastructure and internal services to the third-party AI model endpoint. Continuous synthetic monitoring, dependency mapping, and AI-driven root cause analysis help teams detect and resolve issues before they impact operations.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-can-i-reduce-recovery-time-when-an-ai-agent-fails\">\n            How can I reduce recovery time when an AI agent fails?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>Start by mapping all dependencies your AI agents rely on so you know where to look when something breaks. Implement continuous monitoring to catch anomalies early, use automation to correlate signals across domains, and have a failover plan ready so operations can continue while the root cause is resolved.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div>","protected":false},"excerpt":{"rendered":"<p>Les agents d'IA autonomes reposent sur des cha\u00eenes de d\u00e9pendance fragiles. Apprenez comment une surveillance proactive et de bout en bout pr\u00e9vient les temps d'arr\u00eat co\u00fbteux et maintient les op\u00e9rations en marche.<\/p>","protected":false},"author":16,"featured_media":621523,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[5035],"tags":[7753,5331,5339,7850,7783,7760,7864,7854,6677,7084],"industry":[6790],"role":[6786],"lm_strategic_tags":[],"topic":[6769],"class_list":["post-617226","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-all","role-itops","topic-aiops-automation"],"acf":{"page_language":"english","translated_pages":"","updated_date":null,"author_section_checkbox":true,"author_image":617027,"author_linkedin":"https:\/\/www.linkedin.com\/in\/denton-chikura-422186201\/","author_name":"Denton Chikura","author_job_title":"Technical Writer","author_dept":"","author_bio":"Denton Chikura is a technical writer and longtime observability advocate focused on helping site reliability engineers and engineering teams discover the tools and capabilities that strengthen internet resilience. He works at the intersection of monitoring, performance, and infrastructure to make complex systems more understandable and usable, bridging the gap between deep technical detail and real\u2011world operations. His goal is to help teams build faster, detect issues earlier, and recover smarter, ultimately making the internet a better, more reliable place for everyone.","reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.2 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Agentic AI Risks: How to Prevent Downtime in AI Workflows | LogicMonitor<\/title>\n<meta name=\"description\" content=\"As AI agents take over tasks, each new dependency becomes a risk. Here&#039;s how to prevent downtime with smarter monitoring and planning.\" \/>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Agentic AI: Powerful but Fragile\u2014What You Need to Know\" \/>\n<meta property=\"og:description\" content=\"As AI agents take over tasks, each new dependency becomes a risk. Here&#039;s how to prevent downtime with smarter monitoring and planning.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.logicmonitor.com\/fr\/blog\/agentic-ai-powerful-but-fragile-what-you-need-to-know\" \/>\n<meta property=\"og:site_name\" content=\"LogicMonitor\" \/>\n<meta property=\"article:published_time\" content=\"2026-08-11T22:01:52+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-08-11T22:01:53+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/Blog_Agentic-AI-Powerful-but-Fragile-What-You-Need-to-Know_Meta-1600x900px.png\" \/>\n\t<meta property=\"og:image:width\" content=\"2400\" \/>\n\t<meta property=\"og:image:height\" content=\"1350\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"destiny.setzer@logicmonitor.com\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"6 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/blog\\\/agentic-ai-powerful-but-fragile-what-you-need-to-know#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/blog\\\/agentic-ai-powerful-but-fragile-what-you-need-to-know\"},\"author\":{\"name\":\"destiny.setzer@logicmonitor.com\",\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/#\\\/schema\\\/person\\\/bfbb8cb00c9595482098c66aa78b9def\"},\"headline\":\"Agentic AI: Powerful but Fragile\u2014What You Need to Know\",\"datePublished\":\"2026-08-11T22:01:52+00:00\",\"dateModified\":\"2026-08-11T22:01:53+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/blog\\\/agentic-ai-powerful-but-fragile-what-you-need-to-know\"},\"wordCount\":1112,\"image\":{\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/blog\\\/agentic-ai-powerful-but-fragile-what-you-need-to-know#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.logicmonitor.com\\\/wp-content\\\/uploads\\\/2026\\\/07\\\/Blog_Agentic-AI-Powerful-but-Fragile-What-You-Need-to-Know_940x600_Featured-Image.png\",\"keywords\":[\"AI Agent\",\"alerts\",\"anomaly detection\",\"Catchpoint\",\"dependency mapping\",\"Incident Response\",\"Internet Sonar\",\"Outage Detection\",\"Performance optimization\",\"Troubleshooting\"],\"articleSection\":[\"Blog\"],\"inLanguage\":\"fr-FR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/blog\\\/agentic-ai-powerful-but-fragile-what-you-need-to-know\",\"url\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/blog\\\/agentic-ai-powerful-but-fragile-what-you-need-to-know\",\"name\":\"Agentic AI Risks: How to Prevent Downtime in AI Workflows | LogicMonitor\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/blog\\\/agentic-ai-powerful-but-fragile-what-you-need-to-know#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/blog\\\/agentic-ai-powerful-but-fragile-what-you-need-to-know#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.logicmonitor.com\\\/wp-content\\\/uploads\\\/2026\\\/07\\\/Blog_Agentic-AI-Powerful-but-Fragile-What-You-Need-to-Know_940x600_Featured-Image.png\",\"datePublished\":\"2026-08-11T22:01:52+00:00\",\"dateModified\":\"2026-08-11T22:01:53+00:00\",\"author\":{\"@id\":\"https:\\\/\\\/www.logicmonitor.com\\\/fr\\\/#\\\/schema\\\/person\\\/bfbb8cb00c9595482098c66aa78b9def\"},\"description\":\"As AI agents take over tasks, each new dependency becomes a risk. 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de panne : ce que la panne de Google Cloud a r\u00e9v\u00e9l\u00e9 sur les d\u00e9pendances cach\u00e9es"},"content":{"rendered":"<?xml encoding=\"UTF-8\"><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-book-open\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xs fs-md-text-display-sm fs-lg-text-display-md font-medium text-core-blue-900\">\n        Le t\u00e9l\u00e9chargement rapide :      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900 headline-is-quote\">\n        <p>A routine Google Cloud quota change cascaded into a global outage, proving that no provider is too big to fail.<\/p>\n      <\/div>\n    \n                  <ul class=\"rtc-text-content__bullet-list\">\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>The incident took down 30+ GCP services and disrupted major platforms including Discord, Spotify, and Cloudflare across four continents.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Google&rsquo;s status page lagged nearly an hour behind real-time detection, leaving teams without confirmation while services burned.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Independent, cloud-external monitoring flagged anomalies within one minute, well before any official acknowledgment.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Audit your monitoring stack today: if it lives inside the cloud you&rsquo;re watching, it will go dark when you need it most.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p class=\"wp-block-paragraph\"><br>On June 12, 2025, an automated quota change in Google Cloud&rsquo;s infrastructure triggered a global outage that affected APIs, compute services, and downstream applications. The disruption spread quickly, and for many teams, the first signal that something was wrong came from their own users, not from Google&rsquo;s status page.<\/p><p class=\"wp-block-paragraph\">The root cause was a routine quota update. A configuration change deep in Google&rsquo;s systems cascaded across services, taking down workloads for organizations around the world.<\/p><p class=\"wp-block-paragraph\">The incident highlighted how dependent modern businesses are on cloud infrastructure they don&rsquo;t control and can&rsquo;t independently verify. When a provider&rsquo;s own reporting lags behind reality, customers are left guessing whether the problem is on their side or their provider&rsquo;s.<\/p><p class=\"wp-block-paragraph\">This post covers what happened during the outage, why status pages alone leave gaps in incident response, what real-time, independent visibility looks like in practice, and why it matters for every organization running critical services on shared infrastructure.<\/p><h2 id=\"h-what-happened\" class=\"wp-block-heading\">Qu'est-il arriv\u00e9 ?<\/h2><p class=\"wp-block-paragraph\">At <strong>1:49 PM ET on June 12<\/strong>, Google Cloud began experiencing a major service disruption. The cause: an automated quota update in Google&rsquo;s global API management system that triggered widespread 503 errors and external API request failures. What followed was a cascading breakdown, one that reached deep into the infrastructure powering core Google Cloud services and beyond.<\/p><p class=\"wp-block-paragraph\"><strong>Affected services included:<\/strong><\/p><ul class=\"wp-block-list\">\n<li>Google Cloud Console, App Engine, Cloud DNS, and Dataflow<\/li>\n\n\n\n<li>Identity and Access Management (IAM), Pub\/Sub, and Dialogflow<\/li>\n\n\n\n<li>Apigee API Management and other backend services<\/li>\n\n\n\n<li>30+ additional GCP products across the Americas, EMEA, APAC, and Africa<\/li>\n<\/ul><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1379\" height=\"788\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-24.png\" alt=\"\" class=\"wp-image-617217\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-24.png 1379w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-24-18x10.png 18w\" sizes=\"auto, (max-width: 1379px) 100vw, 1379px\"><\/figure><p class=\"wp-block-paragraph\">The outage reverberated outward, hitting major platforms like Discord, Spotify, Snapchat, Twitch, and Cloudflare, all of which depend on GCP under the hood.<\/p><p class=\"wp-block-paragraph\">Recovery began within hours for most regions, but in us-central1, where a quota policy database was overwhelmed, the impact lingered well into the afternoon.<\/p><h2 id=\"h-how-was-it-detected\" class=\"wp-block-heading\">How was it detected?<\/h2><p class=\"wp-block-paragraph\">Within a minute, <a href=\"https:\/\/www.logicmonitor.com\/fr\/logicmonitor-catchpoint\">Point de rattrapage<\/a>, a LogicMonitor company, began flagging anomalies via <a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-health\">Internet Sonar<\/a> for services such as Google Drive and App Engine at 1:50 PM ET.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"448\" height=\"725\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-25.png\" alt=\"\" class=\"wp-image-617218\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-25.png 448w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-25-7x12.png 7w\" sizes=\"auto, (max-width: 448px) 100vw, 448px\"><\/figure><p class=\"wp-block-paragraph\">Catchpoint Internet Sonar view<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1380\" height=\"403\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-27.png\" alt=\"\" class=\"wp-image-617220\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-27.png 1380w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-27-18x5.png 18w\" sizes=\"auto, (max-width: 1380px) 100vw, 1380px\"><\/figure><p class=\"wp-block-paragraph\">Apigee service disruptions detected across 109 cities worldwide<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1377\" height=\"431\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-29.png\" alt=\"\" class=\"wp-image-617222\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-29.png 1377w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-29-18x6.png 18w\" sizes=\"auto, (max-width: 1377px) 100vw, 1377px\"><\/figure><p class=\"wp-block-paragraph\">Google Cloud service degradation detected across 157 cities, with active incidents spanning North America, Latin America, Europe, and Asia-Pacific<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1376\" height=\"625\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-30.png\" alt=\"\" class=\"wp-image-617223\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-30.png 1376w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-30-18x8.png 18w\" sizes=\"auto, (max-width: 1376px) 100vw, 1376px\"><\/figure><p class=\"wp-block-paragraph\">This screenshot shows a spike in failed tests across multiple workflows. The failure pattern is sudden, sustained, and correlated across multiple test types, a classic signal of a widespread upstream infrastructure disruption.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1379\" height=\"683\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-31.png\" alt=\"\" class=\"wp-image-617224\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-31.png 1379w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-31-18x9.png 18w\" sizes=\"auto, (max-width: 1379px) 100vw, 1379px\"><\/figure><p class=\"wp-block-paragraph\">This chart from a Catchpoint user shows a sharp drop in availability and a spike in checkout failures across multiple countries, confirming global impact on user-facing transactions during the outage window.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1381\" height=\"687\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-28.png\" alt=\"\" class=\"wp-image-617221\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-28.png 1381w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-28-18x9.png 18w\" sizes=\"auto, (max-width: 1381px) 100vw, 1381px\"><\/figure><p class=\"wp-block-paragraph\">Carte de la pile Internet<\/p><p class=\"wp-block-paragraph\">This <a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-stack-map\">Carte de la pile Internet<\/a> shows a clear breakdown in service dependencies, with Google Cloud and Apigee at the center of the disruption.<\/p><p class=\"wp-block-paragraph\">You can see how multiple layers (including analytics, cloud logging, storage, and identity) all failed in tandem. These failures directly impacted third-party tools, CDNs, and SaaS integrations downstream.<\/p><p class=\"wp-block-paragraph\">The alert indicators show transaction failures and response errors cascading outward, affecting not just infrastructure, but also the digital experience of users relying on these tools in real time. Overall, the dependency map above captures what many teams experienced: when one layer goes, it doesn&rsquo;t go alone.<\/p><h2 id=\"h-no-official-word-yet\" class=\"wp-block-heading\">No official word, yet<\/h2><p class=\"wp-block-paragraph\">While synthetic tests and customer data clearly showed the disruption unfolding in real time, Google Cloud&rsquo;s first public acknowledgment didn&rsquo;t arrive until 2:46 PM ET, nearly an hour after anomalies first appeared and services began failing globally.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1114\" height=\"268\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-26.png\" alt=\"\" class=\"wp-image-617219\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-26.png 1114w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-26-18x4.png 18w\" sizes=\"auto, (max-width: 1114px) 100vw, 1114px\"><\/figure><p class=\"wp-block-paragraph\">Google Cloud status page<\/p><p class=\"wp-block-paragraph\">During that gap, the GCP <a href=\"https:\/\/status.cloud.google.com\/incidents\/ow5i3PPK96RduMcb1SsW\">status page remained green<\/a>.<\/p><p class=\"wp-block-paragraph\">For teams on the front lines (SREs, DevOps, or customer support) that matters. It creates doubt. Are we at fault? Is this a local issue? Can we act, or do we wait?<\/p><p class=\"wp-block-paragraph\">This is simply the reality of operating at scale. Status pages are often downstream from detection. They&rsquo;re built for caution, not speed. And by the time they update, most teams have lost the window for a proactive response.<\/p><h2 id=\"h-what-was-the-impact\" class=\"wp-block-heading\">What was the impact?<\/h2><p class=\"wp-block-paragraph\">The blast radius was wide and layered.<\/p><ul class=\"wp-block-list\">\n<li><strong>Direct GCP customers<\/strong> lost access to core infrastructure: management consoles, APIs, storage, and authentication services.<\/li>\n\n\n\n<li><strong>SaaS and enterprise platforms<\/strong> saw critical user workflows stall for over two hours, with transaction-level failures visible in real-time test data.<\/li>\n\n\n\n<li><strong>Consumer platforms<\/strong> including Discord, Snapchat, Twitch, and Spotify suffered cascading slowdowns due to their dependencies on affected Google services.<\/li>\n\n\n\n<li><strong>Geographic scope<\/strong>: Failures were observed across North America, EMEA, APAC, and Latin America.<\/li>\n<\/ul><p class=\"wp-block-paragraph\">What began as a quiet configuration change rippled outward, breaking not just cloud services, but the trust and functionality layered on top of them.<\/p><h2 id=\"h-key-lessons\" class=\"wp-block-heading\">Key lessons<\/h2><p class=\"wp-block-paragraph\">Outages like this break systems and expose assumptions about how we monitor, communicate, and respond. Here&rsquo;s what the June 12 Google Cloud incident reinforced.<\/p><h2 id=\"h-1-no-one-is-too-big-to-go-down\" class=\"wp-block-heading\">#1 No one is too big to go down<\/h2><p class=\"wp-block-paragraph\">No provider, not even Google, is immune to large-scale outages. The events of June 12 made that clear. A routine quota update cascaded into global downtime, reminding every digital business just how quickly dependencies can unravel.<\/p><p class=\"wp-block-paragraph\"><em>&ldquo;This is a timely wakeup call: even hyperscalers like Google aren&rsquo;t immune to largescale outages. In today&rsquo;s interconnected digital landscape, external observability via tools like Catchpoint isn&rsquo;t optional, it&rsquo;s essential.&rdquo;<\/em><em><br><\/em><strong>Mehdi Daoudi, CEO &amp; Co-founder, Catchpoint<\/strong><\/p><h2 id=\"h-2-the-domino-effect-is-real\" class=\"wp-block-heading\">#2 The domino effect is real<\/h2><p class=\"wp-block-paragraph\">When a hyperscaler like Google stumbles, the impact extends far beyond their own systems. SaaS platforms, third-party APIs, and the end-user experiences they power all feel the effects.<\/p><p class=\"wp-block-paragraph\">This incident showed just how fast a single point of failure can ripple outward, breaking things that appear unrelated at first glance.<\/p><p class=\"wp-block-paragraph\"><em>&ldquo;Your system is as resilient as the weakest of its components. Which means it only takes one dependency to bring down an entire system. If the authentication service used by a critical API is down, your system is down, even if everything else is working.&rdquo;<\/em><em><br><\/em><strong>Gerardo Dada, Field CTO, Catchpoint<\/strong><\/p><h2 id=\"h-3-status-pages-arent-enough\" class=\"wp-block-heading\">#3 Status pages aren&rsquo;t enough<\/h2><p class=\"wp-block-paragraph\">Provider dashboards serve a purpose, but they aren&rsquo;t built for real-time incident response. They&rsquo;re designed to be cautious, accurate, and measured, which often means they lag behind the actual impact felt by users and customers.<\/p><p class=\"wp-block-paragraph\">Provider status pages reflect operational reality at scale. The real lesson is to expect more from your own visibility.<\/p><h2 id=\"h-4-design-for-resilience\" class=\"wp-block-heading\">#4 Design for resilience<\/h2><p class=\"wp-block-paragraph\">Outages happen, even to the best-engineered platforms on the planet. What matters isn&rsquo;t avoiding every failure, but mitigating the blast radius when one occurs.<\/p><p class=\"wp-block-paragraph\">That means building systems that assume things will break, architecting across regions, diversifying providers, and creating failovers that actually fail over.<\/p><p class=\"wp-block-paragraph\"><em>&ldquo;One thing we see with Internet Sonar is even the greatest companies with the most advanced tech can suffer outages. It happens to the best. All the more reason for a multi-multi architecture.&rdquo;<\/em><em><br><\/em><strong>Matt Izzo, VP Product, Catchpoint<\/strong><\/p><h2 id=\"h-5-your-monitoring-cant-live-in-the-same-cloud-youre-trying-to-monitor\" class=\"wp-block-heading\">#5 Your monitoring can&rsquo;t live in the same cloud you&rsquo;re trying to monitor<\/h2><p class=\"wp-block-paragraph\">Outages like this raise an uncomfortable but important question: Can your monitoring still see what&rsquo;s happening when your cloud provider goes dark?<\/p><p class=\"wp-block-paragraph\">Many monitoring tools rely on cloud-hosted vantage points, often within the very infrastructure they&rsquo;re meant to observe. When that cloud provider has an outage, your diagnostics might vanish along with it. Synthetic tests hosted in hyperscalers rarely reflect real user environments, and they mask failures within the provider itself.<\/p><ul class=\"wp-block-list\">\n<li><strong>Synthetic tests inside the cloud<\/strong> often miss real-world issues like DNS errors, CDN disruptions, or ISP-level failures.<\/li>\n\n\n\n<li><strong>Cloud-only testing<\/strong> creates a false sense of security. You&rsquo;re essentially monitoring yourself, from yourself.<\/li>\n<\/ul><p class=\"wp-block-paragraph\">True visibility comes from <strong>outside the cloud<\/strong>, from the edge of the Internet where real users live. Monitoring should never go down when you need it most.<\/p><h2 id=\"h-staying-resilient-when-the-internet-isnt\" class=\"wp-block-heading\">Staying resilient when the Internet isn&rsquo;t<\/h2><p class=\"wp-block-paragraph\">The June 12 outage disrupted far more than Google Cloud, creating cascading effects across Cloudflare, CDNs, productivity platforms, and AI tools. It&rsquo;s a vivid reminder of how deeply interconnected and interdependent digital systems have become.<\/p><p class=\"wp-block-paragraph\">These failures had real consequences. Picture a hospital unable to access patient records or drug databases due to a cloud outage. This is about critical services failing at the worst possible moment.<\/p><p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\">LM Internet Performance Monitoring<\/a>, powered by Catchpoint, is built for exactly this kind of scenario. During the incident:<\/p><ul class=\"wp-block-list\">\n<li>Catchpoint remained fully operational.<\/li>\n\n\n\n<li>Monitoring continued from outside the public cloud.<\/li>\n\n\n\n<li>While some customers faced issues reaching third-party services, Catchpoint itself remained visible and stable throughout.<\/li>\n<\/ul><p class=\"wp-block-paragraph\">That kind of independence matters, and it&rsquo;s a core part of why LogicMonitor brought Catchpoint into its platform. By unifying <a href=\"https:\/\/www.logicmonitor.com\/fr\/infrastructure-monitoring\">LM Envision<\/a>, <a href=\"https:\/\/www.logicmonitor.com\/blog\/edwin-ai-catchpoint-internet-visibility-autonomous-it\">Internet Performance Monitoring, and Edwin AI<\/a>, LogicMonitor gives teams a single system that spans infrastructure, Internet dependencies, and digital experience, so blind spots like these become visible before they cascade.<\/p><p class=\"wp-block-paragraph\"><strong>Tools that made a difference<\/strong><\/p><p class=\"wp-block-paragraph\">Catchpoint users navigating the Google Cloud outage had two key advantages on their side:<\/p><ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-health\"><strong>Internet Sonar<\/strong><\/a> offers real-time, independent monitoring of the Internet&rsquo;s core services, helping you detect third-party issues early, understand their scope, and act decisively.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-stack-map\"><strong>Carte de la pile Internet<\/strong><\/a> provides a live view of your service&rsquo;s dependencies, making it easy to trace cascading failures and pinpoint root causes fast.<\/li>\n<\/ul><h2 id=\"h-from-detection-to-action\" class=\"wp-block-heading\">From detection to action<\/h2><p class=\"wp-block-paragraph\">Detecting the June 12 outage was the first step. But for most teams, detection only opens the door to a longer, harder question: where exactly is the problem, and what should we do about it? When the issue sits outside your infrastructure, in a cloud provider&rsquo;s network or a third-party dependency, manual triage can stretch from minutes to hours.<\/p><p class=\"wp-block-paragraph\">This is where Internet Performance Monitoring and<a href=\"https:\/\/www.logicmonitor.com\/fr\/edwin-ai\"> Edwin AI<\/a> work together. Catchpoint&rsquo;s observability network (3,100+ intelligent collectors across cloud, backbone, last-mile, wireless, BGP peers, and enterprise environments) feeds Internet-layer telemetry directly into LogicMonitor&rsquo;s intelligence layer. Edwin AI analyzes that telemetry alongside infrastructure and application data, understands service relationships through a shared context graph, and prioritizes issues by business impact. Teams can answer &ldquo;is it us or the Internet?&rdquo; in seconds, with contextual correlation replacing manual war-room triage.<\/p><p class=\"wp-block-paragraph\">That&rsquo;s the practical foundation of<a href=\"https:\/\/www.logicmonitor.com\/blog\/autonomous-operations-without-blind-spots\"> IT autonome<\/a>: full-path visibility from user to code, connected to AI that can reason across every layer and act on what it finds. When observability, intelligence, and action run through<a href=\"https:\/\/www.logicmonitor.com\/blog\/edwin-ai-catchpoint-internet-visibility-autonomous-it\"> one telemetry pipeline and one context graph<\/a>, operations teams move from reactive firefighting to early warnings, faster root cause, and governed response, before degradation reaches revenue.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-calendar-check\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xxs fs-md-text-display-xs fs-lg-text-display-sm font-medium text-core-blue-900\">\n        D\u00e9couvrez comment la surveillance Internet ind\u00e9pendante comble le manque de visibilit\u00e9 avant votre prochaine panne.      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900\">\n        <p>La surveillance des performances Internet LM, propuls\u00e9e par Catchpoint, offre une visibilit\u00e9 en temps r\u00e9el et ind\u00e9pendante du cloud \u00e0 chaque niveau de votre pile num\u00e9rique, vous permettant ainsi de d\u00e9tecter les pannes avant m\u00eame que la page de statut de votre fournisseur ne le fasse.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/catchpoint-demo\" class=\"btn btn-link\" target=\"_self\">\n         Demander une d\u00e9monstration          <span class=\"icon-end\"><svg class=\"\" width=\"20px\" height=\"20px\" style=\"fill: #060F4B\">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-arrow-right\"><\/use>\n    <\/svg><\/span>\n      <\/a>\n        <\/div>\n            <\/div>\n<\/div><h4 id=\"h-faqs\" class=\"wp-block-heading\">FAQ<\/h4><div class=\"accordion-block accordion-block--light\">\n      <div class=\"accordion-block__items\">\n              <div class=\"accordion-block__item active\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-what-caused-the-june-12-2025-google-cloud-outage\">\n            What caused the June 12, 2025, Google Cloud outage?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer active\">\n            <p>An automated quota update in Google&rsquo;s global API management system triggered widespread 503 errors and external API request failures. The configuration change cascaded across 30+ GCP services, affecting customers and downstream platforms across the Americas, EMEA, APAC, and Africa.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-why-did-googles-status-page-take-so-long-to-reflect-the-outage\">\n            Why did Google's status page take so long to reflect the outage?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>Provider status pages are designed for caution and accuracy, which often means they lag behind real-time impact. During this incident, Google&rsquo;s first public acknowledgment arrived at 2:46 PM ET, nearly an hour after independent monitoring tools detected anomalies at 1:50 PM ET.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-can-organizations-detect-cloud-outages-faster-than-the-providers-own-status-page\">\n            How can organizations detect cloud outages faster than the provider's own status page?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>By using independent, cloud-external monitoring tools such as Catchpoint&rsquo;s Internet Sonar, which operates outside public cloud infrastructure. These tools detect anomalies from the edge of the Internet where real users connect, providing visibility even when the cloud provider&rsquo;s own systems are compromised.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div>","protected":false},"excerpt":{"rendered":"<p>La panne de Google Cloud a provoqu\u00e9 des perturbations mondiales. Voici comment la surveillance ind\u00e9pendante l'a d\u00e9tect\u00e9e en premier et ce que cela signifie pour la r\u00e9silience num\u00e9rique.<\/p>","protected":false},"author":16,"featured_media":621520,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[5035],"tags":[7850,7852,7885,7851,5985,7760,7864,7906,7854,6677],"industry":[7523],"role":[6786],"lm_strategic_tags":[],"topic":[7842],"class_list":["post-617214","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-technology","role-itops","topic-internet-performance-monitoring"],"acf":{"page_language":"english","translated_pages":"","updated_date":null,"author_section_checkbox":true,"author_image":617027,"author_linkedin":"https:\/\/www.linkedin.com\/in\/denton-chikura-422186201\/","author_name":"Denton Chikura","author_job_title":"Technical Writer","author_dept":"","author_bio":"Denton Chikura is a technical writer and longtime observability advocate focused on helping site reliability engineers and engineering teams discover the tools and capabilities that strengthen internet resilience. He works at the intersection of monitoring, performance, and infrastructure to make complex systems more understandable and usable, bridging the gap between deep technical detail and real\u2011world operations. His goal is to help teams build faster, detect issues earlier, and recover smarter, ultimately making the internet a better, more reliable place for everyone.","reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.2 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Google Cloud Outage and Hidden Dependencies | LogicMonitor<\/title>\n<meta name=\"description\" content=\"A major Google Cloud outage on June 12, 2025, caused global disruption. 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r\u00e9f\u00e9rencement naturel (SEO) \u00e0 l'optimisation pour les moteurs de r\u00e9ponse (AEO) : pourquoi la performance web est la cl\u00e9 du succ\u00e8s dans la recherche par IA"},"content":{"rendered":"<?xml encoding=\"UTF-8\"><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50 rtc-text-content--no-top-pad\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-book-open\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xs fs-md-text-display-sm fs-lg-text-display-md font-medium text-core-blue-900\">\n        Le t\u00e9l\u00e9chargement rapide :      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900 headline-is-quote\">\n        <p>AI search engines favor fast, stable websites, making web performance the foundation of both SEO and AEO success.<\/p>\n      <\/div>\n    \n                  <ul class=\"rtc-text-content__bullet-list\">\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>AI answer engines cite fewer sources than traditional search, so only high-performing pages make the cut.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Slow load times, unstable rendering, and poor global coverage directly reduce your chances of being cited by AI systems like ChatGPT, Perplexity, and Google AI Overviews.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Core Web Vitals, server response times, and Internet backbone health all influence whether your content reaches AI crawlers.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Start monitoring your site&rsquo;s performance continuously with synthetic and real-user data to protect your visibility in AI-driven search.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p class=\"wp-block-paragraph\"><br>Search isn&rsquo;t what it used to be. The way people discover information online is shifting. Instead of clicking through search results, many now ask AI answer engines like ChatGPT and Perplexity to do the research for them.<\/p><p class=\"wp-block-paragraph\">In March 2025, 13.1% of Google desktop searches featured AI Overviews, doubling from over 6% in January, according to <a href=\"https:\/\/www.semrush.com\/blog\/semrush-ai-overviews-study\/\">Semrush analysis<\/a> of 10+ million queries. <a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2024-02-19-gartner-predicts-search-engine-volume-will-drop-25-percent-by-2026-due-to-ai-chatbots-and-other-virtual-agents\">Gartner predicts<\/a> that by 2026, a quarter of all search traffic will shift to AI assistants, with ChatGPT alone serving 400+ million users each week.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"796\" height=\"582\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-22.png\" alt=\"\" class=\"wp-image-617210\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-22.png 796w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-22-16x12.png 16w\" sizes=\"auto, (max-width: 796px) 100vw, 796px\"><\/figure><p class=\"wp-block-paragraph\"><em>Share of queries triggering AI overviews Jan-Mar 2025<\/em><\/p><p class=\"wp-block-paragraph\">This means getting your content recommended by these AIs (a practice called Answer Engine Optimization, or AEO, also known as Generative Engine Optimization) has quickly become a priority for brands that want to stay visible. You need to be the go-to answer when your audience turns to AI for help.<\/p><p class=\"wp-block-paragraph\">But a <a href=\"https:\/\/searchengineland.com\/how-to-get-cited-by-ai-seo-insights-from-8000-ai-citations-455284\">Search Engine Land study<\/a> of nearly 8,000 AI citations shows just how fragmented the ecosystem is:<\/p><ul class=\"wp-block-list\">\n<li>ChatGPT leans heavily on sites like Wikipedia and Reddit<\/li>\n\n\n\n<li>Perplexity diversifies across news publishers and niche blogs<\/li>\n\n\n\n<li>Google&rsquo;s AI Overviews mix in Reddit, Quora, and authoritative domains<\/li>\n<\/ul><p class=\"wp-block-paragraph\">AI answer engines are opaque systems that change often, and it&rsquo;s hard to keep up with where and how you&rsquo;ll get cited. But one thing remains unchanged: web performance still matters.<\/p><p class=\"wp-block-paragraph\">If your website isn&rsquo;t fast, stable, and reliable, you reduce your chances of being cited. AI systems pull from multiple sources, and performance is one factor that can determine whether your page is included in those answers.<\/p><h2 id=\"h-seo-vs-aeo-shared-foundations-new-challenges\" class=\"wp-block-heading\">SEO vs AEO: Shared Foundations, New Challenges<\/h2><p class=\"wp-block-paragraph\">SEO isn&rsquo;t going away. The fundamentals (quality content, smart keyword use, structured data, and Core Web Vitals) remain essential.<\/p><p class=\"wp-block-paragraph\">AEO adds new demands that go beyond traditional SEO:<\/p><ul class=\"wp-block-list\">\n<li><strong>AI assistants give fewer answers.<\/strong> Instead of ten links, users may see one or two citations. You want to be one of them.<\/li>\n\n\n\n<li><strong>AI crawlers are selective.<\/strong> Many use lightweight crawling. They don&rsquo;t reliably execute heavy JavaScript and won&rsquo;t wait long for slow-loading content.<\/li>\n\n\n\n<li><strong>Zero-click search is real.<\/strong> In SEO, clicks to your site are the primary measure of success. But with AEO, zero-click answers are common. AI engines might give the user what they need right inside the interface, without anyone visiting your page. That means your brand&rsquo;s visibility depends on being cited, not just ranked.<\/li>\n<\/ul><h2 id=\"h-why-performance-still-matters-in-ai-search\" class=\"wp-block-heading\">Why Performance Still Matters in AI Search<\/h2><p class=\"wp-block-paragraph\">When it comes to being seen by AI, performance is a baseline. It affects AI search visibility in three concrete ways:<\/p><ul class=\"wp-block-list\">\n<li><strong>Page speed affects crawl priority.<\/strong> Google factors speed into SEO rankings. AI answer engines need speed even more to generate responses in real time. A slow site can lose its chance at being considered.<\/li>\n\n\n\n<li><strong>Stable rendering signals content quality.<\/strong> Sites that render smoothly and reliably keep users engaged and signal quality to AI systems.<\/li>\n\n\n\n<li><strong>Geographic performance coverage determines global inclusion.<\/strong> AI searches come from everywhere. If your site only performs well locally, you risk being excluded from global answers.<\/li>\n<\/ul><h2 id=\"h-how-to-optimize-your-website-performance-for-seo-and-aeo\" class=\"wp-block-heading\">How to Optimize Your Website Performance for SEO and AEO<\/h2><p class=\"wp-block-paragraph\">The following steps address the most common performance gaps that affect both SEO and AEO.<\/p><h3 id=\"h-1-measure-and-monitor-your-performance-continuously\" class=\"wp-block-heading\">1. Measure and Monitor Your Performance Continuously<\/h3><p class=\"wp-block-paragraph\">Begin by benchmarking your site&rsquo;s speed and responsiveness across geographies, devices, and networks using WebPageTest. Run tests to track your performance metrics and test your critical user journeys to identify potential issues.<\/p><p class=\"wp-block-paragraph\">Combine real-user monitoring data with synthetic tests to get a full picture of your site&rsquo;s health. This approach lets you see how real visitors experience your pages and also catch issues proactively in a controlled environment. The goal is to have eyes on your website&rsquo;s performance around the clock, so you can spot and fix small slowdowns before they snowball.<\/p><p class=\"wp-block-paragraph\">For teams juggling both proactive testing and real-world data, Catchpoint IPM, part of the LogicMonitor platform, offers a unified way to combine synthetics with real user monitoring (RUM) for full visibility, giving you both lab-grade diagnostics and production-level insight in one place.<\/p><h3 id=\"h-2-tackle-the-usual-suspects\" class=\"wp-block-heading\">2. Tackle the Usual Suspects<\/h3><ul class=\"wp-block-list\">\n<li><strong>Server response (TTFB):<\/strong> Time to First Byte (TTFB) is how long it takes your server to respond after a request is made. If this is slow, everything else will be too. Speed up backend processes, cache aggressively, and use a CDN to reduce latency.<\/li>\n\n\n\n<li><strong>Heavy assets:<\/strong> Compress images, switch to modern formats (WebP\/AVIF), and lazy-load below-the-fold content.<\/li>\n\n\n\n<li><strong>Render-blocking resources:<\/strong> A quick look at the WebPageTest waterfall chart can reveal exactly which CSS or JavaScript files are slowing down the first paint. The chart shows the loading order of every resource, making it straightforward to identify what&rsquo;s blocking rendering. Once identified, defer or async non-critical scripts, and inline critical CSS to help content appear faster.<\/li>\n<\/ul><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"868\" height=\"936\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-23.png\" alt=\"\" class=\"wp-image-617211\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-23.png 868w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-23-11x12.png 11w\" sizes=\"auto, (max-width: 868px) 100vw, 868px\"><\/figure><p class=\"wp-block-paragraph\"><em>WebPageTest waterfall chart for a leading streaming platform, tested from Amsterdam on August 7, 2025, using Chrome<\/em><\/p><ul class=\"wp-block-list\">\n<li><strong>Third-party scripts:<\/strong> Audit frequently. Ads, analytics, and widgets can slow you down.<\/li>\n\n\n\n<li><strong>Core Web Vitals:<\/strong> Focus on Largest Contentful Paint (LCP), Cumulative Layout Shift (CLS), and responsiveness (INP). These metrics aren&rsquo;t just SEO signals. They also make your site more AI-friendly.<\/li>\n<\/ul><h3 id=\"h-3-dont-forget-the-backbone\" class=\"wp-block-heading\">3. Don&rsquo;t Forget the Backbone<\/h3><p class=\"wp-block-paragraph\">DNS lookups, CDN routing, and TLS handshake times all impact how quickly your site loads. A sluggish DNS could mean you&rsquo;re left out of the answer entirely. DNS plays a bigger role than most people realize.<\/p><p class=\"wp-block-paragraph\">With Catchpoint IPM&rsquo;s Internet-layer monitoring (including Internet Sonar and BGP Monitoring), teams can track DNS performance, routing changes, and third-party dependencies that sit outside traditional application monitoring. These blind spots in the Internet backbone are often the difference between a page that loads in one second and one that times out.<\/p><h3 id=\"h-4-keep-monitoring-and-improving\" class=\"wp-block-heading\">4. Keep Monitoring and Improving<\/h3><p class=\"wp-block-paragraph\">Web performance isn&rsquo;t a one-and-done project. Every new script, image, or design tweak can tip the scales. Continuous monitoring with synthetic + RUM, combined with smart alerting, ensures you catch regressions and fix issues before they affect experience or search ranking.<\/p><p class=\"wp-block-paragraph\">Because <a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\">LM Internet Performance Monitoring<\/a> feeds into the broader LogicMonitor platform, teams can correlate web performance data with infrastructure and application telemetry in one place, making it easier to pinpoint root causes and prioritize by business impact.<\/p><h2 id=\"h-what-this-means-for-your-search-visibility\" class=\"wp-block-heading\">What This Means for Your Search Visibility<\/h2><p class=\"wp-block-paragraph\">SEO continues to evolve. AEO means your site must be discoverable <em>et<\/em> deliver a great experience instantly. High-quality, authoritative content paired with fast, stable, and trustworthy pages gets prioritized by answer engines.<\/p><p class=\"wp-block-paragraph\">AI search algorithms have changed frequently since these systems launched, and that pattern is likely to continue. Maintaining fast, stable, globally consistent performance gives your content a durable baseline that helps regardless of how crawlers evolve. By measuring performance from all angles, fixing bottlenecks, and monitoring continuously, you protect both your rankings and your brand&rsquo;s visibility in AI-driven search.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-calendar-check\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xxs fs-md-text-display-xs fs-lg-text-display-sm font-medium text-core-blue-900\">\n        Monitor your web performance across every layer to stay visible in AI search.      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900\">\n        <p>AI crawlers reward speed, stability, and global consistency. LogicMonitor with Catchpoint IPM gives you full-stack visibility, from infrastructure to Internet backbone, so your content stays citation-ready.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/catchpoint-demo\" class=\"btn btn-link\" target=\"_self\">\n         Demander une d\u00e9monstration          <span class=\"icon-end\"><svg class=\"\" width=\"20px\" height=\"20px\" style=\"fill: #060F4B\">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-arrow-right\"><\/use>\n    <\/svg><\/span>\n      <\/a>\n        <\/div>\n            <\/div>\n<\/div><h4 id=\"h-faqs\" class=\"wp-block-heading\">FAQ<\/h4><div class=\"accordion-block accordion-block--light\">\n      <div class=\"accordion-block__items\">\n              <div class=\"accordion-block__item active\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-what-is-aeo-and-how-does-it-differ-from-seo\">\n            What is AEO and how does it differ from SEO?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer active\">\n            <p>AEO (Answer Engine Optimization) focuses on getting your content cited by AI answer engines like ChatGPT, Perplexity, and Google AI Overviews. While SEO drives clicks from search result pages, AEO aims to make your site a trusted source that AI systems reference when generating answers. Both share foundational requirements like quality content and fast performance.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-does-web-performance-affect-ai-search-citations\">\n            How does web performance affect AI search citations?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>AI crawlers use lightweight processes that skip slow-loading or unstable pages. Fast server response times, stable rendering, and global CDN coverage increase the likelihood that your content is crawled and cited. Poor performance can exclude your pages from AI-generated answers entirely.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-what-tools-help-monitor-performance-for-both-seo-and-aeo\">\n            What tools help monitor performance for both SEO and AEO?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>Combining synthetic monitoring with real user monitoring (RUM) provides the most complete view. Catchpoint IPM, part of the LogicMonitor platform, unifies both approaches and adds Internet-layer monitoring for DNS, BGP, and CDN performance, covering blind spots that traditional application monitoring misses.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div><p class=\"wp-block-paragraph\"><\/p>","protected":false},"excerpt":{"rendered":"<p>Les moteurs de recherche aliment\u00e9s par l'IA accordent la priorit\u00e9 aux sites Web rapides et stables. Apprenez comment la performance web fait le lien entre le SEO et l'AEO pour maintenir la visibilit\u00e9 de votre contenu \u00e0 l'heure o\u00f9 la recherche \u00e9volue vers les r\u00e9ponses g\u00e9n\u00e9r\u00e9es par l'IA.<\/p>","protected":false},"author":16,"featured_media":621304,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[5035],"tags":[7850,7867,7882,7851,6677,7808,7866,7860,7883,7912],"industry":[6790,7523],"role":[6786],"lm_strategic_tags":[],"topic":[7842],"class_list":["post-617061","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-all","industry-technology","role-itops","topic-internet-performance-monitoring"],"acf":{"page_language":"english","translated_pages":"","updated_date":null,"author_section_checkbox":true,"author_image":617027,"author_linkedin":"https:\/\/www.linkedin.com\/in\/denton-chikura-422186201\/","author_name":"Denton Chikura","author_job_title":"Technical Writer","author_dept":"","author_bio":"Denton Chikura is a technical writer and longtime observability advocate focused on helping site reliability engineers and engineering teams discover the tools and capabilities that strengthen internet resilience. He works at the intersection of monitoring, performance, and infrastructure to make complex systems more understandable and usable, bridging the gap between deep technical detail and real\u2011world operations. His goal is to help teams build faster, detect issues earlier, and recover smarter, ultimately making the internet a better, more reliable place for everyone.","reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.2 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Web Performance: The Missing Link Between SEO and AEO | LogicMonitor<\/title>\n<meta name=\"description\" content=\"Fast, stable websites win in AI search. 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LLM n'ont pas vocation \u00e0 stagner : comment surveiller et faire confiance aux mod\u00e8les qui alimentent votre IA"},"content":{"rendered":"<?xml encoding=\"UTF-8\"><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50 rtc-text-content--no-top-pad\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-book-open\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xs fs-md-text-display-sm fs-lg-text-display-md font-medium text-core-blue-900\">\n        The quick download:      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900 headline-is-quote\">\n        <p>Every LLM you depend on is changing, and without continuous monitoring, you won&rsquo;t know until your users do.<\/p>\n      <\/div>\n    \n                  <ul class=\"rtc-text-content__bullet-list\">\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>LLMs update silently, drift in tone and accuracy, and perform inconsistently across regions and providers.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Side-by-side benchmarking of GPT, Claude, and Gemini reveals measurable differences in latency, cost, and output quality.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>LM Internet Performance Monitoring, powered by Catchpoint, enables repeatable LLM testing from 3,100+ global collectors.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Start monitoring your LLMs today to detect drift, validate fallback logic, and maintain trust in production AI.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\" id=\"h-one-large-language-model-llm-nails-your-brand-s-tone-but-drifts-after-a-model-update-another-is-lightning-fast-until-it-spikes-in-latency-during-peak-hours-a-third-delivers-brilliant-answers-except-in-specific-regions-where-it-falters\">One Large Language Model (LLM) nails your brand&rsquo;s tone but drifts after a model update. Another is lightning fast until it spikes in latency during peak hours. A third delivers brilliant answers except in specific regions where it falters.<\/p><h2 id=\"h-why-choosing-and-keeping-the-right-llm-is-so-hard\" class=\"wp-block-heading\">Why Choosing (and Keeping) the Right LLM Is So Hard<\/h2><p class=\"wp-block-paragraph\">Across open-source and proprietary options, LLMs are inherently dynamic. They update silently, hallucinate unexpectedly, and their costs shift with usage and configuration. Performance also varies by geography, task, and input.<\/p><p class=\"wp-block-paragraph\">That makes it hard to trust that the model you chose yesterday is still the best option today.<\/p><p class=\"wp-block-paragraph\">What teams need is a way to continuously evaluate the LLMs they rely on, to compare, validate, monitor drift, and surface anomalies before users do. Not just once during procurement, but every day in production.<\/p><h2 id=\"h-types-of-llms-and-what-they-mean-for-monitoring\" class=\"wp-block-heading\">Types of LLMs and What They Mean for Monitoring<\/h2><p class=\"wp-block-paragraph\">LLMs come in various forms: fully open-source, closed-source APIs, and hybrid models.<\/p><p class=\"wp-block-paragraph\"><strong>Open-source LLMs<\/strong> allow you to access, modify, and self-host the model weights and sometimes training data or code.<br><strong>Closed-source models<\/strong> (e.g., GPT-4, Claude) are proprietary and accessed via API.<br><strong>Hybrid models<\/strong> may be hosted by providers but expose some architecture or tuning capabilities.<\/p><p class=\"wp-block-paragraph\"><strong>Open-source advantages:<\/strong><\/p><ul class=\"wp-block-list\">\n<li>No licensing costs<\/li>\n\n\n\n<li>Greater flexibility (especially on-premise use)<\/li>\n\n\n\n<li>More transparency (to varying degrees)<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">Open-source LLMs offer flexibility and transparency, but the real challenge, open or closed, is monitoring and maintaining model trust over time.<\/p><h2 id=\"h-how-do-ai-agents-choose-the-right-llm\" class=\"wp-block-heading\">How Do AI Agents Choose the Right LLM?<\/h2><p class=\"wp-block-paragraph\">Modern AI agents often route tasks to different models depending on the need. Their choice depends on:<\/p><ul class=\"wp-block-list\">\n<li><strong>Task type<\/strong> &ndash; reasoning, creativity, retrieval, real-time queries<\/li>\n\n\n\n<li><strong>Performance goals<\/strong> &ndash; speed, cost, consistency<\/li>\n\n\n\n<li><strong>Security needs<\/strong> &ndash; private infrastructure vs. cloud<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">Before routing, an AI agent typically receives user input, anything from a question to a task request, via a front-end interface like a chatbot or form.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1080\" height=\"607\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-16.png\" alt=\"\" class=\"wp-image-617052\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-16.png 1080w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-16-18x10.png 18w\" sizes=\"auto, (max-width: 1080px) 100vw, 1080px\"><\/figure><p class=\"wp-block-paragraph\"><em>How prompts flow through a multi-LLM system<\/em><\/p><p class=\"wp-block-paragraph\">AI agents act like routers, matching each prompt to the best-fit model using business logic.<\/p><p class=\"wp-block-paragraph\"><strong>Common LLM routing scenarios:<\/strong><\/p><ul class=\"wp-block-list\">\n<li><strong>GPT (OpenAI):<\/strong> Ideal for research-heavy, general-purpose text generation.<\/li>\n\n\n\n<li><strong>LLaMA:<\/strong> Lightweight, open-source alternative for on-premise or private setups.<\/li>\n\n\n\n<li><strong>Gemini:<\/strong> Good for reasoning and integrating with the Google ecosystem.<\/li>\n\n\n\n<li><strong>Grok:<\/strong> Chosen for video generation or multimedia-related queries.<\/li>\n\n\n\n<li><strong>Claude (Anthropic):<\/strong> Safer alignment in regulated domains.<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">A condition-based logic is used: e.g., &ldquo;If input involves video processing, use Grok.&rdquo;<\/p><p class=\"wp-block-paragraph\">Once an LLM is chosen, the real challenge is ensuring it continues to perform. This is where Catchpoint IPM, part of the LogicMonitor platform, provides continuous LLM monitoring and validation.<\/p><h2 id=\"h-logicmonitors-approach-to-testing-and-monitoring-llms\" class=\"wp-block-heading\">LogicMonitor&rsquo;s Approach to Testing and Monitoring LLMs<\/h2><p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.logicmonitor.com\/internet-performance-monitoring\">LM Internet Performance Monitoring<\/a>, powered by <a href=\"https:\/\/www.logicmonitor.com\/blog\/edwin-ai-catchpoint-internet-visibility-autonomous-it\">Catchpoint<\/a>, enables teams to evaluate how models perform across a wide range of tasks, from summarization to code generation, and measures how reliably they respond to real-world use cases. With 3,100+ intelligent collectors across 6 continents, teams can rigorously monitor the health, quality, and latency of LLM responses, whether from GPT, Claude, Gemini, or another platform.<\/p><p class=\"wp-block-paragraph\">In practical terms, that means:<\/p><ul class=\"wp-block-list\">\n<li>Sending live prompts to multiple LLMs across geographies<\/li>\n\n\n\n<li>Capturing how each responds (tone, coherence, freshness)<\/li>\n\n\n\n<li>Identifying issues like drift, hallucination, or performance degradation<\/li>\n<\/ul><p class=\"wp-block-paragraph\">This is a repeatable testing framework for teams evaluating generative AI in their workflows. It helps de-risk LLM adoption by offering visibility, choice, and control, core principles that extend LogicMonitor&rsquo;s user-to-code visibility to AI model dependencies.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1074\" height=\"382\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-19.png\" alt=\"\" class=\"wp-image-617055\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-19.png 1074w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-19-18x6.png 18w\" sizes=\"auto, (max-width: 1074px) 100vw, 1074px\"><\/figure><p class=\"wp-block-paragraph\"><em>A summary of the use cases and KPIs LogicMonitor tracks across LLMs<\/em><\/p><p class=\"wp-block-paragraph\"><strong>Some core capabilities tested include:<\/strong><\/p><ul class=\"wp-block-list\">\n<li>Interpret prompts and generate natural language responses.<\/li>\n\n\n\n<li>Provide multiple perspectives on the same input.<\/li>\n\n\n\n<li>Demonstrate behavior under various hyperparameters.<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><strong>Key API Parameters That Shape LLM Behavior<\/strong><\/p><p class=\"wp-block-paragraph\">A model&rsquo;s response style depends not just on its architecture, but on how it&rsquo;s configured via prompt parameters. These control randomness, verbosity, and tone, and small tweaks can produce drastically different results.<\/p><p class=\"wp-block-paragraph\">Below: A sample request sent to an LLM API, showing how:<\/p><ul class=\"wp-block-list\">\n<li>Key parameters help structure the response<\/li>\n\n\n\n<li>Key metrics should be tracked to make sure quality of response and performance are metered equally<\/li>\n<\/ul><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1143\" height=\"393\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-15.png\" alt=\"\" class=\"wp-image-617051\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-15.png 1143w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-15-18x6.png 18w\" sizes=\"auto, (max-width: 1143px) 100vw, 1143px\"><\/figure><p class=\"wp-block-paragraph\">LogicMonitor also uses scripts like the one below to send prompts to multiple models and compare outcomes.<\/p><p class=\"wp-block-paragraph\"><strong>LogicMonitor Script Sample<\/strong><\/p><p class=\"wp-block-paragraph\">var apiURL = &ldquo;https:\/\/abc.com\/models\/openai | anthropic | google&rdquo;; var apiData = { &ldquo;messages&rdquo;: [ { &ldquo;role&rdquo;: &ldquo;user&rdquo;, &ldquo;content&rdquo;: &ldquo;What does Catchpoint do?&rdquo; } ], &ldquo;temperature&rdquo;: 0.7, &ldquo;top_p&rdquo;: 0.9, &ldquo;frequency_penalty&rdquo;: 0.3, &ldquo;presence_penalty&rdquo;: 0.1, &ldquo;max_tokens&rdquo;: 500 };<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1059\" height=\"295\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-21.png\" alt=\"\" class=\"wp-image-617057\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-21.png 1059w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-21-18x5.png 18w\" sizes=\"auto, (max-width: 1059px) 100vw, 1059px\"><\/figure><p class=\"wp-block-paragraph\"><em>How LogicMonitor agents connect through proxy gateways to LLM clusters, injecting parameters and retrieving functional responses for validation.<\/em><\/p><h2 id=\"h-api-parameters-and-their-use-cases\" class=\"wp-block-heading\">API Parameters and Their Use Cases<\/h2><p class=\"wp-block-paragraph\">These tuning parameters control how an LLM responds, from the length and style of the output to how creative or focused it should be. Small changes here can dramatically affect tone, accuracy, and cost.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1080\" height=\"528\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-18.png\" alt=\"\" class=\"wp-image-617054\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-18.png 1080w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-18-18x9.png 18w\" sizes=\"auto, (max-width: 1080px) 100vw, 1080px\"><\/figure><p class=\"wp-block-paragraph\"><em>Reference for tuning key model behaviors across creativity, diversity, repetition, and response length.<\/em><\/p><p class=\"wp-block-paragraph\"><strong>Pro Tip:<\/strong> Use either Temperature or Top-p for tuning style, not both. Fine-tuning these variables is essential for aligning model behavior to business goals.<\/p><h2 id=\"h-turning-llm-benchmarking-into-an-ongoing-practice\" class=\"wp-block-heading\">Turning LLM Benchmarking Into an Ongoing Practice<\/h2><p class=\"wp-block-paragraph\">To understand how LLMs behave across tasks, LogicMonitor tests multiple models using a consistent methodology. This helps compare tone, latency, cost, and more.<\/p><p class=\"wp-block-paragraph\">Teams can:<\/p><ul class=\"wp-block-list\">\n<li>Send the <strong>same prompt<\/strong> to multiple models (e.g., GPT, Claude, Gemini)<\/li>\n\n\n\n<li>Measure <strong>latency<\/strong>, <strong>style<\/strong>, <strong>accuracy<\/strong>, and <strong>cost<\/strong> side-by-side<\/li>\n\n\n\n<li>Detect <strong>model drift<\/strong> when output changes unexpectedly<\/li>\n\n\n\n<li>Test <strong>fallback routing<\/strong> logic when a model degrades or fails<\/li>\n\n\n\n<li>Simulate <strong>regional prompts<\/strong> for localization or compliance<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">In one multi-model test, LogicMonitor, through Catchpoint, recorded latency spikes exceeding 27 seconds for a local deployment, while OpenAI maintained higher but more stable response times than Claude or Gemini.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1071\" height=\"508\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-17.png\" alt=\"\" class=\"wp-image-617053\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-17.png 1071w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-17-18x9.png 18w\" sizes=\"auto, (max-width: 1071px) 100vw, 1071px\"><\/figure><p class=\"wp-block-paragraph\"><em>Average LLM response time showing latency spikes for local agent and sustained higher latency for OpenAI<\/em><\/p><p class=\"wp-block-paragraph\">The graph above shows results from the same customer test, with each line representing a different LLM responding to the same prompt under controlled conditions. The variations highlight both transient spikes and sustained latency patterns, giving teams the evidence they need to assess performance and reliability. Detecting these anomalies early allows teams to trigger fallback routing automatically, switching to a backup model before users are impacted.<\/p><p class=\"wp-block-paragraph\">LogicMonitor&rsquo;s vendor-neutral platform enables teams to evaluate, compare, and orchestrate multiple LLMs from a single interface. In the example below from Catchpoint, that approach revealed 100% availability for Claude, OpenAI, and Gemini during the test period, but also clear differences in average response time, from 3.3 seconds for Gemini to 6.8 seconds for OpenAI.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1080\" height=\"372\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-20.png\" alt=\"\" class=\"wp-image-617056\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-20.png 1080w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-20-18x6.png 18w\" sizes=\"auto, (max-width: 1080px) 100vw, 1080px\"><\/figure><p class=\"wp-block-paragraph\"><em>Catchpoint dashboard showing LLM availability, regional incidents, and per-model response times<\/em><\/p><p class=\"wp-block-paragraph\">The dashboard also tracks downloaded byte volumes, which can highlight efficiency differences between providers, and maps incidents geographically so teams can pinpoint where performance issues occur.<\/p><p class=\"wp-block-paragraph\">By combining these metrics with prompt-level scoring, LogicMonitor provides teams an end-to-end view of LLM performance. That includes not only the quality of model responses, but also the reliability of API gateways, proxies, and network paths that can affect delivery. As part of the broader LogicMonitor platform, this LLM visibility connects directly to Edwin AI&rsquo;s intelligence layer, where anomaly detection and governed workflows can automate response when model performance degrades.<\/p><p class=\"wp-block-paragraph\">In practice, that means teams can:<\/p><ul class=\"wp-block-list\">\n<li><strong>Evaluate model tone, cost, and performance before integration<\/strong> &ndash; Test accuracy, tone, style, and brand voice alignment against your own data before committing to a model.<\/li>\n\n\n\n<li><strong>Continuously monitor LLM drift, hallucination risk, and latency across APIs<\/strong> &ndash; Detect subtle output changes, tone\/style mismatches, or quality regressions before they reach end-users.<\/li>\n\n\n\n<li><strong>Run side-by-side tests with prompt scoring and fallback logic<\/strong> &ndash; Measure output quality and validate automated failover strategies.<\/li>\n\n\n\n<li><strong>Track gateway and proxy reliability to ensure end-to-end LLM delivery<\/strong> &ndash; Confirm the entire request path is healthy, not just the model itself.<\/li>\n\n\n\n<li><strong>Adapt tests to any model, deployment style, or geography<\/strong> &ndash; Apply the same monitoring approach to cloud-hosted, on-premises, or hybrid LLMs worldwide.<\/li>\n\n\n\n<li><strong>Test for security and safety compliance<\/strong> &ndash; Use synthetic prompts to trigger edge cases and validate that models meet responsible AI guidelines.<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">LLMs aren&rsquo;t static assets. They&rsquo;re constantly evolving, often in ways that affect accuracy, cost, and reliability without notice. In production environments, &ldquo;set it and forget it&rdquo; isn&rsquo;t an option. With LM Internet Performance Monitoring, teams can continuously verify performance across providers, regions, and deployment models, detect drift or regressions before they impact users, and validate failover strategies under real-world conditions.<\/p><p class=\"wp-block-paragraph\">By operationalizing trust with measurable metrics, from latency and availability to tone and brand alignment, you turn LLM monitoring from a reactive chore into a proactive advantage. The result is faster issue resolution, higher model reliability, and a clear understanding of which LLM is the right fit at any given moment.<\/p><h2 id=\"h-recommended-reading\" class=\"wp-block-heading\">Recommended Reading<\/h2><p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.logicmonitor.com\/ai-observability\">AI Observability<\/a>: Track the performance and reliability of AI-powered assistants like chatbots, copilots, and digital agents across regions and providers.<\/p><p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.logicmonitor.com\/blog\/agentic-aiops-and-observability\">Agentic AIOps and Observability<\/a>: Monitoring AI agents, orchestration logic, and toolchains that rely on LLMs to ensure end-to-end resilience.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-calendar-check\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xxs fs-md-text-display-xs fs-lg-text-display-sm font-medium text-core-blue-900\">\n        Monitor every LLM in your stack before the next silent update catches you off guard.      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900 \">\n        <p>LogicMonitor, powered by Catchpoint, gives you continuous visibility into LLM performance, drift, and reliability across providers and regions.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/catchpoint-demo\" class=\"btn btn-link\" target=\"_self\">\n         Request a Demo          <span class=\"icon-end\"><svg class=\"\" width=\"20px\" height=\"20px\" style=\"fill: #060F4B\">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-arrow-right\"><\/use>\n    <\/svg><\/span>\n      <\/a>\n        <\/div>\n            <\/div>\n<\/div><h4 id=\"h-faqs\" class=\"wp-block-heading\">FAQs<\/h4><div class=\"accordion-block accordion-block--light\">\n      <div class=\"accordion-block__items\">\n              <div class=\"accordion-block__item active\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-what-is-llm-drift-and-why-does-it-matter\">\n            What is LLM drift and why does it matter?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer active\">\n            <p>LLM drift occurs when a model&rsquo;s outputs change after a silent update, affecting tone, accuracy, or consistency. It matters because teams relying on LLMs in production may not notice degraded quality until end users are impacted.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item \">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-does-logicmonitor-monitor-llm-performance\">\n            How does LogicMonitor monitor LLM performance?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer \">\n            <p>LogicMonitor uses Internet Performance Monitoring to send live prompts to multiple LLMs across geographies. It captures response latency, tone, coherence, and freshness, then scores and compares results to detect anomalies and regressions.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item \">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-can-i-compare-multiple-llms-side-by-side\">\n            Can I compare multiple LLMs side by side?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer \">\n            <p> Yes. LogicMonitor&rsquo;s vendor-neutral platform lets you send the same prompt to models like GPT, Claude, and Gemini simultaneously. You can measure latency, accuracy, cost, and style differences, and set up automated fallback routing when a model degrades.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div><p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Les LLMs se mettent \u00e0 jour silencieusement, d\u00e9rivent de mani\u00e8re impr\u00e9visible et ont des performances variables selon les r\u00e9gions. Apprenez \u00e0 surveiller et \u00e0 comparer en continu les mod\u00e8les d'IA en production.<\/p>","protected":false},"author":16,"featured_media":621301,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[5035],"tags":[5339,5348,7850,7859,7760,7908,7854,6677,7866,7883],"industry":[7523],"role":[6786],"lm_strategic_tags":[],"topic":[7842],"class_list":["post-617049","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-technology","role-itops","topic-internet-performance-monitoring"],"acf":{"page_language":"english","translated_pages":"","updated_date":null,"author_section_checkbox":true,"author_image":617027,"author_linkedin":"https:\/\/www.linkedin.com\/in\/denton-chikura-422186201\/","author_name":"Denton Chikura","author_job_title":"Technical Writer","author_dept":"","author_bio":"Denton Chikura is a technical writer and longtime observability advocate focused on helping site reliability engineers and engineering teams discover the tools and capabilities that strengthen internet resilience. He works at the intersection of monitoring, performance, and infrastructure to make complex systems more understandable and usable, bridging the gap between deep technical detail and real\u2011world operations. His goal is to help teams build faster, detect issues earlier, and recover smarter, ultimately making the internet a better, more reliable place for everyone.","reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.2 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>How to Monitor and Trust the LLMs Powering Your AI | LogicMonitor<\/title>\n<meta name=\"description\" content=\"LLMs drift. Performance varies. 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AI"}]},{"@type":"WebSite","@id":"https:\/\/www.logicmonitor.com\/fr\/#website","url":"https:\/\/www.logicmonitor.com\/fr\/","name":"LogicMonitor","description":"","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.logicmonitor.com\/fr\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"fr-FR"},{"@type":"Person","@id":"https:\/\/www.logicmonitor.com\/fr\/#\/schema\/person\/bfbb8cb00c9595482098c66aa78b9def","name":"destiny.setzer@logicmonitor.com","url":"https:\/\/www.logicmonitor.com\/fr\/blog\/author\/destiny-setzer"}]}},"_links":{"self":[{"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/posts\/617049","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/users\/16"}],"replies":[{"embeddable":true,"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/comments?post=617049"}],"version-history":[{"count":5,"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/posts\/617049\/revisions"}],"predecessor-version":[{"id":622039,"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/posts\/617049\/revisions\/622039"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/media\/621301"}],"wp:attachment":[{"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/media?parent=617049"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/categories?post=617049"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/tags?post=617049"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/industry?post=617049"},{"taxonomy":"role","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/role?post=617049"},{"taxonomy":"lm_strategic_tags","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/lm_strategic_tags?post=617049"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/fr\/wp-json\/wp\/v2\/topic?post=617049"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":617043,"date":"2026-08-11T16:30:09","date_gmt":"2026-08-11T21:30:09","guid":{"rendered":"https:\/\/www.logicmonitor.com\/?p=617043"},"modified":"2026-08-11T16:30:10","modified_gmt":"2026-08-11T21:30:10","slug":"aws-outage-how-do-you-prepare-for-the-failure-of-your-own-safety-net","status":"publish","type":"post","link":"https:\/\/www.logicmonitor.com\/fr\/blog\/aws-outage-how-do-you-prepare-for-the-failure-of-your-own-safety-net","title":{"rendered":"R\u00e9trospective de panne : comment la panne d'AWS a r\u00e9v\u00e9l\u00e9 le risque de la surveillance h\u00e9berg\u00e9e dans le cloud"},"content":{"rendered":"<?xml encoding=\"UTF-8\"><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50 rtc-text-content--no-top-pad\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-book-open\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xs fs-md-text-display-sm fs-lg-text-display-md font-medium text-core-blue-900\">\n        Le t\u00e9l\u00e9chargement rapide :      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900 headline-is-quote\">\n        <p>Catchpoint Internet Sonar detected the AWS outage 16 minutes before AWS acknowledged it, proving that cloud-independent monitoring delivers the early warning teams need.<\/p>\n      <\/div>\n    \n                  <ul class=\"rtc-text-content__bullet-list\">\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Cloud-hosted monitoring tools from Datadog, New Relic, Dynatrace, and others lost visibility during the outage because they relied on the same infrastructure that failed.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Organizations that lacked independent external monitoring spent critical minutes flying blind, learning about the outage from customer complaints and social media instead of their own tools.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>A five-step resilience framework, from separating monitoring from monitored infrastructure to mapping dependencies and investing in Internet Performance Monitoring, closes the visibility gap.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Audit your monitoring architecture today: if your observability stack lives in a single cloud, your next outage will be invisible until it&rsquo;s already impacting customers.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\" id=\"h-when-aws-s-massive-outage-struck-it-didn-t-just-take-down-cloud-services-apps-and-enterprise-platforms-it-also-knocked-out-many-of-the-monitoring-systems-organizations-depend-on-for-real-time-answers-observability-companies-including-datadog-new-relic-checkly-dynatrace-speedcurve-and-splunk-observability-lost-visibility-or-functionality-precisely-when-organizations-needed-them-most\"><a href=\"https:\/\/www.tomsguide.com\/news\/live\/amazon-outage-october-2025\">When AWS&rsquo;s massive outage<\/a> struck, it didn&rsquo;t just take down cloud services, apps, and enterprise platforms. It also knocked out many of the monitoring systems organizations depend on for real-time answers. Observability companies, including Datadog, New Relic, Checkly, Dynatrace, SpeedCurve, and Splunk Observability, lost visibility or functionality precisely when organizations needed them most.<\/p><p class=\"wp-block-paragraph\">In those first, chaotic 15 to 20 minutes, before teams knew the problem was AWS East, most organizations were flying blind. Their monitoring tools live in the very cloud that just failed, so there was no way to see what was really happening.<\/p><p class=\"wp-block-paragraph\">Ensuring ongoing visibility during events like these requires a fundamentally different approach to monitoring architecture. Here&rsquo;s what organizations can do today to protect themselves before the next major outage hits.<\/p><h2 id=\"h-what-happens-when-your-monitoring-fails\" class=\"wp-block-heading\">What happens when your monitoring fails?<\/h2><p class=\"wp-block-paragraph\">En tant que <a href=\"https:\/\/adrianco.medium.com\/who-monitors-the-monitoring-systems-715a333f97fc\">Adrian Cockcroft<\/a> writes, monitoring systems themselves can fail, and when they do, organizations lose the visibility they need to respond effectively. You need monitoring that&rsquo;s independent of the systems being monitored.<\/p><p class=\"wp-block-paragraph\">The AWS outage demonstrated this principle. Organizations that relied solely on cloud-hosted monitoring tools found themselves blind to the very outage impacting their operations. <strong>Your monitoring strategy must account for the possibility that your monitoring tools themselves can fail<\/strong>.<\/p><p class=\"wp-block-paragraph\">Organizations that haven&rsquo;t audited their monitoring architecture should do so now. These five steps are a practical starting point.<\/p><h2 id=\"h-1-your-monitoring-cant-live-in-the-same-cloud-youre-trying-to-monitor\" class=\"wp-block-heading\">#1. Your monitoring can&rsquo;t live in the same cloud you&rsquo;re trying to monitor<\/h2><p class=\"wp-block-paragraph\">Relying on monitoring tools hosted exclusively in the same cloud environment as your critical systems creates a significant risk. If that cloud experiences an outage, both your production systems and your monitoring go down together, leaving you without visibility at the most critical moment.<\/p><p class=\"wp-block-paragraph\">Even as we wrapped up this post at 4pm ET, many of the leading monitoring platforms still reported incidents on their status pages.<\/p><h2 id=\"h-2-map-your-critical-third-party-dependencies\" class=\"wp-block-heading\">#2. Map your critical third-party dependencies<\/h2><p class=\"wp-block-paragraph\">Most organizations aren&rsquo;t fully aware of all the dependencies their digital systems rely on. If you&rsquo;re a retailer, for example, even if your website is architected to survive a cloud provider outage, it still depends on DNS, BGP routing, SSL certificates, CDN services, payment processing systems, third-party APIs, cloud services, and dozens of smaller components. Any of these can fail and impact your operations.<\/p><p class=\"wp-block-paragraph\"><strong>Action:<\/strong> Conduct a thorough audit of your critical systems. Internet dependency mapping tools like <a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-stack-map\">Carte de la pile Internet<\/a> can help you visualize and document every protocol, service, and third-party vendor your operations rely on, making it easier to pinpoint single points of failure and strengthen your resilience.<\/p><h2 id=\"h-3-develop-a-resilience-plan\" class=\"wp-block-heading\">#3. Develop a resilience plan<\/h2><p class=\"wp-block-paragraph\">For each critical system, develop a resilience plan that includes multi-cloud or multi-region architectures, redundant systems, and documented fallback procedures. Cloud engineering teams have embraced <a href=\"https:\/\/www.logicmonitor.com\/resources\/2026-observability-ai-trends-outlook-2\">Chaos Engineering<\/a>, a philosophy of deliberately testing failure scenarios to understand how systems break and how to respond. Things <em>will<\/em> break, and the only variable is whether you&rsquo;re prepared when they do.<\/p><p class=\"wp-block-paragraph\"><strong>Action:<\/strong> Implement chaos testing, tabletop exercises, and regular drills. Build redundancy where it matters most. Document and practice your incident response playbook.<\/p><h2 id=\"h-4-invest-in-internet-performance-monitoring\" class=\"wp-block-heading\">#4. Invest in Internet Performance Monitoring<\/h2><p class=\"wp-block-paragraph\">Many organizations haven&rsquo;t invested enough in <a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\">Internet Performance Monitoring (IPM)<\/a>, a solution that provides visibility into the performance and availability of every aspect of the internet stack, internal and external. As part of the <a href=\"https:\/\/www.logicmonitor.com\/fr\">LogicMonitor<\/a> platform, Catchpoint IPM gives you external, cloud-independent awareness to detect, diagnose, and respond to outages across the entire stack. Many cloud-hosted monitoring tools lack visibility into the Internet path itself. IPM closes that gap.<\/p><p class=\"wp-block-paragraph\"><strong>Action:<\/strong> Deploy IPM to ensure you have external visibility into cloud providers, DNS, CDN, and other critical services.<\/p><h2 id=\"h-5-make-resilience-a-priority\" class=\"wp-block-heading\">#5. Make resilience a priority<\/h2><p class=\"wp-block-paragraph\">Resilience shouldn&rsquo;t be an afterthought. Internet systems are interdependent and fragile. Invest in the planning, redundancy, runbooks, and processes needed to make resilience a reality.<\/p><p class=\"wp-block-paragraph\">Investing in resilience can feel difficult amidst the push for consolidation and rising observability costs. But <a href=\"https:\/\/thenewstack.io\/why-synthetic-tracing-delivers-better-data-not-just-more-data\/\">prioritizing high-quality, actionable signal<\/a> reduces costs while improving visibility. LogicMonitor&rsquo;s unified platform, combining <a href=\"https:\/\/www.logicmonitor.com\/fr\/infrastructure-monitoring\">LM Envision<\/a>,<a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\"> Catchpoint IPM<\/a>, et <a href=\"https:\/\/www.logicmonitor.com\/fr\/edwin-ai\">Edwin AI<\/a> in a single telemetry pipeline, is built around signal quality and purposeful AI.<\/p><p class=\"wp-block-paragraph\">Some organizations are creating dedicated Chief Resilience Officer roles, a signal of how seriously the industry is taking Internet dependency risk.<\/p><h2 id=\"h-how-internet-performance-monitoring-tools-caught-the-incident-16-minutes-ahead-of-aws-reporting-it\" class=\"wp-block-heading\">How Internet Performance Monitoring tools caught the incident 16 minutes ahead of AWS reporting it<\/h2><p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-health\">Internet Sonar<\/a> detected the AWS outage at 06:55 AM UTC, a full 16 minutes before AWS updated its status page at 07:11 AM UTC.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"901\" height=\"384\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-13.png\" alt=\"\" class=\"wp-image-617045\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-13.png 901w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-13-18x8.png 18w\" sizes=\"auto, (max-width: 901px) 100vw, 901px\"><\/figure><p class=\"wp-block-paragraph\"><em>Catchpoint Internet Sonar dashboard showing global impact of the AWS outage, with Asia Pacific, Europe, Middle East and Africa, Latin America and North America affected<\/em><\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"901\" height=\"459\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-14.png\" alt=\"\" class=\"wp-image-617046\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-14.png 901w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-14-18x9.png 18w\" sizes=\"auto, (max-width: 901px) 100vw, 901px\"><\/figure><p class=\"wp-block-paragraph\"><em>Scatterplot visualization of test performance and failures from dozens of monitoring locations and services during the AWS outage. Across the timeline, there&rsquo;s a sharp spike in failed tests and dramatically increased response times.<\/em><\/p><p class=\"wp-block-paragraph\">Those 16 minutes have a real cost. Without visibility, teams can&rsquo;t triage, escalate, or communicate status to the business. Every minute without visibility extends the incident&rsquo;s impact on customers, revenue, and internal confidence.<\/p><h2 id=\"h-conclusion\" class=\"wp-block-heading\">Conclusion<\/h2><p class=\"wp-block-paragraph\">The AWS outage showed that even well-resourced organizations can lose monitoring visibility within minutes when their tools depend on the infrastructure that just failed. Every layer of the <a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-stack-map\">Internet Stack<\/a>, from cloud providers and DNS to CDN, SSL certificates, APIs, and payment processors, introduces risk. The next failure could come from any of them. Outages will happen. What matters is how prepared your organization is to respond.<\/p><p class=\"wp-block-paragraph\" id=\"h-\">Organizations that rely solely on cloud-hosted monitoring tools risk losing visibility to the very incidents that threaten their operations. Organizations that want to avoid the same outcome should adopt independent external monitoring, <a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/internet-stack-map\">map their dependencies<\/a>, invest in resilience planning, and practice their incident response before the next outage.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-calendar-check\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xxs fs-md-text-display-xs fs-lg-text-display-sm font-medium text-core-blue-900\">\n        See how cloud-independent monitoring keeps you visible when your infrastructure goes dark.      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900\">\n        <p>LogicMonitor, through Catchpoint IPM, delivers external, always-on visibility across the entire internet stack, so your team can detect and respond to outages before customers notice.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/catchpoint-demo\" class=\"btn btn-link\" target=\"_self\">\n        Demandez une d\u00e9mo          <span class=\"icon-end\"><svg class=\"\" width=\"20px\" height=\"20px\" style=\"fill: #060F4B\">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-arrow-right\"><\/use>\n    <\/svg><\/span>\n      <\/a>\n        <\/div>\n            <\/div>\n<\/div><h4 id=\"h-faqs\" class=\"wp-block-heading\">FAQ<\/h4><div class=\"accordion-block accordion-block--light\">\n      <div class=\"accordion-block__items\">\n              <div class=\"accordion-block__item active\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-why-did-cloud-hosted-monitoring-tools-fail-during-the-aws-outage\">\n            Why did cloud-hosted monitoring tools fail during the AWS outage?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer active\">\n            <p>Most leading observability platforms, including Datadog, New Relic, and Dynatrace, host their infrastructure on AWS. When AWS experienced its outage, these tools lost functionality because they depended on the same cloud environment that failed. This left organizations without the visibility they needed to diagnose and respond to the incident.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-did-catchpoint-ipm-detect-the-outage-before-aws-reported-it\">\n            How did Catchpoint IPM detect the outage before AWS reported it?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>Catchpoint IPM continuously monitors billions of signals in real time from monitoring locations that are independent of any single cloud provider. Because it operates outside the affected infrastructure, it detected performance degradation and failures at 06:55 AM UTC, a full 16 minutes before AWS updated its status page.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-what-is-internet-performance-monitoring-and-why-does-it-matter-for-outage-preparedness\">\n            What is Internet Performance Monitoring and why does it matter for outage preparedness?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>Internet Performance Monitoring (IPM) provides visibility into the performance and availability of every layer of the internet stack, including DNS, BGP, CDN, SSL, and cloud services. Unlike cloud-hosted monitoring tools, IPM operates independently and can detect issues across external dependencies that internal observability platforms miss.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div>","protected":false},"excerpt":{"rendered":"<p>La panne d'AWS a mis hors service les outils de surveillance h\u00e9berg\u00e9s dans le cloud au moment o\u00f9 on en avait le plus besoin. D\u00e9couvrez cinq \u00e9tapes pour maintenir la visibilit\u00e9 lors de la prochaine panne majeure.<\/p>","protected":false},"author":16,"featured_media":621296,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[5035],"tags":[5408,7850,7867,7910,7851,7760,7864,7911,7854,7890],"industry":[6790],"role":[6786],"lm_strategic_tags":[],"topic":[7842],"class_list":["post-617043","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-all","role-itops","topic-internet-performance-monitoring"],"acf":{"page_language":"english","translated_pages":"","updated_date":null,"author_section_checkbox":true,"author_image":617027,"author_linkedin":"https:\/\/www.linkedin.com\/in\/denton-chikura-422186201\/","author_name":"Denton Chikura","author_job_title":"Technical Writer","author_dept":"","author_bio":"Denton Chikura is a technical writer and longtime observability advocate focused on helping site reliability engineers and engineering teams discover the tools and capabilities that strengthen internet resilience. He works at the intersection of monitoring, performance, and infrastructure to make complex systems more understandable and usable, bridging the gap between deep technical detail and real\u2011world operations. His goal is to help teams build faster, detect issues earlier, and recover smarter, ultimately making the internet a better, more reliable place for everyone.","reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.2 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>AWS Outage and Cloud-Hosted Monitoring Risk | LogicMonitor<\/title>\n<meta name=\"description\" content=\"The October 2025 AWS outage impacted global businesses &amp; infrastructure. Learn how our Internet Sonar delivered early detection and actionable insights while cloud-hosted monitoring tools went dark.\" \/>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Outage Retrospective: How the AWS Outage Exposed the Risk of Cloud-Hosted Monitoring\" \/>\n<meta property=\"og:description\" content=\"The October 2025 AWS outage impacted global businesses &amp; infrastructure. 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en cache s\u00e9mantique pour les agents IA : comment \u00e7a fonctionne et pourquoi la surveillance est importante"},"content":{"rendered":"<?xml encoding=\"UTF-8\"><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50 rtc-text-content--no-top-pad\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-book-open\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xs fs-md-text-display-sm fs-lg-text-display-md font-medium text-core-blue-900\">\n        Le t\u00e9l\u00e9chargement rapide :      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900 headline-is-quote\">\n        <p>Semantic caching matches LLM queries by meaning instead of exact text, eliminating redundant model calls and reducing response times.<\/p>\n      <\/div>\n    \n                  <ul class=\"rtc-text-content__bullet-list\">\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Traditional caching delivers near-zero hit rates on natural language workloads because users rarely phrase queries the same way twice.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Agentic AI systems are especially vulnerable: a single task can chain five to ten LLM calls, and silent cache failures compound cost and latency at every step.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>Internet Performance Monitoring (IPM) validates cache behavior by tracking hit\/miss rates, semantic similarity scores, and latency splits in real time.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                      <li class=\"bullet-list-item\">\n              <span class=\"bullet-list-item__icon\">\n                <svg class=\"\" width=\"24px\" height=\"24px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-check-mark\"><\/use>\n    <\/svg>              <\/span>\n              <div class=\"bullet-list-item__content\">\n                                  <span class=\"bullet-list-item__content-heading fs-sm-text-sm fs-md-text-md fs-lg-text-md text-midnight-blue-500\">\n                    <p>In controlled testing with Catchpoint IPM, cache hits cut response times by 50%, confirming that semantic caching delivers measurable savings when properly monitored.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p class=\"wp-block-paragraph\"><\/p><h2 id=\"h-every-llm-call-costs-money-semantic-caching-changes-the-math\" class=\"wp-block-heading\">Every LLM Call Costs Money. Semantic Caching Changes the Math.<\/h2><p class=\"wp-block-paragraph\">Every call to a large language model burns tokens, and tokens cost money. As AI systems scale, especially agentic architectures that chain multiple LLM calls per task, the cost and latency of repeated queries add up fast. A single agent resolving one support ticket might make five to ten LLM calls. Multiply that across thousands of requests per day, and the numbers become difficult to ignore.<\/p><p class=\"wp-block-paragraph\">Semantic caching is the optimization layer that addresses this. Instead of sending every prompt to the model, a semantic cache identifies when a new query is close enough in meaning to a previous one and returns the stored response. The result: fewer redundant LLM calls, lower latency, and significantly reduced spend.<\/p><p class=\"wp-block-paragraph\">This post covers what semantic caching is, why traditional caching falls short for natural language workloads, where semantic caching delivers the most value, the design trade-offs teams should watch for, how to monitor it effectively, and real test data proving the impact.<\/p><h2 id=\"h-what-is-semantic-caching\" class=\"wp-block-heading\">What Is Semantic Caching?<\/h2><p class=\"wp-block-paragraph\">Traditional caching stores responses based on exact string matches. If the same question has been asked before, verbatim, the system returns a fast answer from cache. But if the phrasing changes even slightly, the system treats it as a brand-new request.<\/p><p class=\"wp-block-paragraph\">Semantic caching takes a different approach. Instead of matching by text, it matches by meaning. It uses embeddings (numerical representations of the intent behind a query) to determine whether a new request is close enough to a previous one. If two queries are semantically similar, the system can return the same result without reprocessing it through the LLM.<\/p><h3 id=\"h-how-it-works\" class=\"wp-block-heading\">Comment \u00e7a marche<\/h3><ol class=\"wp-block-list\">\n<li><strong>Receive the prompt.<\/strong> A user or system sends a natural language query to the application.<\/li>\n\n\n\n<li><strong>Generate an embedding.<\/strong> The system converts the prompt into a vector, a numerical representation of its meaning.<\/li>\n\n\n\n<li><strong>Search the semantic cache.<\/strong> The system compares the new vector against previously stored embeddings to find similar prompts.<\/li>\n\n\n\n<li><strong>If similarity exceeds the threshold, return the cached response.<\/strong> The match is close enough in meaning that the stored answer applies, so the system returns it without calling the LLM.<\/li>\n\n\n\n<li><strong>If no match, send to the LLM and cache the new response.<\/strong> The system processes the query through the model, stores both the embedding and the response, and makes them available for future matches.<\/li>\n<\/ol><p class=\"wp-block-paragraph\">This is especially useful in AI systems where users might ask the same thing in many different ways. With semantic caching, &ldquo;Who&rsquo;s the President of the US?&rdquo; and &ldquo;Who runs America?&rdquo; can trigger the same cached response, saving time, compute, and cost.<\/p><h2 id=\"h-why-traditional-caching-falls-short-for-llms\" class=\"wp-block-heading\">Why Traditional Caching Falls Short for LLMs<\/h2><p class=\"wp-block-paragraph\">Exact-match caching works well for structured data: API calls with predictable parameters, database queries, static asset requests. But natural language doesn&rsquo;t behave that way. People rarely phrase things identically. &ldquo;Explain this error,&rdquo; &ldquo;Why am I seeing this error?,&rdquo; and &ldquo;What caused this issue?&rdquo; all express the same intent, but a string-based cache treats each one as a separate, uncached request.<\/p><p class=\"wp-block-paragraph\">The result is near-zero cache hit rates in most natural language workloads. The cache exists, it&rsquo;s populated, but it almost never fires because the matching logic doesn&rsquo;t account for meaning.<\/p><p class=\"wp-block-paragraph\">This mismatch between string-level caching and meaning-level workloads is the core reason traditional caching provides limited value for LLM-powered applications. Semantic caching closes that gap by shifting the comparison from exact text to vector similarity.<\/p><h2 id=\"h-why-semantic-caching-matters-for-agentic-ai\" class=\"wp-block-heading\">Why Semantic Caching Matters for Agentic AI<\/h2><p class=\"wp-block-paragraph\">Agentic AI systems don&rsquo;t just respond to single prompts. They plan, reason, and act across multiple steps, each involving an LLM call: retrieving documents, rephrasing responses, deciding what to do next. In these architectures, a silent cache failure doesn&rsquo;t just mean a slower response. It can derail entire multistep workflows, driving up latency and cost at every stage.<\/p><p class=\"wp-block-paragraph\">The challenge is that these failures are often invisible. The API returns a 200 OK, but behind the scenes, every missed cache hit sends an expensive call to the backend model. Teams don&rsquo;t see the problem until the bill arrives or performance degrades.<\/p><p class=\"wp-block-paragraph\">Unlike traditional caching, semantic caches introduce risks that are harder to detect:<\/p><ul class=\"wp-block-list\">\n<li><strong>Model updates breaking embeddings.<\/strong> When the underlying embedding model changes, previously cached vectors may no longer match new queries the same way.<\/li>\n\n\n\n<li><strong>Vector drift.<\/strong> Over time, small shifts in embedding space can cause cache misses even for queries that should match.<\/li>\n\n\n\n<li><strong>Phrasing variation.<\/strong> Users and agents express the same intent differently, leading to unexpected misses that accumulate across multi-step workflows.<\/li>\n<\/ul><h2 id=\"h-where-semantic-caching-delivers-the-most-value\" class=\"wp-block-heading\">Where Semantic Caching Delivers the Most Value<\/h2><p class=\"wp-block-paragraph\">Semantic caching has the biggest impact in workloads where similar questions come up repeatedly but in varied phrasing. A few patterns stand out:<\/p><ul class=\"wp-block-list\">\n<li><strong>Agentic and workflow-based systems.<\/strong> Agents frequently rephrase similar sub-questions during multi-step reasoning. Caching these intermediate queries reduces both latency and token spend across the workflow.<\/li>\n\n\n\n<li><strong>Customer support and help desks.<\/strong> Support queries cluster around common issues. &ldquo;How do I reset my password?,&rdquo; &ldquo;I can&rsquo;t log in,&rdquo; and &ldquo;My account is locked&rdquo; all point to the same resolution, and a semantic cache can serve them from a single stored response.<\/li>\n\n\n\n<li><strong>Internal knowledge assistants.<\/strong> Employees ask the same questions in different ways across teams and time zones. Semantic caching prevents redundant LLM calls for questions that have already been answered.<\/li>\n\n\n\n<li><strong>Documentation and Q&amp;A systems.<\/strong> Search-style questions about product features, configuration, or troubleshooting tend to have high semantic overlap, making them strong candidates for cache reuse.<\/li>\n<\/ul><h2 id=\"h-design-trade-offs-to-watch\" class=\"wp-block-heading\">Design Trade-offs to Watch<\/h2><p class=\"wp-block-paragraph\">Semantic caching isn&rsquo;t a set-and-forget optimization. Several design decisions affect whether it actually delivers value in production:<\/p><p class=\"wp-block-paragraph\"><strong>Similarity threshold tuning.<\/strong> The threshold that determines whether a cached response is &ldquo;close enough&rdquo; requires workload-specific tuning. Set it too low, and the cache returns irrelevant responses for queries that only loosely match. Set it too high, and hit rates drop because the system demands near-exact similarity. There&rsquo;s no universal default; the right threshold depends on the application and the consequences of a wrong match.<\/p><p class=\"wp-block-paragraph\"><strong>Cache freshness.<\/strong> Some prompts depend on data that changes. A cached answer about current pricing, system status, or recent events can become stale quickly. Teams need TTL (time-to-live) policies and context-aware invalidation strategies to prevent the cache from serving outdated information.<\/p><p class=\"wp-block-paragraph\"><strong>Observability.<\/strong> Without visibility into hit and miss rates, latency impact, and cost savings, teams can&rsquo;t tell whether the cache is doing its job. Caching should be measurable infrastructure, not a hidden optimization that&rsquo;s assumed to work.<\/p><h2 id=\"h-how-to-monitor-semantic-caching\" class=\"wp-block-heading\">How to Monitor Semantic Caching<\/h2><p class=\"wp-block-paragraph\">Trusting a semantic cache requires measuring how well it&rsquo;s working. Three monitoring strategies help teams validate cache behavior and catch problems before they affect users or budgets.<\/p><h3 id=\"h-strategy-1-test-semantically-similar-queries\" class=\"wp-block-heading\">Strategy 1: Test Semantically Similar Queries<\/h3><p class=\"wp-block-paragraph\">Semantic caching lives or dies on how well it matches similar questions. Synthetic monitoring can simulate different phrasings of the same intent:<\/p><ul class=\"wp-block-list\">\n<li>&ldquo;Who&rsquo;s the President of the US?&rdquo;<\/li>\n\n\n\n<li>&ldquo;Who runs the US government?&rdquo;<\/li>\n\n\n\n<li>&ldquo;Commander-in-Chief of America?&rdquo;<\/li>\n<\/ul><p class=\"wp-block-paragraph\">Then compare the outcomes: Did they result in cache hits or misses? What were the semantic similarity scores? This gives visibility into whether the caching system is recognizing intent consistently. For agentic AI, it isn&rsquo;t enough for one query to be fast. Teams need confidence that <em>tout<\/em> expressions of the same intent are covered.<\/p><h3 id=\"h-strategy-2-track-semantic-similarity-scores\" class=\"wp-block-heading\">Strategy 2: Track Semantic Similarity Scores<\/h3><p class=\"wp-block-paragraph\">Semantic caches often return a similarity score (for example, 0.85) to indicate how close the new query is to an existing cached answer. Teams can monitor these scores over time, visualize trends, and alert if scores drop below thresholds.<\/p><p class=\"wp-block-paragraph\">If the embedding model changes or query phrasing drifts, scores could drop, leading to unexpected misses and rising costs. Tracking these numbers ensures the semantic cache stays reliable and that teams aren&rsquo;t spending on backend calls unnecessarily.<\/p><h3 id=\"h-strategy-3-measure-real-world-latency-differences\" class=\"wp-block-heading\">Strategy 3: Measure Real-World Latency Differences<\/h3><p class=\"wp-block-paragraph\">One of the biggest benefits of semantic caching is speed. Cache hits should be significantly faster than misses. Monitoring tools can:<\/p><ul class=\"wp-block-list\">\n<li>Split metrics for cache hits vs. misses<\/li>\n\n\n\n<li>Show precise latency differences<\/li>\n\n\n\n<li>Alert when cache misses cause slowdowns<\/li>\n<\/ul><p class=\"wp-block-paragraph\">In the test results shared below, cache miss response time was approximately 5 seconds, while cache hit response time was approximately 2 seconds. That&rsquo;s a 2.5x speedup. In agentic AI systems, that gap is the difference between a seamless interaction and a noticeable pause.<\/p><h2 id=\"h-case-study-validating-semantic-caching-with-internet-performance-monitoring\" class=\"wp-block-heading\">Case Study: Validating Semantic Caching with Internet Performance Monitoring<\/h2><p class=\"wp-block-paragraph\">To put these monitoring strategies into practice,<a href=\"https:\/\/www.logicmonitor.com\/fr\/logicmonitor-catchpoint\"> Point de rattrapage<\/a>, a LogicMonitor company, used<a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\"> Supervision des performances Internet<\/a> (IPM) to validate semantic caching behavior in a controlled lab environment.<\/p><h3 id=\"h-lab-setup\" class=\"wp-block-heading\">Lab Setup<\/h3><p class=\"wp-block-paragraph\">A FastAPI application ran locally, exposing a <strong>\/search<\/strong> endpoint via a public URL. Every incoming search query followed this logic:<\/p><ul class=\"wp-block-list\">\n<li><strong>Cosmos DB lookup:<\/strong> Check whether a similar semantic query has been seen before, using the query text as the key.<\/li>\n\n\n\n<li><strong>Cache hit:<\/strong> Return the cached vector embedding directly, saving time and cost.<\/li>\n\n\n\n<li><strong>Cache miss:<\/strong> Call Gemini Pro to generate a new vector embedding for the query, then store it in Cosmos DB for future reuse.<\/li>\n\n\n\n<li>The embedding was sent to Azure AI Search, performing a vector similarity search to find the top matching documents.<\/li>\n\n\n\n<li>The search results plus two custom HTTP headers were returned: <strong>X-Semantic-Cache<\/strong> (hit or miss) and <strong>X-Semantic-Score<\/strong> (for example, 0.8543) indicating how close the new query was to previous ones.<\/li>\n<\/ul><h3 id=\"h-test-methodology\" class=\"wp-block-heading\">Test Methodology<\/h3><p class=\"wp-block-paragraph\">The team simulated user queries against the public endpoint. The test sent randomized prompts (for example, &ldquo;NYC weather,&rdquo; &ldquo;New York forecast&rdquo;) to trigger both cache hits and misses. Catchpoint captured and parsed the semantic headers using regex to track cache efficiency (percentage of hits vs. misses) and semantic similarity scores. The data was visualized in dashboards to show latency differences between hits and misses.<\/p><h3 id=\"h-results\" class=\"wp-block-heading\">Results<\/h3><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1344\" height=\"578\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-10.png\" alt=\"\" class=\"wp-image-617037\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-10.png 1344w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-10-18x8.png 18w\" sizes=\"auto, (max-width: 1344px) 100vw, 1344px\"><\/figure><p class=\"wp-block-paragraph\">Cache Hits vs. Misses: Measurable Latency Gap<\/p><p class=\"wp-block-paragraph\">The trend line showed that overall response time was 50% to 250% higher when the semantic cache returned a miss compared to a hit.<\/p><p class=\"wp-block-paragraph\">Diving deeper, the first run of a prompt went to the backend (a cache miss), with higher latency and costs.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1124\" height=\"580\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-12.png\" alt=\"\" class=\"wp-image-617039\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-12.png 1124w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-12-18x9.png 18w\" sizes=\"auto, (max-width: 1124px) 100vw, 1124px\"><\/figure><p class=\"wp-block-paragraph\">First Run: Cache Miss with High Latency<\/p><p class=\"wp-block-paragraph\">The second run of the same semantic query hit the cache, cutting response times by 50%.<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"816\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-11.png\" alt=\"\" class=\"wp-image-617038\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-11.png 1000w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-11-15x12.png 15w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\"><\/figure><p class=\"wp-block-paragraph\">Second Run: Served from Cache (Hit). Same Semantic Score (Prompt Matched). Response Time Is 50% Lower<\/p><figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1408\" height=\"120\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-9.png\" alt=\"\" class=\"wp-image-617036\" srcset=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-9.png 1408w, https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/07\/image-9-18x2.png 18w\" sizes=\"auto, (max-width: 1408px) 100vw, 1408px\"><figcaption class=\"wp-element-caption\">Semantic Caching Performance Dashboard<\/figcaption><\/figure><p class=\"wp-block-paragraph\">Key findings from the test:<\/p><ul class=\"wp-block-list\">\n<li>Cache misses increased latency by 50% to 250% compared to cache hits.<\/li>\n\n\n\n<li>Cache hits delivered a 2.5x speedup in response time.<\/li>\n\n\n\n<li>The second run of a semantically similar prompt reduced response time by 50%.<\/li>\n<\/ul><p class=\"wp-block-paragraph\"><\/p><p class=\"wp-block-paragraph\">These results provided real, quantifiable evidence that semantic caching reduces API calls to the LLM backend and improves response times, validating the monitoring strategies described above.<\/p><h2 id=\"h-final-takeaway\" class=\"wp-block-heading\">Final Takeaway<\/h2><p class=\"wp-block-paragraph\">Semantic caching is becoming core infrastructure for real-time AI systems. It reduces cost, lowers latency, and makes agentic workflows more efficient. It&rsquo;s also uniquely fragile. Changes in language, embedding drift, or model updates can quietly degrade performance in ways that don&rsquo;t surface in standard API monitoring.<\/p><p class=\"wp-block-paragraph\">Monitoring semantic caching with<a href=\"https:\/\/www.logicmonitor.com\/fr\/internet-performance-monitoring\"> LM Internet Performance Monitoring<\/a> gives teams the confidence that their systems are fast, reliable, and cost-efficient. LogicMonitor unifies LM Envision, Catchpoint, and Edwin AI into one Autonomous IT platform, giving teams the full picture from user experience to backend infrastructure.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n      <span class=\"head-icon\"><svg class=\"\" width=\"50px\" height=\"50px\" style=\"fill: \">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-light-calendar-check\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\n          <h4 class=\"rtc-text-content__headline fs-sm-text-display-xxs fs-md-text-display-xs fs-lg-text-display-sm font-medium text-core-blue-900\">\n        Monitor every layer of your AI stack, from user experience to backend model calls.      <\/h4>\n    \n          <div class=\"rtc-text-content__body fs-sm-text-md fs-md-text-lg fs-lg-text-lg text-core-blue-900\">\n        <p>LogicMonitor brings together LM Envision, Catchpoint, and Edwin AI in one Autonomous IT platform, giving teams the full picture across agentic workflows.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/catchpoint-demo\" class=\"btn btn-link\" target=\"_self\">\n        Voyez-le en action          <span class=\"icon-end\"><svg class=\"\" width=\"20px\" height=\"20px\" style=\"fill: #060F4B\">\n        <use xlink:href=\"https:\/\/www.logicmonitor.com\/wp-content\/themes\/unicorntwentyfive\/assets\/icons\/sprite.svg#icon-arrow-right\"><\/use>\n    <\/svg><\/span>\n      <\/a>\n        <\/div>\n            <\/div>\n<\/div><h4 id=\"h-faqs\" class=\"wp-block-heading\">FAQ<\/h4><div class=\"accordion-block accordion-block--light\">\n      <div class=\"accordion-block__items\">\n              <div class=\"accordion-block__item active\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-does-semantic-caching-differ-from-traditional-caching-for-llm-applications\">\n            How does semantic caching differ from traditional caching for LLM applications?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer active\">\n            <p> Traditional caching relies on exact string matches, which almost never fire in natural language workloads because users phrase the same question differently every time. Semantic caching converts queries into vector embeddings and matches by meaning, so &ldquo;Who&rsquo;s the President?&rdquo; and &ldquo;Who runs America?&rdquo; return the same cached result. This shift from text-level to meaning-level comparison is what makes caching viable for LLM-powered systems.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-what-causes-a-semantic-cache-to-silently-fail\">\n            What causes a semantic cache to silently fail?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>Three common causes are embedding model updates (which change how vectors are generated, breaking prior matches), vector drift over time, and natural variation in how users phrase queries. These failures return a 200 OK response, so teams only discover the problem when costs spike or latency degrades.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-can-i-measure-whether-my-semantic-cache-is-actually-saving-money\">\n            How can I measure whether my semantic cache is actually saving money?            <span class=\"accordion-block__icon\">\n              <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M6 9L12 15L18 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><\/path>\n<\/svg>\n            <\/span>\n          <\/h3>\n          <div class=\"accordion-block__answer\">\n            <p>Track three things: cache hit vs. miss rates, semantic similarity scores over time, and latency split by hit and miss. In the tests described in this article, cache hits delivered a 2.5x speedup. If your hit rate drops or similarity scores trend downward, your cache may be degrading without obvious symptoms.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div>","protected":false},"excerpt":{"rendered":"<p>Le cache s\u00e9mantique r\u00e9duit les co\u00fbts et la latence des LLM en associant les requ\u00eates par leur sens. D\u00e9couvrez son fonctionnement, ses \u00e9checs silencieux et comment le surveiller avec l'IPM.<\/p>","protected":false},"author":16,"featured_media":621291,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[5035],"tags":[7753,5348,7850,7882,5634,7813,6291,7908,6677,7866],"industry":[7523],"role":[7843],"lm_strategic_tags":[],"topic":[6781],"class_list":["post-617024","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-technology","role-sre","topic-observability"],"acf":{"page_language":"english","translated_pages":"","updated_date":null,"author_section_checkbox":true,"author_image":617027,"author_linkedin":"https:\/\/www.linkedin.com\/in\/denton-chikura-422186201\/","author_name":"Denton Chikura","author_job_title":"Technical Writer","author_dept":"","author_bio":"Denton Chikura is a technical writer and longtime observability advocate focused on helping site reliability engineers and engineering teams discover the tools and capabilities that strengthen internet resilience. He works at the intersection of monitoring, performance, and infrastructure to make complex systems more understandable and usable, bridging the gap between deep technical detail and real\u2011world operations. His goal is to help teams build faster, detect issues earlier, and recover smarter, ultimately making the internet a better, more reliable place for everyone.","reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.2 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Semantic Caching for AI Agents: Monitoring LLM Performance | LogicMonitor<\/title>\n<meta name=\"description\" content=\"Semantic caching cuts LLM costs and latency by avoiding redundant queries. 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