[{"id":612891,"date":"2026-06-17T10:45:51","date_gmt":"2026-06-17T15:45:51","guid":{"rendered":"https:\/\/www.logicmonitor.com\/?p=612891"},"modified":"2026-06-17T10:45:58","modified_gmt":"2026-06-17T15:45:58","slug":"ai-workload-observability-itops-priority","status":"publish","type":"post","link":"https:\/\/www.logicmonitor.com\/de\/blog\/ai-workload-observability-itops-priority","title":{"rendered":"Warum KI-Observability eine kritische ITOps-Priorit\u00e4t ist"},"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        Der schnelle \u00dcberblick      <\/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 Observability is a Critical Priority for ITOps Teams<\/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 workloads add new failure points across GPUs, LLMs, APIs, cloud, and internet dependencies.<\/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>ITOps teams need one view of workload health, user impact, and root cause.<\/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>Edwin AI and Catchpoint help teams cut alert noise, validate user experience, and act faster.<\/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><strong>Empfehlung: <\/strong>Position AI workload observability to leaders as a non-negotiable addition.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n  \n  <div class=\"rtc-text-content__wrapper\">\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>See how LogicMonitor helps ITOps teams monitor AI workloads, reduce blind spots, and move toward Autonomous IT.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/de\/ki-monitoring\" class=\"btn btn-link\" target=\"_self\">\n        Schedule a meeting          <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><p>AI has shifted from experimental pilots to everyday business operations. Customers are interacting with AI-powered applications. Engineering teams are building with LLMs, GPUs, APIs, and automation at a much faster pace.<\/p><p>That adds to the visibility strain on already overburdened ITOps teams.<\/p><p>A single AI interaction can depend on multiple touchpoints including cloud infrastructure, GPU capacity, model APIs, vector databases, application services, internet paths, SaaS tools, and third-party providers. With those resource requirements, combined with hybrid infrastructure pathways, that complexity can quickly impact end outcomes. When performance drops, teams need to know what happened, who is impacted, and what to do next.<\/p><p>That is why AI workload observability is crucial.<\/p><p>AI workload visibility gives IT Operations teams the ability to monitor AI systems in production, control costs, protect user experiences, and move toward an autonomous operating model.<\/p><h2 class=\"wp-block-heading\" id=\"h-ai-workloads-create-new-blind-spots\">AI workloads create new blind spots<\/h2><p>Holistic observability matters across hybrid infrastructure, but AI adds new layers of resource level dependency.<\/p><p>Teams now need to understand metrics such as GPU utilization, memory, temperature, power usage, model latency, and token consumption. On the front end, the same teams need to ensure that user experience remains optimal. Adding to the complexity, they need to know whether an issue is coming from internal infrastructure, an external LLM provider, a network path, DNS, CDN, or a third-party service. It can quickly get confusing.<\/p><p>Without that connected view, teams lose time during incidents, or can&rsquo;t even see if an incident is imminent. Alerts pile up. Teams chase symptoms. Business leaders ask for answers. And application downtime starts to become a real risk.<\/p><p>AI workload observability helps answer the most pressing questions:<\/p><p>&middot;&nbsp; &nbsp; &nbsp; Is the AI service healthy?<\/p><p>&middot;&nbsp; &nbsp; &nbsp; Are users being impacted?<\/p><p>&middot;&nbsp; &nbsp; &nbsp; Where is the issue coming from?<\/p><p>&middot;&nbsp; &nbsp; &nbsp; What action should we take next?<\/p><p>For ITOps leaders, creating a solid observability foundation is the key to operating AI at scale.<\/p><h2 class=\"wp-block-heading\" id=\"h-the-path-to-autonomous-it\">The path to Autonomous IT<\/h2><p>As AI adoption grows, operations teams need a model that is faster, more connected, and less dependent on manual investigation.<\/p><p>That is where Autonomous IT comes in.<\/p><p>The operating model helps ITOps teams see what is happening, understand what matters, and take action faster. Over time, more of that action becomes automated, consistent, and repeatable.<\/p><p>For AI workloads, this means connecting infrastructure health, GPU performance, LLM behavior, internet dependencies, digital experience, event intelligence, and remediation workflows.<\/p><p>Together, LogicMonitor, Edwin AI, and Catchpoint make that possible.<\/p><h2 class=\"wp-block-heading\" id=\"h-logicmonitor-lets-itops-teams-track-ai-workload-performance\">LogicMonitor lets ITOps teams track AI workload performance<\/h2><p>LogicMonitor helps teams monitor the infrastructure and services that power AI workloads in production.<\/p><p>That includes hybrid infrastructure, compute resources, Kubernetes clusters, applications, APIs, logs, events, and the systems supporting AI workloads. Teams can make sense of signals that come from GPUs, LLMs, vector databases, and application dependencies in one operational view, and understand what those signals mean for their workload&rsquo;s operational health.<\/p><p>For GPU monitoring, LogicMonitor helps teams track utilization, memory usage, temperature, power draw, and overall health. That visibility is important because GPUs are expensive, performance-sensitive resources. Idle GPUs waste budget. Overloaded GPUs create latency. Poor GPU visibility makes it harder to scale AI responsibly.<\/p><p>For LLM monitoring, LogicMonitor helps teams track latency, error rates, token usage, API performance, and provider availability. As organizations build AI assistants, copilots, and agentic workflows, these signals become essential to understanding reliability, performance, and cost.<\/p><p>When ITOps teams get clear views of AI workload health across the stack, they can feel prepared to make resource changes, prevent cost overruns, and build scalable applications.<\/p><h2 class=\"wp-block-heading\" id=\"h-edwin-ai-helps-teams-move-from-signal-to-action\">Edwin AI helps teams move from signal to action<\/h2><p>AI workloads generate a multitude of alerts, events, logs, and performance signals. All the additional telemetry could create more noise if it&rsquo;s not set up the right way.<\/p><p>Edwin AI helps teams cut through that complexity.<\/p><p>Instead of asking teams to manually make sense of GPU saturation, LLM latency, API errors, and performance issues, Edwin AI helps surface the relationships between those signals. Edwin AI does this by correlating related events, reducing alert noise, summarizing incident context, and identifying likely root causes.<\/p><p>That matters during AI incidents, where every minute spent gathering context slows down response.<\/p><p>With Edwin AI and event intelligence capabilities, teams can understand what changed, determine which systems are involved, and decide the next best action to take. When paired with automated remediation, known issues can follow consistent response paths instead of relying on manual escalation every time.<\/p><p>This is how teams begin moving from reactive monitoring toward Autonomous IT.<\/p><h2 class=\"wp-block-heading\" id=\"h-catchpoint-adds-the-internet-and-user-experience-view\">Catchpoint adds the internet and user experience view<\/h2><p>AI services depend on more than internal infrastructure.<\/p><p>A slow or unavailable AI experience can be caused by DNS, CDN, ISP, cloud edge, routing, or third-party API issues. Even when backend systems look healthy, users may still be experiencing poor performance.<\/p><p>Catchpoint adds that outside-in perspective.<\/p><p>With Internet Performance Monitoring, teams can determine how internet paths, service providers, regions, and external dependencies affect AI service delivery. With Real User Monitoring, teams can see how users actually experience AI-powered applications across locations, networks, and devices. With Synthetic Monitoring, teams can proactively test critical journeys before users are impacted.<\/p><p>For AI workload observability, this helps teams quickly separate internal issues from external dependencies.<\/p><p>If an AI assistant slows down, the cause may be GPU saturation, LLM provider latency, application middleware, DNS, CDN, or a regional network issue. Catchpoint gives teams the user and internet context needed to make that call faster.<\/p><h2 class=\"wp-block-heading\" id=\"h-a-holistic-approach-to-ai-operations\">A holistic approach to AI operations<\/h2><p>The operating model toward Autonomous IT looks like this:<\/p><p>&middot;&nbsp; &nbsp; &nbsp; Observe the AI workload<\/p><p>&middot;&nbsp; &nbsp; &nbsp; Understand the incident<\/p><p>&middot;&nbsp; &nbsp; &nbsp; Validate the user experience<\/p><p>&middot;&nbsp; &nbsp; &nbsp; Automate the response<\/p><p>To help operations teams take action on AI workloads, LogicMonitor provides core visibility across hybrid infrastructure, cloud, applications, GPUs, and LLMs, with context that lets teams know how to solve issues..<\/p><p>Edwin AI adds event intelligence, incident context, root cause support, and the ability to move faster from detection to action.<\/p><p>Catchpoint extends the view to internet performance, synthetic testing, and real user experience.<\/p><p>Together, the platform helps operations teams observe AI services holistically and operate with intention to scale.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-itops-teams-should-prioritize\">What ITOps teams should prioritize<\/h2><p>If you are building the case for AI workload observability, focus on the outcomes your leadership team already cares about.<\/p><ul class=\"wp-block-list\">\n<li><strong>Performance confidence<\/strong><strong><br><\/strong> Know whether AI services, GPUs, LLMs, APIs, and infrastructure are performing as expected.<\/li>\n\n\n\n<li><strong>Cost control<\/strong><strong><br><\/strong> Identify underused GPUs, inefficient model usage, high token consumption, and overprovisioned cloud resources.<\/li>\n\n\n\n<li><strong>Faster root cause analysis<\/strong><strong><br><\/strong> Correlate signals across infrastructure, model providers, application telemetry, internet dependencies, and user experience.<\/li>\n\n\n\n<li><strong>User-impact prioritization<\/strong><strong><br><\/strong> Understand which issues affect real users, key regions, critical services, or important business journeys.<\/li>\n\n\n\n<li><strong>Automatisierte Fehlerbehebung<\/strong><strong><br><\/strong> Turn known issues into repeatable response workflows that reduce manual effort and speed resolution.<\/li>\n\n\n\n<li><strong>Executive-ready visibility<\/strong><strong><br><\/strong> Give leaders clear insight into AI availability, performance, usage, risk, and operational readiness.<\/li>\n<\/ul><h2 class=\"wp-block-heading\" id=\"h-ai-needs-an-operating-model-that-scales-with-it\">AI needs an operating model that scales with it<\/h2><p>AI is changing what the business expects from IT. Teams are asked to support new services, complex workloads, and multiple dependencies.<\/p><p>That complexity cannot be managed with disconnected tools and manual processes.<\/p><p>ITOps teams need observability that connects AI workload health, infrastructure performance, internet dependencies, and user experience. They need AI-powered intelligence that explains what matters. They need automation that turns insight into action.<\/p><p>LogicMonitor, Edwin AI, and Catchpoint give teams the foundation to operate AI services with confidence and build toward Autonomous IT.<\/p><h2 class=\"wp-block-heading\" id=\"h-ready-to-monitor-ai-workloads-with-confidence\">Ready to monitor AI workloads with confidence?<\/h2><p>LogicMonitor helps teams monitor AI workloads, GPUs, LLMs, infrastructure, internet dependencies, and digital experience in one connected operating model.<\/p><p>With Edwin AI and Catchpoint, teams can reduce blind spots, accelerate incident response, prioritize real user impact, and move closer to Autonomous IT.<\/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        Don&rsquo;t wait for AI complexity to become an outage      <\/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 workloads are already changing how IT operates. Act now with LogicMonitor, Edwin AI, and Catchpoint to reduce blind spots, protect user experience, and build the foundation for Autonomous IT.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/de\/ki-monitoring\" class=\"btn btn-link\" target=\"_self\">\n        Mehr erfahren          <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>","protected":false},"excerpt":{"rendered":"<p>KI-Arbeitslastbeobachtbarkeit hilft ITOps-Teams, KI-Dienste zu \u00fcberwachen, blinde Flecken zu reduzieren und sich in Richtung autonomer IT zu bewegen.<\/p>","protected":false},"author":16,"featured_media":612894,"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":[7856,7855,7812,7850,7814,5697,7857,7813,6232,7858],"industry":[6790],"language":[7],"role":[6786],"lm_search_queries":[],"lm_strategic_tags":[],"topic":[6769],"class_list":["post-612891","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-all","language-english","role-itops","topic-aiops-automation"],"acf":{"is_global_bar_disabled":false,"is_global_bar_overriden":false,"is_search_excluded":false,"page_language":"english","translated_pages":"","reviewers":false,"is_global_form_disabled":false,"is_global_form_override":false,"component_layouts":false,"related_resources":false,"updated_date":"","author_section_checkbox":true,"reviewer_name":"","author_image":"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2023\/07\/Ismath-Mohideen-headshot-1.png","author_linkedin":"","author_name":"Ismath Mohideen ","author_job_title":"Sr. Manager, Product Marketing","author_dept":"","author_bio":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.9 (Yoast SEO v27.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Why AI observability is a critical ITOps priority | LogicMonitor<\/title>\n<meta name=\"description\" content=\"Learn why AI workload observability is now critical for ITOps, and how LogicMonitor, Edwin AI, and Catchpoint help teams monitor AI services, reduce blind spots, and move toward Autonomous IT.\" \/>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Why AI observability is a critical ITOps priority\" \/>\n<meta property=\"og:description\" content=\"Learn why AI workload observability is now critical for ITOps, and how LogicMonitor, Edwin AI, and Catchpoint help 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KI-Untersuchung f\u00fcr ITOps: Was sie ist und warum sie wichtig ist"},"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        Der schnelle \u00dcberblick      <\/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>Investigation is the most time-consuming and cognitively demanding phase of incident response, and it&rsquo;s the phase least served by existing tooling.<\/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 investigation agents reason across multiple data sources to identify root causes automatically, moving beyond alert correlation into genuine diagnostic reasoning.<\/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>Multi-agent coordination and context graphs accelerate diagnosis by starting from precedent rather than rediscovery.<\/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>AI investigation improves with every resolved incident through continuous learning loops that retain what worked, what failed, and why.<\/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 using AI investigation have reduced resolution times by 30-60% and alert noise by up to 91%.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p>Modern ITOps teams have spent years investing in better detection and alerting. The tools are faster, the dashboards are richer, and anomaly detection keeps improving.&nbsp;<\/p><p>Yet when a complex incident hits, the response still looks the same: engineers manually correlating logs, metrics, topology, and change records across disconnected systems, racing to find a root cause before the business impact compounds.<\/p><p>The gap between detecting a problem and understanding its cause is where most teams lose the battle. Industry data shows that a significant share of incidents are still first detected through customer complaints rather than proactive monitoring. Detection has matured, but investigation, the cognitive work of diagnosing why something broke, remains stubbornly manual.&nbsp;<\/p><p>This article explains what deep AI investigation is, how it works under the hood, and why it represents the next critical capability for ITOps teams moving toward Autonomous IT.<\/p><h2 class=\"wp-block-heading\" id=\"h-why-investigation-is-the-hardest-part-of-incident-response\">Why Investigation Is the Hardest Part of Incident Response<\/h2><p>Detection and alerting have benefited from a decade of engineering investment. Anomaly detection, threshold tuning, and event correlation have all improved significantly. Investigation hasn&rsquo;t kept pace, and the reasons are structural.<\/p><p>Cross-domain failures are the norm in hybrid environments. A single incident can span cloud infrastructure, on-prem servers, network devices, and third-party services. Engineers context-switch between monitoring tools, mentally reconstructing a failure chain that no single dashboard can show them. As a result, the cognitive load is substantial, including correlating metrics, logs, traces, topology, and change records simultaneously while the clock ticks on a business-impacting outage.<\/p><p>Tribal knowledge makes this worse. Senior engineers carry years of environment-specific experience in their heads, understanding which services depend on which, what a particular metric pattern means in context, and where past incidents had their root causes. That knowledge doesn&rsquo;t scale. When those engineers are unavailable, investigation slows dramatically.<\/p><p>The cost compounds quickly. Slow investigation extends downtime, triggers escalation chains, and leads to repeated incidents when the actual root cause goes unidentified. A<a href=\"https:\/\/www.logicmonitor.com\/resources\/logicmonitor-edwin-ai-total-economic-impact-study-by-forrester\"> Forrester Total Economic Impact study<\/a> shared a 313% ROI for organizations that close this gap, and the business case is already measurable across production deployments.<\/p><p>Unlike the familiar<a href=\"https:\/\/www.logicmonitor.com\/blog\/network-monitoring-avoid-alert-fatigue\"> alert fatigue<\/a> problem, the core issue here is the reasoning gap between knowing something is wrong and understanding why.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-deep-ai-investigation-means\">What Deep AI Investigation Means<\/h2><p>AI investigation is the process of <a href=\"https:\/\/www.logicmonitor.com\/blog\/what-is-an-ai-agent\">KI-Agenten<\/a> autonomously reasoning through an incident: ingesting signals from multiple sources, enriching them with operational context like topology, service dependencies, change history, and past incidents, then generating and ranking hypotheses about root cause before presenting findings with supporting evidence. This capability operates at a fundamentally different level than alert summarization, dashboard consolidation, or basic pattern matching.<\/p><p>Where earlier AIOps tools focused on anomaly detection and alert grouping, AI investigation constructs a chain of evidence that connects symptoms to causes across infrastructure layers. The distinction matters because grouping related alerts still requires a human to determine why those alerts are related and what caused the underlying issue.<\/p><p>Investigation is the missing layer between observability and automation. Observability shows what&rsquo;s happening, and automation acts on known conditions, but investigation is the reasoning that connects the two with critical <a href=\"https:\/\/www.logicmonitor.com\/blog\/why-itops-automation-needs-context-graphs\">Kontext<\/a>. Without it, the link between detection and action depends entirely on human cognitive throughput, and in complex environments with thousands of interdependent services, that doesn&rsquo;t scale.<\/p><p>Historical pattern matching accelerates this by comparing current conditions against prior incident fingerprints. Failed remediation paths from past incidents are preserved and avoided. Investigation agents build a chain of evidence that shows both what broke and how the failure propagated across the stack.<\/p><h3 class=\"wp-block-heading\" id=\"h-recommend-delivering-actionable-findings\">Recommend: Delivering Actionable Findings<\/h3><p>Investigation agents produce human-readable summaries explaining the root cause in natural language, attaching supporting evidence such as correlated signals, a timeline of events, affected services, and confidence scores. Recommended next steps include specific remediation actions or runbook references.<\/p><p>Findings route to the right resolver group with full context, eliminating the handoff tax that extends resolution in traditional workflows. When an L1 engineer receives investigation results backed by evidence chains and confidence scores, they can resolve incidents that would previously have required escalation to L2 or L3.<\/p><h2 class=\"wp-block-heading\" id=\"h-ai-investigation-in-complex-hybrid-environments\">AI Investigation in Complex Hybrid Environments<\/h2><p>Cross-domain investigation is where AI reasoning delivers clear, measurable value. When a failure spans cloud infrastructure, on-prem servers, network devices, and third-party services, manual investigation requires engineers to navigate separate monitoring tools, correlate timestamps across systems with different time zones and formats, and mentally reconstruct the failure chain.<\/p><p>AI investigation agents operate across these boundaries simultaneously. Multi-source ingestion pulls telemetry from every layer into a unified diagnostic view. The context graph maps service dependencies across environments, so an agent can trace an application slowdown in the cloud back to a network configuration change in the data center, even when the two systems are monitored by different tools.<\/p><p>Gartner has identified multiagent systems as one of its <a href=\"https:\/\/www.gartner.com\/en\/articles\/top-technology-trends-2026\">Top 10 Strategic Technology Trends<\/a> for 2026, reflecting broader industry momentum toward modular AI agents that collaborate on complex tasks. In hybrid investigation environments, this approach takes a concrete form: specialized agents handle correlation, diagnosis, and<a href=\"https:\/\/www.logicmonitor.com\/blog\/agentic-autonomous-itops-incident-lifecycle\"> remediation as a coordinated system<\/a>. A Correlation Agent manages signal ingestion and noise reduction, an Investigation Agent handles diagnosis, a Dashboards Agent surfaces visual context, and an Automation Agent carries out approved remediation actions.<\/p><h2 class=\"wp-block-heading\" id=\"h-continuous-learning-how-ai-investigation-gets-smarter-over-time\">Continuous Learning: How AI Investigation Gets Smarter Over Time<\/h2><p>Static rule-based systems perform the same way on day one thousand as they do on day one. AI investigation systems improve with each resolved incident because every outcome feeds back into the knowledge graph as structured state.<\/p><p>When a root cause is confirmed, that confirmation strengthens the pattern for future matching. When a remediation path fails, that failure is preserved alongside the conditions that led to it, preventing the system from recommending the same approach under similar circumstances. Escalation outcomes, override decisions, and resolution timelines all become first-class data points.<\/p><p>Over time, investigation starts closer to the answer because the system has accumulated precedent for similar conditions. Alert noise drops as correlation improves.<a href=\"https:\/\/www.logicmonitor.com\/blog\/reduce-mttr-with-ai\"> Resolution times<\/a> decrease as investigation begins from precedent rather than from scratch. Organizations have reported 30% or greater reductions in MTTR and up to 91% alert noise reduction as these feedback loops compound across hundreds of investigations.<\/p><h2 class=\"wp-block-heading\" id=\"h-how-edwin-ai-puts-deep-investigation-into-practice\">How Edwin AI Puts Deep Investigation into Practice<\/h2><p><a href=\"https:\/\/www.logicmonitor.com\/de\/edwin-ai\">Edwin AI<\/a> is LogicMonitor&rsquo;s AI agent for ITOps, built around the investigation workflow described above. As part of LogicMonitor&rsquo;s AI-first platform for Autonomous IT, Edwin AI is embedded directly into the system, operating across LM Envision&rsquo;s telemetry foundation and <a href=\"https:\/\/www.logicmonitor.com\/blog\/edwin-ai-catchpoint-internet-visibility-autonomous-it\">Catchpoint&rsquo;s Internet experience data<\/a> through a single context graph.<\/p><p>For investigation specifically, Edwin AI deploys specialized agents that handle each phase of the diagnostic process. Event Intelligence agents manage signal correlation and noise reduction, compressing thousands of alerts into focused incident candidates. Investigation agents enrich those candidates with topology, change records, and past incident patterns from the ITOps context graph, then generate and rank root cause hypotheses with supporting evidence. The output is a natural language summary that explains what happened, why, and what to do next.<\/p><p>What makes this practical for enterprise teams is<a href=\"https:\/\/www.logicmonitor.com\/blog\/ai-agent-governance-agentic-itops-workflows\"> governed autonomy<\/a>. Edwin AI supports approvals, audit trails, rollback mechanisms, and human override throughout the workflow. When a remediation action is recommended, it can trigger an existing Ansible Playbook through the <a href=\"https:\/\/www.logicmonitor.com\/blog\/agentic-aiops-self-healing-it-logicmonitor-ibm-red-hat\">IBM watsonx and Red Hat Ansible Automation Platform integration<\/a>, or auto-generate a new playbook if none exists for the identified root cause. The system acts within boundaries that the team defines, not as an unchecked autonomous agent.<\/p><p>Edwin AI also reasons across sources that extend beyond traditional monitoring: ITSM records, collaboration tools, change management systems, and a growing MCP ecosystem of integrations. This multi-source reasoning is what enables investigation across hybrid environments where the root cause and the symptoms sit in different infrastructure layers. Production deployments have delivered 80-91% alert noise reduction and 30% or greater reductions in MTTR, with a<a href=\"https:\/\/www.logicmonitor.com\/resources\/logicmonitor-edwin-ai-total-economic-impact-study-by-forrester\"> Forrester-supported 313% ROI<\/a> over three years.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-deep-ai-investigation-means-for-itops-teams\">What Deep AI Investigation Means for ITOps Teams<\/h2><p>Deep AI investigation changes daily work for <a href=\"https:\/\/www.logicmonitor.com\/solutions\/l2-l3-sre-itops-automation-productivity\">L2\/L3 engineers and SREs<\/a> in concrete ways. Time spent on manual log parsing and cross-tool correlation shifts to reviewing AI-generated findings and validating root causes. Fewer after-hours escalations occur because investigation agents surface root cause before issues compound. L1 teams resolve more incidents independently because AI provides clear, evidence-backed summaries.<\/p><p>Senior engineers shift from reactive diagnosis to strategic infrastructure work and reliability engineering. The cognitive load of holding an entire environment&rsquo;s history and dependencies in working memory transfers to the context graph, freeing experienced operators for higher-value work.<\/p><p>This is the path toward<a href=\"https:\/\/www.logicmonitor.com\/de\/solutions\/autonomous-it\"> Autonomes IT-Monitoring<\/a>, where investigation bridges the gap between reactive monitoring and proactive, self-healing 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    \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>See how Edwin AI helps ITOps teams diagnose incidents faster, cut through alert noise, and move from reactive troubleshooting to proactive operations.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/de\/edwin-ai-demo\" class=\"btn btn-link\" target=\"_self\">\n        Demo vereinbaren          <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><h3 class=\"wp-block-heading\" id=\"h-faqs\">FAQs<\/h3><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-ai-investigation-in-itops\">\n            What Is AI Investigation in ITOps?            <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>AI investigation is the process of using AI agents to autonomously diagnose IT incidents by correlating signals across infrastructure, enriching them with operational context, and identifying the most likely root cause with supporting evidence.<br>\nHier konzentrieren wir uns auf Monitoring und Observability: die Ebene, die MSPs nutzen, um den Zustand von Infrastruktur, Cloud, Netzwerk, SaaS und digitaler Erfahrung ihrer Kunden zu verstehen.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-does-ai-investigation-differ-from-traditional-aiops\">\n            How Does AI Investigation Differ from Traditional AIOps?            <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>Traditional AIOps focuses on alert correlation and noise reduction. AI investigation goes further by reasoning through the full diagnosis, generating hypotheses, ranking root causes by probability, and delivering actionable findings with evidence chains.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-can-ai-investigation-work-across-hybrid-environments\">\n            Can AI Investigation Work Across Hybrid 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>AI investigation agents ingest telemetry from cloud, on-prem, network, and third-party sources simultaneously, creating a unified diagnostic view that doesn&rsquo;t require engineers to context-switch between tools.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-does-ai-investigation-improve-over-time\">\n            How Does AI Investigation Improve Over Time?            <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>Every investigation outcome feeds back into the system&rsquo;s knowledge graph. The system retains which root causes were confirmed, which remediation paths succeeded or failed, and what conditions led to each outcome. This continuous learning loop makes future investigations faster and more accurate.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div>","protected":false},"excerpt":{"rendered":"<p>KI-gest\u00fctzte Untersuchungen helfen ITOps-Teams, von der manuellen Protokollanalyse zur automatisierten Ursachenanalyse \u00fcberzugehen. Erfahren Sie, wie das funktioniert und warum es die Diagnose von St\u00f6rungen ver\u00e4ndert.<\/p>","protected":false},"author":16,"featured_media":613649,"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":[7753,5331,5339,7783,7777,7815,7760,6872,7050,7084],"industry":[6790],"language":[7],"role":[6786],"lm_search_queries":[],"lm_strategic_tags":[],"topic":[6769],"class_list":["post-613645","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-all","language-english","role-itops","topic-aiops-automation"],"acf":{"is_global_bar_disabled":false,"is_global_bar_overriden":false,"is_search_excluded":false,"page_language":"english","translated_pages":"","reviewers":false,"is_global_form_disabled":false,"is_global_form_override":false,"component_layouts":false,"related_resources":false,"updated_date":"","author_section_checkbox":true,"reviewer_name":"","author_image":"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2025\/02\/margo-2-1.jpeg","author_linkedin":"https:\/\/www.linkedin.com\/in\/mspoda\/","author_name":"Margo Poda","author_job_title":"Sr. Content Marketing Manager, AI","author_dept":"Ewin AI","author_bio":"Margo Poda leads content strategy for Edwin AI at LogicMonitor. With a background in both enterprise tech and AI startups, she focuses on making complex topics clear, relevant, and worth reading\u2014especially in a space where too much content sounds the same. She\u2019s not here to hype AI; she\u2019s here to help people understand what it can actually do."},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.9 (Yoast SEO v27.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Deep AI Investigation for ITOps: What It Is and Why It Matters | LogicMonitor<\/title>\n<meta name=\"description\" content=\"AI investigation helps ITOps teams move from manual log parsing to automated root cause analysis. 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Matters"}]},{"@type":"WebSite","@id":"https:\/\/www.logicmonitor.com\/de\/#website","url":"https:\/\/www.logicmonitor.com\/de\/","name":"LogicMonitor","description":"","publisher":{"@id":"https:\/\/www.logicmonitor.com\/de\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.logicmonitor.com\/de\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"de"},{"@type":"Organization","@id":"https:\/\/www.logicmonitor.com\/de\/#organization","name":"LogicMonitor","url":"https:\/\/www.logicmonitor.com\/de\/","logo":{"@type":"ImageObject","inLanguage":"de","@id":"https:\/\/www.logicmonitor.com\/de\/#\/schema\/logo\/image\/","url":"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2025\/03\/lm-logo-color.png","contentUrl":"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2025\/03\/lm-logo-color.png","width":447,"height":82,"caption":"LogicMonitor"},"image":{"@id":"https:\/\/www.logicmonitor.com\/de\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/LogicMonitor\/","https:\/\/x.com\/logicmonitor","https:\/\/www.linkedin.com\/company\/logicmonitor","https:\/\/www.instagram.com\/logicmonitor\/","https:\/\/www.youtube.com\/channel\/UCeiil_Bau3hXJSNwJvyh-3Q","https:\/\/www.g2.com\/products\/logicmonitor\/reviews","https:\/\/www.capterra.com\/p\/113371\/LogicMonitor\/","https:\/\/www.trustradius.com\/products\/logicmonitor\/reviews"]},{"@type":"Person","@id":"https:\/\/www.logicmonitor.com\/de\/#\/schema\/person\/6eed89efa2f1a7bc2d16393927230350","name":"destiny.setzer@logicmonitor.com","image":{"@type":"ImageObject","inLanguage":"de","@id":"https:\/\/secure.gravatar.com\/avatar\/5cbcc0bb1812eba057595d95b89ff084dd9de9cc3ea4285aad24aafb31445419?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/5cbcc0bb1812eba057595d95b89ff084dd9de9cc3ea4285aad24aafb31445419?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/5cbcc0bb1812eba057595d95b89ff084dd9de9cc3ea4285aad24aafb31445419?s=96&d=mm&r=g","caption":"destiny.setzer@logicmonitor.com"}}]}},"_links":{"self":[{"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/posts\/613645","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/users\/16"}],"replies":[{"embeddable":true,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/comments?post=613645"}],"version-history":[{"count":5,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/posts\/613645\/revisions"}],"predecessor-version":[{"id":613653,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/posts\/613645\/revisions\/613653"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/media\/613649"}],"wp:attachment":[{"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/media?parent=613645"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/categories?post=613645"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/tags?post=613645"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/industry?post=613645"},{"taxonomy":"language","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/language?post=613645"},{"taxonomy":"role","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/role?post=613645"},{"taxonomy":"lm_search_queries","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/lm_search_queries?post=613645"},{"taxonomy":"lm_strategic_tags","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/lm_strategic_tags?post=613645"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/www.logicmonitor.com\/de\/wp-json\/wp\/v2\/topic?post=613645"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":612858,"date":"2026-06-11T10:15:08","date_gmt":"2026-06-11T15:15:08","guid":{"rendered":"https:\/\/www.logicmonitor.com\/?p=612858"},"modified":"2026-06-11T10:15:16","modified_gmt":"2026-06-11T15:15:16","slug":"internet-performance-monitoring-safeguard-revenue","status":"publish","type":"post","link":"https:\/\/www.logicmonitor.com\/de\/blog\/internet-performance-monitoring-safeguard-revenue","title":{"rendered":"Umsatz und Markenvertrauen mit Full-Stack-Sichtbarkeit sch\u00fctzen"},"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        Der schnelle \u00dcberblick      <\/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>The quick download: Most observability strategies overlook the internet layer that underpins every user&rsquo;s digital experience, leaving it almost entirely unmonitored.<\/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><span style=\"font-weight: 400\">Most IT teams monitor internal infrastructure far more rigorously than the external internet, so third-party dependencies like DNS, CDNs, and SaaS platforms are often under-observed until they degrade or fail.<\/span><\/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><span style=\"font-weight: 400\">Outside-in monitoring acts as a &ldquo;digital mystery shopper,&rdquo; validating the user experience from thousands of global locations before customers notice a problem.<\/span><\/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><span style=\"font-weight: 400\">False negatives on the Internet layer are more dangerous than noisy alerts, because customers silently churn when you miss performance issues.<\/span><\/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><span style=\"font-weight: 400\">Extend your observability strategy to include Internet Performance Monitoring and feed internet-layer signals into Edwin AI to resolve issues faster and protect the customer experience.<\/span><\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><section id=\"\" class=\"section bg-white theme-light    section-bg-dark\">\n        <div class=\"section-content container\">\n    <div class=\"full-width-media-wrapper\">\n<div class=\"media-assets-block\">\n    <div class=\"media-container object-center-center aspect-auto type-wistia_embed\" style=\"max-width: 100svh; \">\n\n          <div class=\"wistia_embed\">\n        <div class=\"\">\n          <p><script src=\"https:\/\/fast.wistia.com\/embed\/medias\/arkm4osk5v.jsonp\" async><\/script><br>\n<script src=\"https:\/\/fast.wistia.com\/assets\/external\/E-v1.js\" async><\/script><\/p>\n<div class=\"wistia_responsive_padding\" style=\"padding: 56.25% 0 0 0; position: relative;\">\n<div class=\"wistia_responsive_wrapper\" style=\"height: 100%; left: 0; position: absolute; top: 0; width: 100%;\">\n<div class=\"wistia_embed wistia_async_arkm4osk5v videoFoam=true\" style=\"height: 100%; position: relative; width: 100%;\">\n<div class=\"wistia_swatch\" style=\"height: 100%; left: 0; opacity: 0; overflow: hidden; position: absolute; top: 0; transition: opacity 200ms; width: 100%;\"><img decoding=\"async\" style=\"filter: blur(5px); height: 100%; object-fit: contain; width: 100%;\" src=\"https:\/\/fast.wistia.com\/embed\/medias\/arkm4osk5v\/swatch\" alt=\"\" aria-hidden=\"true\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n        <\/div>\n      <\/div>\n      <\/div>\n  <\/div>\n<\/div><\/div><\/section><p><\/p><p>Most IT teams monitor servers, networks, and applications, yet the infrastructure layer that carries traffic to users remains largely unmonitored. In this webinar, Andrew Keating, VP of Product and Solutions Marketing at LogicMonitor, and Mehdi Daoudi, GM of Catchpoint and the company&rsquo;s co-founder, explored why this blind spot has become a serious business risk.<\/p><p>Keating and Daoudi unpack how outside-in monitoring works, why traditional observability tools miss Internet-layer failures, and how <a href=\"https:\/\/www.logicmonitor.com\/de\/edwin-ai\">Edwin AI<\/a> turns combined internal and external signals into faster root cause identification and automated incident response.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-experts-discussed\">Was Experten diskutierten                                                       <\/h2><h3 class=\"wp-block-heading\" id=\"h-how-internet-dependencies-outpaced-most-observability-strategies\">How internet dependencies outpaced most observability strategies<\/h3><p>Most observability strategies are still built around data centers, cloud workloads, and application traces. Daoudi pointed out that every digital experience depends on a chain of third-party services, from DNS providers and CDNs to SaaS platforms and LLM APIs. A single weak link in that chain can disrupt the user journey, even when internal infrastructure is healthy.<\/p><h3 class=\"wp-block-heading\" id=\"h-three-blind-spots-that-keep-it-teams-exposed\">Three blind spots that keep IT teams exposed<\/h3><p>Daoudi described three categories of blind spots based on his 30 years of experience in IT Operations. The first is a false sense of coverage, where teams believe every entry point is monitored, even though third-party tags on a webpage prove otherwise. The second is the unknown unknown: failure scenarios like fiber cuts that teams haven&rsquo;t planned a response for. The third, and most dangerous in his view, is the false negative, where your monitoring doesn&rsquo;t detect a problem while customers silently leave for a competitor.<\/p><h3 class=\"wp-block-heading\" id=\"h-outside-in-monitoring-works-like-a-digital-mystery-shopper\">Outside-in monitoring works like a digital mystery shopper<\/h3><p>LogicMonitor&rsquo;s approach, powered by <a href=\"https:\/\/www.logicmonitor.com\/de\/internet-performance-monitoring\">Catchpoint Internet Performance Monitoring<\/a> (IPM), deploys synthetic monitors from over 3,000 global locations to validate the user experience layer by layer, from DNS resolution to final page render. Daoudi compared it to a hotel chain hiring mystery shoppers: you can&rsquo;t assume the &ldquo;room is clean&rdquo; without someone on the ground verifying it. This outside-in model detects degradation in the <a href=\"https:\/\/www.catchpoint.com\/glossary\/internet-stack\">Internet-Stack<\/a> before it becomes a customer-facing outage.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n  \n  <div class=\"rtc-text-content__wrapper\">\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><b>Outside&#8209;in monitoring<\/b><span style=\"font-weight: 400\"> means continuously testing your digital services from the public internet so you see performance and availability exactly as users do. You use external synthetic checks across DNS, CDNs, ISPs, and SaaS providers rather than relying solely on internal metrics and logs.<\/span><\/p>\n      <\/div>\n    \n      <\/div>\n<\/div><h3 class=\"wp-block-heading\" id=\"h-how-edwin-ai-turns-combined-signals-into-faster-resolution\">How Edwin AI turns combined signals into faster resolution<\/h3><p>Keating described how <a href=\"https:\/\/www.logicmonitor.com\/de\/edwin-ai\">Edwin AI<\/a>, LogicMonitor&rsquo;s agentic AIOps engine, correlates internal infrastructure signals with Catchpoint&rsquo;s internet telemetry in real time. The result is a system that can detect a trend shift like rising latency on a cloud provider and trace root cause across domains to trigger automated failover. One customer mentioned in the webinar detected an AWS degradation 13 minutes before the outage was declared and rerouted workloads to GCP with no customer impact.<\/p><h2 class=\"wp-block-heading\" id=\"h-implications-for-it-operations-leaders\">Implications for IT operations leaders<\/h2><h3 class=\"wp-block-heading\" id=\"h-your-delivery-chain-is-your-responsibility-even-the-parts-you-dont-own\">Your delivery chain is your responsibility, even the parts you don&rsquo;t own<\/h3><p>&ldquo;The customer doesn&rsquo;t care whose fault it is,&rdquo; Daoudi said. &ldquo;They only care that something they&rsquo;re interacting with works 24\/7, whether they&rsquo;re sending an email, ordering an Uber, or sending a document to be signed in the middle of the night.&rdquo; Planning for third-party failures reduces their blast radius and keeps teams ahead of customer-facing impact.<\/p><h3 class=\"wp-block-heading\" id=\"h-false-negatives-are-more-dangerous-than-false-positives\">False negatives are more dangerous than false positives<\/h3><p>The monitoring industry has spent years training teams to worry about noisy alerts. Daoudi argued the real threat is silence: &ldquo;The false negative, the not knowing you have a problem, is, in my opinion, the worst thing because customers are suffering. Typically, they don&rsquo;t even complain. They&rsquo;re moving away to your competitors, and you don&rsquo;t know about it.&rdquo; Outside-in monitoring surfaces the failures that internal telemetry can&rsquo;t reach.<\/p><h3 class=\"wp-block-heading\" id=\"h-thirteen-minutes-of-early-warning-can-save-millions-in-revenue\">Thirteen minutes of early warning can save millions in revenue<\/h3><p>During a major AWS outage, Catchpoint&rsquo;s high-frequency testing detected a trend shift 13 minutes before the outage was officially declared. The customer automatically shifted workloads to Google Cloud Platform (GCP), avoiding a catastrophic impact on one of the world&rsquo;s largest retailers. That&rsquo;s the model Daudi described for the future: &ldquo;You wake up, you read an email, and it says, last night there was an outage. The systems automatically routed around it.<\/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        Sehen Sie sich das On-Demand-Webinar an      <\/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><span style=\"font-weight: 400\">See how LogicMonitor and Catchpoint detect internet-layer failures before they impact your customers.<\/span><\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/resources\/webinar-full-stack-internet-visibility-digital-performance\" class=\"btn btn-link\" target=\"_self\">\n        Jetzt ansehen          <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><h3 class=\"wp-block-heading\" id=\"h-recommended-reading-and-webinars\">Empfohlene Lekt\u00fcre und Webinare<\/h3><ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.logicmonitor.com\/de\/internet-performance-monitoring\">Internet Performance Monitoring (IPM)<\/a>: Learn how LogicMonitor, via Catchpoint, monitors networks, regions, and providers to detect issues faster and protect user experience.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/resources\/webinar-operationalizing-lm-catchpoint-observability\">From Visibility to Action: Operationalizing LM + Catchpoint Observability<\/a>: This on-demand webinar explores how LogicMonitor and Catchpoint integrate to deliver end-to-end internet observability, with practical guidance on deployment patterns.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/blog\/edwin-ai-catchpoint-internet-visibility-autonomous-it\">Closing the Internet Gap to Enable Autonomous IT with Edwin AI<\/a>: A deep dive into why LogicMonitor acquired Catchpoint and how Edwin AI connects internet-layer signals to infrastructure monitoring for autonomous operations.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/blog\/better-together-logicmonitor-catchpoint-self-healing-enterprise\">Gemeinsam besser: Der Aufbau des selbstheilenden Unternehmens<\/a>: The original announcement of the LogicMonitor + Catchpoint acquisition, explaining the vision for a unified observability platform with self-healing capabilities.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/de\/edwin-ai\">Edwin AI: Der AIOps-Agent f\u00fcr die schnelle L\u00f6sung von Vorf\u00e4llen<\/a>: LogicMonitor&rsquo;s Edwin AI product page details how the agentic AIOps engine predicts outages, correlates alerts, and accelerates root cause analysis.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/de\/agentic-aiops-guide\">Agentic AIOps Guide<\/a>: A comprehensive resource on how agentic AIOps integrates with hybrid observability to provide full-stack visibility and proactively prevent failures.<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>Ihr Observability-Stack hat wahrscheinlich eine blinde Stelle in der Gr\u00f6\u00dfe des gesamten Internets. 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MSP-Software im Jahr 2026: Wie Sie die richtige Plattform ausw\u00e4hlen"},"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        Der schnelle \u00dcberblick      <\/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>MSPs haben bereits eine F\u00fclle von Werkzeugen. Das schwierigere Problem ist es, einen klaren \u00dcberblick dar\u00fcber zu bekommen, was in jeder Kundenumgebung vor sich geht, welche Alarme auf dasselbe Problem hinweisen und wo die Ingenieure anfangen sollen.<\/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>RMM- und PSA-Tools sind immer noch Teil des Stacks, aber sie sind nicht darauf ausgelegt, jedes Problem in Bezug auf Infrastruktur, Cloud, Netzwerk, SaaS und digitales Erlebnis zu diagnostizieren.<\/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>F\u00fcr \u00dcberwachung und Observability priorisieren Sie Multi-Tenant-Management, automatische Erkennung, Topologie, Alarmkorrelation, Berichterstattung und PSA- oder ITSM-Integrationen.<\/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>KI sollte Ingenieuren helfen, Vorf\u00e4lle nach Auswirkung zu sortieren, die wahrscheinliche Ursache zu finden, zusammenzufassen, was sich ge\u00e4ndert hat, und zu entscheiden, was als N\u00e4chstes zu tun ist.<\/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>Suchen Sie nach einer Plattform, die Ihrem Team hilft, Kunden schnell online zu bringen, Umgebungen zu durchsuchen und anzuzeigen, wann der Dienst wieder einwandfrei funktioniert.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p>Die Auswahl der richtigen MSP-Software bedeutet im Grunde die Auswahl der richtigen Betriebsebene f\u00fcr die Servicebereitstellung. MSPs unterst\u00fctzen mehr Kunden, mehr Umgebungen und mehr Alarme, aber das Hinzuf\u00fcgen eines weiteren Tools erleichtert die Arbeit nicht immer. Wenn \u00dcberwachung, Ticketing, Automatisierung und Kundenkontext in separaten Systemen leben, verlieren Ingenieure Zeit mit dem Wechseln der Bildschirme, anstatt das Problem zu l\u00f6sen.<\/p><p>Diese Verz\u00f6gerungen zeigen sich schnell durch verfehlte SLA-Ziele, ein h\u00f6heres Aufkommen am Helpdesk, engere Margen und l\u00e4ngere Wartezeiten f\u00fcr Kunden bei der Beantwortung ihrer Anfragen.<\/p><p>Dieser Blog konzentriert sich auf die \u00dcberwachungs- und Beobachtungsschicht des MSP-Software-Stacks. Das ist die Schicht, die MSPs nutzen, um \u00fcber hybride Infrastrukturen hinweg zu sehen, zusammenh\u00e4ngende Signale zu verbinden, die Grundursache zu identifizieren und zu best\u00e4tigen, dass der Dienst wiederhergestellt ist. RMM-, PSA-, Backup-, Sicherheits- und Abrechnungstools sind weiterhin wichtig, aber sie l\u00f6sen unterschiedliche Teile des Betriebsmodells.<\/p><h2 class=\"wp-block-heading\" id=\"h-msp-platforms-now-span-monitoring-automation-and-service-delivery\">MSP-Plattformen umfassen nun \u00dcberwachung, Automatisierung und Servicebereitstellung<\/h2><p>Eine Benachrichtigung teilt einem MSP lediglich mit, dass etwas Aufmerksamkeit erfordert. Die eigentliche Arbeit besteht darin, herauszufinden, wo der Ausfall begonnen hat, welche Kunden betroffen sind, welche SLAs gef\u00e4hrdet sind und was als N\u00e4chstes zu tun ist.<\/p><p>RMM-Tools sind n\u00fctzlich f\u00fcr die Verwaltung von Endpunkten und Ger\u00e4ten. PSA-Tools verwalten Tickets, SLAs, Abrechnung und Service-Workflows. Aber keine der beiden Kategorien ist darauf ausgelegt, ein Problem zu erkl\u00e4ren, das Infrastruktur, Cloud, Netzwerk, SaaS, Protokolle, Ereignisse und Benutzererfahrung \u00fcberspannt.<\/p><p>Wenn ein Vorfall eintritt, sollte die Plattform dem Team helfen, schnell drei Fragen zu beantworten:<\/p><ul class=\"wp-block-list\">\n<li>Was hat sich ge\u00e4ndert?<\/li>\n\n\n\n<li>Was ist betroffen?<\/li>\n\n\n\n<li>Was sollen wir als N\u00e4chstes tun?<\/li>\n<\/ul><p>Je weniger Zeit Ingenieure mit dem Zusammenf\u00fcgen von Hinweisen verbringen, desto schneller k\u00f6nnen sie dem Kunden mit einer Antwort zur\u00fcckkehren.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n  \n  <div class=\"rtc-text-content__wrapper\">\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>Die richtige MSP-Plattform verwandelt Alarme in Antworten: Was hat sich ge\u00e4ndert, wer ist betroffen und was sind die n\u00e4chsten Schritte.<\/p>\n      <\/div>\n    \n      <\/div>\n<\/div><h2 class=\"wp-block-heading\" id=\"h-what-is-an-msp-platform-and-why-does-it-matter\">Was ist eine MSP-Plattform und warum ist sie wichtig?<\/h2><p>Eine MSP-Plattform ist die Softwareebene, die Dienstleister nutzen, um Kundenumgebungen zu \u00fcberwachen, allt\u00e4gliche Serviceaufgaben zu verwalten und die konsistente Bereitstellung \u00fcber verschiedene Konten hinweg sicherzustellen.<\/p><p>In der Praxis bedeutet das in der Regel, dass mehrere Werkzeuge zusammenarbeiten. RMM (Remote Monitoring and Management) k\u00fcmmert sich um die Verwaltung von Endpunkten und Ger\u00e4ten. PSA (Professional Services Automation) verwaltet Tickets, SLAs (Service Level Agreements), Abrechnung und Kunden-Workflows. Monitoring- und Observability-Plattformen helfen Teams, das Geschehen in Infrastruktur, Cloud, Netzwerk, Anwendungen, Protokollen, Ereignissen und Benutzererlebnissen zu verstehen.<\/p><p>Die Effizienz von MSPs h\u00e4ngt davon ab, wie schnell Ingenieure Symptome von der Ursache trennen k\u00f6nnen. Ohne gemeinsamen Kontext wird jede Benachrichtigung zu einer weiteren Untersuchung. Mit der richtigen Plattform k\u00f6nnen Teams sehen, was sich ge\u00e4ndert hat, die Auswirkungen auf den Kunden verstehen und handeln, bevor ein kleines Problem zu einer verpassten SLA wird.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-are-the-main-types-of-msp-software\">Was sind die Haupttypen von MSP-Software?<\/h2><p>MSP-Software deckt mehrere Kategorien ab. Die meisten MSPs nutzen mehr als eine, und einige Plattformen decken mehrere Ebenen des Stacks ab.<\/p><h4 class=\"wp-block-heading\" id=\"h-1-remote-monitoring-and-management-rmm\">1) Remote Monitoring und Management (RMM)<\/h4><p>RMM-Tools (Remote Monitoring and Management) verwalten Endpunkte, Server und Ger\u00e4te \u00fcber Agenten. Sie werden h\u00e4ufig zur \u00dcberwachung des Ger\u00e4tezustands, f\u00fcr Patching, Fernzugriff und zur Wartung auf Endpoint-Ebene eingesetzt.<\/p><h4 class=\"wp-block-heading\" id=\"h-2-professional-services-automation-psa\">2) Professional Services Automation (PSA)<\/h4><p>PSA-Tools verwalten Service-Delivery-Workflows, einschlie\u00dflich Tickets, SLAs, Abrechnung, Kundenkommunikation und Berichterstattung.<\/p><h4 class=\"wp-block-heading\" id=\"h-3-monitoring-and-observability-platforms\">3) Monitoring- und Observability-Plattformen<\/h4><p>Monitoring- und Observability-Plattformen verfolgen Leistung, Verf\u00fcgbarkeit und Abh\u00e4ngigkeiten in den Umgebungen, die MSPs verwalten. Dazu k\u00f6nnen Infrastruktur, Cloud, Netzwerkger\u00e4te, SaaS-Anwendungen, DNS, APIs, Protokolle, Ereignisse und das digitale Erlebnis geh\u00f6ren.<\/p><p>Breite Abdeckung ist vom ersten Tag an wichtig. MSPs m\u00fcssen herausfinden, was l\u00e4uft, Abh\u00e4ngigkeiten abbilden und mit der Fehlerbehebung beginnen, ohne die Kundenumgebung von Hand neu aufbauen zu m\u00fcssen.<\/p><p>Kollektoren, automatische Erkennung und Topologiezuordnung beschleunigen diese Arbeit. Kollektoren erfassen Daten aus der Kundenumgebung. Die automatische Erkennung identifiziert Ressourcen. Die Topologiezuordnung zeigt, wie die Systeme verbunden sind, sodass Teams ein Problem nachverfolgen k\u00f6nnen, ohne die Karte manuell neu erstellen zu m\u00fcssen.<\/p><h4 class=\"wp-block-heading\" id=\"h-4-security-and-compliance-tools\">4) Sicherheits- und Compliance-Tools<\/h4><p>Sicherheits-, Backup- und Compliance-Tools helfen MSPs, Kundenumgebungen zu sch\u00fctzen, Risiken zu managen, Daten wiederherzustellen, Richtlinien durchzusetzen und Berichterstattungsanforderungen zu erf\u00fcllen. Diese Tools k\u00f6nnen sich mit \u00dcberwachungs- und Service-Workflows verbinden, l\u00f6sen aber unterschiedliche betriebliche Probleme.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-are-the-core-components-of-an-msp-monitoring-and-observability-platform\">Was sind die Kernkomponenten einer MSP-Plattform f\u00fcr Monitoring und Observability?<\/h2><p>Eine Monitoring- und Observability-Plattform sollte MSP-Teams eine funktionierende \u00dcbersicht \u00fcber jede Kundenumgebung, gen\u00fcgend Kontext zur Diagnose von Problemen und einen klaren Weg zu Service-Workflows bieten.<\/p><h4 class=\"wp-block-heading\" id=\"h-1-visibility\">Sichtbarkeit<\/h4><p>MSPs ben\u00f6tigen einen zuverl\u00e4ssigen \u00dcberblick \u00fcber die von ihnen unterst\u00fctzten Umgebungen: Infrastruktur, Cloud, Netzwerk, SaaS, Protokolle, Ereignisse, APIs, DNS und digitales Erlebnis. Mehr Signale helfen nur, wenn sie die Kundengesundheit besser verst\u00e4ndlich machen.<br><\/p><h4 class=\"wp-block-heading\" id=\"h-2-context\">2) Kontext<\/h4><p>Rohe Benachrichtigungen erz\u00e4hlen nur einen Teil der Geschichte. Teams m\u00fcssen auch wissen, wie Systeme zusammenh\u00e4ngen, welche Benachrichtigungen miteinander verbunden sind und wo das Problem wahrscheinlich seinen Ursprung hatte.<\/p><p>Suchen Sie nach automatischer Erkennung, Abh\u00e4ngigkeitszuordnung, Topologie, Alarmkorrelation und kundenseitiger Segmentierung. Dieser Kontext bietet Ingenieuren einen besseren Ausgangspunkt, insbesondere wenn ein Problem Alarme in mehreren Systemen ausl\u00f6st.<\/p><h4 class=\"wp-block-heading\" id=\"h-3-action\">3) Aktion<\/h4><p>Nach der Diagnose stellt sich die n\u00e4chste Frage, wie die Arbeit weitergeleitet, eskaliert und gel\u00f6st wird. Dies kann die Benachrichtigungsweiterleitung, Eskalationslogik, Behebungs-Workflows, Runbooks und Integrationen mit PSA- oder ITSM-Tools umfassen, die Tickets erstellen, aktualisieren oder schlie\u00dfen.<br><\/p><h4 class=\"wp-block-heading\" id=\"h-4-multi-tenant-management\">4) Mandantenverwaltung<\/h4><p>MSPs m\u00fcssen viele Kundenumgebungen aus einer operativen Sicht verwalten, ohne Zug\u00e4nge, Daten, Dashboards oder Berichte zu vermischen. Achten Sie auf kundenseitige Segmentierung, rollenbasierte Berechtigungen, gruppierte Sammler oder Ressourcen und kundenspezifische Dashboards oder Snapshots.<\/p><h2 class=\"wp-block-heading\" id=\"h-why-traditional-rmm-and-psa-tools-arent-enough-on-their-own\">Warum traditionelle RMM- und PSA-Tools allein nicht ausreichen<\/h2><p>RMM- und PSA-Tools sind nach wie vor wichtig, aber sie k\u00f6nnen nicht jedes Problem in einer hybriden Kundenumgebung erkl\u00e4ren. RMM kann den Zustand von Endpunkten oder Ger\u00e4ten anzeigen. PSA kann das Ticket verfolgen. Die schwierigere Arbeit besteht darin, das Signal, den betroffenen Dienst, die Auswirkungen auf den Kunden und die n\u00e4chsten Schritte zu verkn\u00fcpfen.<\/p><h4 class=\"wp-block-heading\" id=\"h-1-hybrid-infrastructure-breaks-tool-silos\">1) Hybride Infrastruktur durchbricht Insell\u00f6sungen<\/h4><p>MSPs verwalten heute Kundenumgebungen, die On-Premise-Infrastrukturen, Cloud-Plattformen, SaaS-Anwendungen, Remote-Endpunkte und Netzwerkpfade umfassen. Ein einziger Vorfall kann Signale \u00fcber mehrere dieser Ebenen hinweg erzeugen.<\/p><p>Ohne Korrelation m\u00fcssen Ingenieure zwischen Tools wechseln und m\u00fchsam zusammensetzen, was sich ge\u00e4ndert hat, wovon was abh\u00e4ngt und wo das Problem seinen Ursprung hat.<\/p><h4 class=\"wp-block-heading\" id=\"h-2-fragmented-signals-create-alert-noise\">2) Fragmentierte Signale erzeugen Alarmrauschen<\/h4><p>Kundenumgebungen generieren Warnungen von Ger\u00e4ten, Netzwerkpfaden, Anwendungen, Protokollen, Ereignissen und externen Abh\u00e4ngigkeiten. Wenn diese Warnungen isoliert bleiben, sehen Teams Symptome statt Servicekontext.<\/p><p>Jede Warnung sieht aus wie ein separates Problem, bis jemand das Muster erkennt.<\/p><h4 class=\"wp-block-heading\" id=\"h-3-manual-processes-don-t-scale\">3) Manuelle Prozesse skalieren nicht<\/h4><p>MSPs k\u00f6nnen nicht effizient wachsen, wenn jedes wiederkehrende Problem die gleichen manuellen Schritte erfordert. Die Verwaltung von Hunderten von Kunden erfordert wiederholbare Arbeitsabl\u00e4ufe, richtlinienbasierte Konfigurationen, Alarmweiterleitung und Automatisierung, die geringwertige Arbeit reduziert.<\/p><p>Monitoring sagt Teams, dass etwas passiert ist. Automatisierung und Workflow-Integration helfen ihnen, konsistent darauf zu reagieren.<\/p><h4 class=\"wp-block-heading\" id=\"h-4-customer-expectations-keep-rising\">4) Kunden wachsen Erwartungen<\/h4><p>MSPs werden anhand von Reaktionszeit, L\u00f6sungszeit, SLA-Einhaltung und Kundenerfahrung gemessen. Eine schnellere L\u00f6sung h\u00e4ngt davon ab, wie schnell Teams den Fehlerbereich isolieren und nachweisen k\u00f6nnen, dass der Dienst wiederhergestellt ist.<\/p><p>Mehr Benachrichtigungen erzeugen nur Rauschen, es sei denn, Ingenieure k\u00f6nnen sehen, was sich ge\u00e4ndert hat, was betroffen ist und wo als n\u00e4chstes gehandelt werden muss.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-capabilities-should-msps-expect-from-a-monitoring-and-observability-platform\">Welche F\u00e4higkeiten sollten MSPs von einer Monitoring- und Observability-Plattform erwarten?<\/h2><p>Wenn Sie Monitoring- und Observability-Plattformen vergleichen, betrachten Sie die t\u00e4gliche Arbeit Ihres Teams: Kunden onboarden, Alarmrauschen reduzieren, die Grundursache finden, die Auswirkungen auf den Kunden aufzeigen und Incidents an den richtigen Service-Workflow weiterleiten.<\/p><h4 class=\"wp-block-heading\" id=\"h-1-unified-visibility-across-infrastructure-cloud-network-and-saas\">Einheitliche Transparenz \u00fcber Infrastruktur, Cloud, Netzwerk und SaaS hinweg<\/h4><p>MSPs ben\u00f6tigen eine Abdeckung \u00fcber die Umgebungen, in denen ihre Kunden tats\u00e4chlich arbeiten: On-Premises-Infrastruktur, Cloud-Plattformen, Netzwerkger\u00e4te, SaaS-Anwendungen, APIs, DNS, Protokolle, Ereignisse und digitale Erfahrung.<\/p><p>Die Plattform sollte diese Ebenen zusammen anzeigen, anstatt Ingenieure f\u00fcr jeden Hinweis in separate Tools zu schicken.<\/p><h4 class=\"wp-block-heading\" id=\"h-2-automated-discovery-and-dependency-context\">2) Automatisierte Erkennung und Abh\u00e4ngigkeitskontext<\/h4><p>Manuelle Einrichtung verlangsamt das Onboarding und hinterl\u00e4sst L\u00fccken. Eine starke Plattform kann Ressourcen entdecken, Beziehungen abbilden und zeigen, wie Systeme voneinander abh\u00e4ngen.<\/p><p>Ingenieure k\u00f6nnen mit der Beziehung zwischen Systemen beginnen, anstatt diese Zuordnung bei jedem Vorfall neu zu erstellen.<\/p><h4 class=\"wp-block-heading\" id=\"h-3-multi-tenant-architecture-and-customer-segmentation\">3) Multi-Tenant-Architektur und Kundensegmentierung<\/h4><p>MSPs m\u00fcssen Kundenumgebungen trennen, ohne die zentralisierte Sichtbarkeit zu verlieren. Kundenspezifische Segmentierung, rollenbasierter Zugriff, gruppierte Ressourcen, kundenindividuelle Dashboards und Berichtsansichten sind hierbei wichtig.<\/p><p>Diese Trennung h\u00e4lt den t\u00e4glichen Betrieb sauberer und bietet den Kunden Berichte, die ihre eigene Umgebung widerspiegeln.<\/p><h4 class=\"wp-block-heading\" id=\"h-4-intelligent-alerting-and-noise-reduction\">4) Intelligente Alarmierung und Rauschunterdr\u00fcckung<\/h4><p>Das Alarmvolumen steigt bei mehreren Kunden schnell an. Dynamische Schwellenwerte, Alarmkorrelation, unterdr\u00fcckte abh\u00e4ngige Alarme, Routing-Logik und Eskalationskontrollen helfen Teams, fokussiert zu bleiben.<\/p><p>Das Team erkennt weiterhin, was Aufmerksamkeit erfordert, aber weniger Ingenieure verlieren Zeit mit der Verfolgung doppelter Symptome.<\/p><h4 class=\"wp-block-heading\" id=\"h-5-psa-and-itsm-integration\">5) PSA und ITSM-Integration<\/h4><p>\u00dcberwachungseinblicke m\u00fcssen sich mit Service-Workflows verbinden. Integrationen mit Tools wie ConnectWise, Autotask, ServiceNow oder anderen PSA- und ITSM-Systemen helfen Teams, Tickets zu erstellen, zu aktualisieren, weiterzuleiten und zu schlie\u00dfen, ohne redundante Arbeit zu leisten.<\/p><h4 class=\"wp-block-heading\" id=\"h-6-automation-and-workflow-orchestration\">6) Automatisierung und Workflow-Orchestrierung<\/h4><p>Automatisierung hilft MSPs, die Reaktion \u00fcber Kunden hinweg zu standardisieren. Alarmgesteuerte Workflows, Runbook-Unterst\u00fctzung, Eskalationsketten und gesteuerte Aktionen k\u00f6nnen repetitive manuelle Arbeiten reduzieren.<\/p><p>Gute Automatisierung ersetzt keine Ingenieure. Sie gibt ihnen eine schnellere, konsistentere M\u00f6glichkeit zu handeln.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n  \n  <div class=\"rtc-text-content__wrapper\">\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>M\u00f6chten Sie verstehen, wie Automatisierung MSPs hilft, ihre Abl\u00e4ufe zu skalieren, ohne die Gemeinkosten zu erh\u00f6hen?<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/blog\/7-reasons-why-msps-benefit-from-it-automation\" class=\"btn btn-link\" target=\"_self\">\n        Lesen Sie unseren Blog          <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 class=\"wp-block-heading\" id=\"h-7-ai-guided-rca-prioritization-and-next-best-action\">7) KI-gesteuerte Ursachenanalyse, Priorisierung und n\u00e4chste beste Aktion<\/h4><p>KI sollte mehr tun, als nur Benachrichtigungen zusammenzufassen. Sie sollte Teams dabei helfen, Telemetriedaten zu interpretieren, wahrscheinliche Ursachen zu identifizieren, nach Auswirkungen zu priorisieren, n\u00e4chste Schritte zu empfehlen und die Aktionen innerhalb der vorgegebenen Grenzen zu koordinieren.<\/p><p>MSP-Teams erhalten weniger verwaiste Hinweise, eine klarere Sicht auf die Auswirkungen auf den Kunden und bessere Beweise daf\u00fcr, dass der Service wiederhergestellt wurde.<\/p><h4 class=\"wp-block-heading\" id=\"h-8-digital-experience-and-internet-performance-visibility\">8) Digitale Erlebnis- und Internetperformancetransparenz<\/h4><p>MSPs m\u00fcssen auch wissen, ob das Problem in der Kundenumgebung oder irgendwo im Dienstbereitstellungspfad liegt. Dazu geh\u00f6ren Benutzererfahrung, Web-Performance, APIs, DNS, CDN, ISP-Verhalten und SaaS-Verf\u00fcgbarkeit.<\/p><p>Dies hilft Teams, die Unschuld zu beweisen, wenn das Problem extern ist, und best\u00e4tigt, dass sich das Kundenerlebnis nach der Behebung verbessert hat.<\/p><h4 class=\"wp-block-heading\" id=\"h-9-validation-at-the-user-layer\">9) Validierung auf Benutzerebene<\/h4><p>MSP m\u00fcssen den Kunden zeigen, was passiert ist, was sich ge\u00e4ndert hat und wie sich die Serviceleistung entwickelt. Kundenorientierte Dashboards, geplante Berichte, Dashboard-Schnappsch\u00fcsse, SLA-Ansichten und QBR-f\u00e4hige Nachweise unterst\u00fctzen diese Arbeit.<\/p><p>Je einfacher es ist zu zeigen, was passiert ist und wie das Team reagiert hat, desto einfacher ist es, den Wert des Dienstes zu belegen.<\/p><h2 class=\"wp-block-heading\" id=\"h-best-msp-software-for-monitoring-and-observability\">Beste MSP-Software f\u00fcr \u00dcberwachung und Observability<\/h2><p>Jede Plattform unten l\u00f6st einen anderen Teil des MSP-Monitoring-Problems. Die richtige Wahl h\u00e4ngt von den Umgebungen ab, die Sie unterst\u00fctzen, den Arbeitsabl\u00e4ufen, die Ihr Team ausf\u00fchrt, und davon, wie viele Kontextinformationen die Ingenieure ben\u00f6tigen, bevor sie handeln k\u00f6nnen.<\/p><figure class=\"wp-block-table is-style-stripes\"><table class=\"has-fixed-layout\"><thead><tr><th>Plattform<\/th><th>Am besten f\u00fcr<\/th><th>Schl\u00fcsselst\u00e4rken<\/th><\/tr><\/thead><tbody><tr><td><strong>LogicMonitor<\/strong><\/td><td>MSPs, die hybride Multi-Kunden-Umgebungen verwalten und Infrastruktur, Cloud, Netzwerk, digitales Erlebnis sowie KI-gest\u00fctzte Fehlerbehebung in einer einzigen operativen Ansicht ben\u00f6tigen<\/td><td>Mandantenf\u00e4hige Architektur mit RBAC<br>Sammlerbasierte Hybrid\u00fcberwachung<br>Auto-Erkennung, Topologie und Kontext<br>Alarmkorrelation<br>KI-gest\u00fctzte Ursachenanalyse und Priorisierung von Vorf\u00e4llen durch Edwin AI<br>Digitale Erlebnis- und Internet-Performance-Transparenz \u00fcber APIs, DNS, CDN, ISP-Verhalten und SaaS-Bereitstellungswege mit Catchpoint<br>ITSM\/PSA-Integrationen<br>Kundenspezifische Dashboards und Berichte<br>Automatisierte Fehlerbehebung<\/td><\/tr><tr><td><strong>Datadog<\/strong><\/td><td>Cloud-native und anwendungsintensive Umgebungen<\/td><td>Infrastruktur, Applikation, Protokoll und Netzwerktelemetrie<br>Cloud-First-\u00dcberwachungsmodell<br>Flexible Tagging und Dashboards<br>Breites Integrations\u00f6kosystem<\/td><\/tr><tr><td><strong>Dynatrace<\/strong><\/td><td>Gro\u00df angelegte Hybrid- und Multi-Cloud-Umgebungen mit komplexen Anwendungsabh\u00e4ngigkeiten<\/td><td>Automatische Erkennung<br>Dienstzuordnung<br>Anwendungsbeobachtbarkeit<br>KI-gest\u00fctzte Ursachenanalyse<\/td><\/tr><tr><td><strong>SolarWinds Observability<\/strong><\/td><td>MSPs, die eine konsolidierte \u00dcberwachung \u00fcber Netzwerke, Server und Anwendungen ben\u00f6tigen<\/td><td>Infrastruktur- und Netzwerk\u00fcberwachung<br>Topologievisualisierung<br>Automatische Erkennung<br>Umfassende Ger\u00e4te- und Anbieterabdeckung<\/td><\/tr><tr><td><strong>ManageEngine (OpManager \/ Site24x7)<\/strong><\/td><td>MSPs, die Multi-Site-Netzwerke und infrastrukturlastige Umgebungen verwalten<\/td><td>Netzwerk-, Server-, WAN-, Wireless- und Speicher\u00fcberwachung<br>Fehler\u00fcberwachung<br>Zentralisierte Multi-Site-Transparenz<br>Infrastrukturelle Berichterstattung<\/td><\/tr><tr><td><strong>New Relic<\/strong><\/td><td>Cloud-native Umgebungen mit Fokus auf verteilte Anwendungen<\/td><td>APM<br>Protokoll- und Infrastruktur\u00fcberwachung<br>OpenTelemetry-Unterst\u00fctzung<br>Service-Level-Sichtbarkeit<\/td><\/tr><tr><td><strong>ScienceLogic<\/strong><\/td><td>Umgebungen in Unternehmensgr\u00f6\u00dfe mit AIOps und Service Mapping Anforderungen<\/td><td>Infrastruktur- und Anwendungs\u00fcberwachung<br>Ereigniskorrelation<br>Dienstzuordnung<br>Workflow-Automatisierung<\/td><\/tr><tr><td><strong>IBM Instana<\/strong><\/td><td>Microservices-lastige und Anwendungsleistungs-Umgebungen<\/td><td>Automatische Erkennung<br>Abbildung von Abh\u00e4ngigkeiten<br>Verteiltes Tracing<br>Echtzeit-Anwendungs\u00fcberwachung<\/td><\/tr><\/tbody><\/table><\/figure><p><\/p><div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\"><\/div>\n<\/div><h4 class=\"wp-block-heading\">LogicMonitor<\/h4><p>LogicMonitor gibt MSPs einen zentralen Ort zur \u00dcberwachung hybrider Kundenumgebungen \u00fcber Infrastruktur, Netzwerk, Cloud, digitales Erlebnis und KI-gest\u00fctzte Vorfallreaktion.<\/p><p>LM Envision fasst Infrastruktur, Cloud, Netzwerk, Protokolle und Ereignisse in einer gemeinsamen Beobachtungsschicht zusammen. Catchpoint IPM erweitert die Sichtbarkeit auf die Service-Lieferpfade, auf die Kunden angewiesen sind, einschlie\u00dflich Benutzererfahrung, Internet-Performance, APIs, DNS, CDN, ISP-Verhalten und SaaS-Verf\u00fcgbarkeit. Edwin AI hilft Teams, Signale zu interpretieren, Vorf\u00e4lle zu priorisieren, wahrscheinliche Ursachen zu identifizieren und die Reaktion durch ITSM- und PSA-Integrationen zu koordinieren.<\/p><p>F\u00fcr MSP-Teams bedeutet das weniger getrennte Signale, klarere Kundenauswirkungen, schnellere Fehlersuche und st\u00e4rkere Nachweise daf\u00fcr, dass der Dienst wiederhergestellt wurde.<\/p><p><strong>Schl\u00fcsselst\u00e4rken:<\/strong><\/p><ul class=\"wp-block-list\">\n<li>Multi-Tenant-\u00dcberwachung mit Kundenisolierung und rollenbasierter Zugriffskontrolle<\/li>\n\n\n\n<li>Collectorbasierte \u00dcberwachung f\u00fcr hybride Umgebungen ohne \u00fcberm\u00e4\u00dfigen Agenten-Overhead<\/li>\n\n\n\n<li>Automatische Erkennung \u00fcber Infrastruktur, Cloud-Ressourcen, Netzwerkger\u00e4te und Dienste<\/li>\n\n\n\n<li>Topologie und Kontext zum Verst\u00e4ndnis von Abh\u00e4ngigkeiten in Kundenumgebungen<\/li>\n\n\n\n<li>Alarmkorrelation, dynamische Schwellenwerte und KI-gest\u00fctzte Ursachenanalyse<\/li>\n\n\n\n<li>Digitale Erfahrung und Sichtbarkeit der Internet-Performance durch Catchpoint<\/li>\n\n\n\n<li>Native Integrationen mit ConnectWise, Autotask, ServiceNow und anderen ITSM-Tools<\/li>\n\n\n\n<li>Kundenspezifische Dashboards, Dashboard-Schnappsch\u00fcsse und Berichtsansichten<\/li>\n\n\n\n<li>REST API und Integrationen f\u00fcr Monitoring-, ITSM- und Automatisierungs-Workflows<\/li>\n<\/ul><p><\/p><p>Vorsichtsma\u00dfnahmen<\/p><ul class=\"wp-block-list\">\n<li>LogicMonitor verst\u00e4rkt die \u00dcberwachungs- und Beobachtbarkeitsebene; es ist kein Ersatz f\u00fcr PSA-, Abrechnungs-, Backup- oder Sicherheitstools.<\/li>\n\n\n\n<li>MSPs erhalten den gr\u00f6\u00dften Nutzen, wenn Sammler-Gruppen, Ressourcen-Gruppen, Dashboards, Warnungs-Weiterleitung und Kunden-Segmentierung gezielt eingerichtet sind.<\/li>\n<\/ul><p><br><strong>Webseite <\/strong><a href=\"https:\/\/www.logicmonitor.com\/de\/solutions\/msp\">LogicMonitor MSP-\u00dcberwachung<\/a><\/p><h4 class=\"wp-block-heading\">2) Datadog<\/h4><p>Datadog bringt Infrastruktur-, Anwendungs-, Protokoll- und Netzwerktelemetrie auf eine Cloud-first-Plattform.<\/p><p>MSPs sollten diese St\u00e4rke gegen nutzungsbasierte Kosten, Konfigurationsanforderungen und den zus\u00e4tzlichen Aufwand zur sauberen Verwaltung vieler Kunden abw\u00e4gen.<\/p><p>Wichtige \u00dcberlegungen:<\/p><ul class=\"wp-block-list\">\n<li>N\u00fctzlich f\u00fcr Cloud-native und containerisierte Umgebungen<\/li>\n\n\n\n<li>St\u00e4rker geeignet f\u00fcr Anwendungs- und Servicetelemetrie als herk\u00f6mmliche MSP-Operationen<\/li>\n\n\n\n<li>Die Kosten k\u00f6nnen mit wachsendem Telemetrievolumen steigen<\/li>\n\n\n\n<li>Multi-Kunden-Workflows erfordern m\u00f6glicherweise zus\u00e4tzliche Konfiguration<\/li>\n<\/ul><p><br><strong>Website<\/strong>: <a href=\"https:\/\/www.datadoghq.com\/monitoring\/cloud-observability\/\">Datadog Observability<\/a><\/p><h4 class=\"wp-block-heading\">3) Dynatrace<\/h4><p>Dynatrace ist f\u00fcr die automatisierte Erkennung, Service-Mapping und anwendungsbewusste Beobachtbarkeit \u00fcber verteilte Systeme hinweg konzipiert.<\/p><p>Der Kompromiss liegt darin, Tiefe gegen operative Eignung abzuw\u00e4gen: Kosten, Implementierungsaufwand und t\u00e4gliche Administration k\u00f6nnen f\u00fcr Multi-Kunden-MSP-Teams eine Belastung darstellen.<\/p><p>Wichtige \u00dcberlegungen:<\/p><ul class=\"wp-block-list\">\n<li>N\u00fctzlich f\u00fcr komplexe Anwendungen und hybride Umgebungen<\/li>\n\n\n\n<li>Automatisierte Erkennung und Abh\u00e4ngigkeitsmapping k\u00f6nnen die Ursachenanalyse unterst\u00fctzen<\/li>\n\n\n\n<li>Implementierung und Verwaltung k\u00f6nnen aufwendig sein<\/li>\n\n\n\n<li>Lizenzierung und Gesamtkosten k\u00f6nnen bei vielen Kunden schwierig zu verwalten sein<\/li>\n<\/ul><p><br><strong>Website<\/strong>: <a href=\"https:\/\/www.dynatrace.com\/\">Dynatrace Observability<\/a><\/p><h4 class=\"wp-block-heading\">4) SolarWinds Observability<\/h4><p>SolarWinds Observability kann f\u00fcr Teams geeignet sein, die das SolarWinds-\u00d6kosystem bereits kennen oder eine Infrastruktur- und Netzwerk\u00fcberwachung in vertrauten IT-Umgebungen ben\u00f6tigen.<\/p><p>MSPs, die SolarWinds bereits kennen, werden es vielleicht wiedererkennen, sollten aber dennoch Ausrei\u00dferger\u00e4usche, Hybridabdeckung und Verwaltungsaufwand auf die Probe stellen.<\/p><p>Wichtige \u00dcberlegungen:<\/p><ul class=\"wp-block-list\">\n<li>Vertraute Option f\u00fcr Infrastruktur- und Netzwerk\u00fcberwachung<\/li>\n\n\n\n<li>Topologievisualisierung und -erkennung kann bei der Umgebungszuordnung helfen<\/li>\n\n\n\n<li>Alarmger\u00e4usche k\u00f6nnen eine sorgf\u00e4ltige Abstimmung erfordern<\/li>\n\n\n\n<li>Fortgeschrittene Anwendungsf\u00e4lle k\u00f6nnen jedoch den Einrichtungs- und Verwaltungsaufwand erh\u00f6hen<\/li>\n<\/ul><p><br><strong>Website<\/strong>: <a href=\"https:\/\/www.solarwinds.com\/solutions\/solarwinds-observability\">SolarWinds Observability<\/a><\/p><h4 class=\"wp-block-heading\">5) ManageEngine (OpManager \/ Site24x7)<\/h4><p>Die ManageEngine-Tools umfassen die \u00dcberwachung von Netzwerken, Servern, WANs, drahtlosen Verbindungen, Speichern und Fehlern \u00fcber verteilte Standorte hinweg.<\/p><p>Es kann eine praktische L\u00f6sung f\u00fcr Umgebungen mit hohem Infrastrukturbedarf sein, obwohl breitere Beobachtbarkeits- und Service-Workflow-Anforderungen m\u00f6glicherweise weitere Integrationsarbeit erfordern.<\/p><p>Wichtige \u00dcberlegungen:<\/p><ul class=\"wp-block-list\">\n<li>N\u00fctzlich f\u00fcr Netzwerk- und Infrastruktur\u00fcberwachung<\/li>\n\n\n\n<li>Kann Sichtbarkeit und Fehlerverwaltung f\u00fcr mehrere Standorte unterst\u00fctzen<\/li>\n\n\n\n<li>Erweiterte Funktionen erfordern m\u00f6glicherweise zus\u00e4tzliche Module<\/li>\n\n\n\n<li>Drittanbieterintegrationen und Skalierbarkeit erfordern m\u00f6glicherweise zus\u00e4tzliche Planung<\/li>\n<\/ul><p><br><strong>Website<\/strong>: <a href=\"https:\/\/www.manageengine.com\/network-monitoring\/\">ManageEngine OpManager \/ Site24x7<\/a><\/p><h4 class=\"wp-block-heading\">6) New Relic<\/h4><p>New Relic vereint Application Performance Monitoring, Protokolle, Infrastruktur-Telemetrie und OpenTelemetry-Unterst\u00fctzung auf einer Plattform.<\/p><p>Sein anwendungsfirstiger Ansatz kann gut f\u00fcr Cloud-native Kunden funktionieren, aber MSPs sollten die Eignung f\u00fcr Netzabdeckung, infrastrukturintensive Kunden, Kundensegmentierung und Berichterstattung pr\u00fcfen.<\/p><p>Wichtige \u00dcberlegungen:<\/p><ul class=\"wp-block-list\">\n<li>N\u00fctzlich f\u00fcr Sichtbarkeit auf Anwendungs- und Serviceebene<\/li>\n\n\n\n<li>OpenTelemetry-Unterst\u00fctzung kann bei der flexiblen Datenerfassung helfen<\/li>\n\n\n\n<li>Weniger fokussiert auf traditionelle, infrastrukturintensive MSP-Umgebungen<\/li>\n\n\n\n<li>Kosten und Datenvolumen m\u00fcssen eng beobachtet werden<\/li>\n<\/ul><p><br><strong>Website<\/strong>: <a href=\"https:\/\/newrelic.com\/\">New Relic Observability<\/a><\/p><h4 class=\"wp-block-heading\">7) ScienceLogic<\/h4><p>ScienceLogic unterst\u00fctzt komplexe hybride Umgebungen mit Infrastruktur- und Anwendungs\u00fcberwachung, Ereigniskorrelation und Service-Mapping.<\/p><p>Es kann komplexe Umgebungen unterst\u00fctzen, aber Einrichtung, Anpassung und Feinabstimmung m\u00fcssen der Kapazit\u00e4t des Teams entsprechen.<\/p><p>Wichtige \u00dcberlegungen:<\/p><ul class=\"wp-block-list\">\n<li>N\u00fctzlich f\u00fcr AIOps-\u00e4hnliches Monitoring und Ereigniskorrelation<\/li>\n\n\n\n<li>Service-Mapping kann komplexe Umgebungen unterst\u00fctzen<\/li>\n\n\n\n<li>Einrichtung und Anpassung k\u00f6nnen ressourcenintensiv sein<\/li>\n\n\n\n<li>Die Anpassung von Alarmen ist wichtig, um St\u00f6rungen zu vermeiden.<\/li>\n<\/ul><p><br><strong>Website<\/strong>: <a href=\"https:\/\/sciencelogic.com\/solutions\/observability\">ScienceLogic Observability Platform<\/a><\/p><h4 class=\"wp-block-heading\">8) IBM Instana<\/h4><p>IBM Instana konzentriert sich auf Echtzeit-\u00dcberwachung f\u00fcr Anwendungen, Infrastruktur und microservice-basierte Umgebungen.<\/p><p>Die Echtzeitanwendung ist n\u00fctzlich f\u00fcr Umgebungen mit vielen Microservices, w\u00e4hrend f\u00fcr umfassendere MSP-Anforderungen zus\u00e4tzliche Planung in Bezug auf Infrastruktur, Netzwerk, Berichterstattung und Service-Workflows erforderlich sein kann.<\/p><p>Wichtige \u00dcberlegungen:<\/p><ul class=\"wp-block-list\">\n<li>N\u00fctzlich f\u00fcr Microservices und Anwendungsleistungs\u00fcberwachung<\/li>\n\n\n\n<li>Automatische Erkennung und Abh\u00e4ngigkeitszuordnung k\u00f6nnen in dynamischen Umgebungen helfen<\/li>\n\n\n\n<li>Weniger auf Infrastruktur-intensive MSP-Betriebe fokussiert<\/li>\n\n\n\n<li>Gro\u00df angelegte Eins\u00e4tze k\u00f6nnen Planung und Feinabstimmung erfordern<\/li>\n<\/ul><p><br><strong>Website<\/strong>: <a href=\"https:\/\/www.ibm.com\/products\/instana\">IBM Instana Observability<\/a><\/p><h2 class=\"wp-block-heading\" id=\"h-how-logicmonitor-helps-msps-move-from-detection-to-resolution\">Wie LogicMonitor MSPs hilft, von der Erkennung zur L\u00f6sung zu gelangen<\/h2><p>W\u00e4hrend eines Vorfalls m\u00fcssen MSP-Teams wissen, wo das Problem begonnen hat, welche Kundendienste betroffen sind und welche Ma\u00dfnahmen als N\u00e4chstes ergriffen werden sollten. LogicMonitor verbindet diese Details \u00fcber Monitoring, digitales Erlebnis, KI-gest\u00fctzte Fehlerbehebung und Service-Workflows.<\/p><p>Hier ist, wie die Teile zusammenarbeiten:<\/p><p>LM Envision sammelt Telemetriedaten in der Kundenumgebung, einschlie\u00dflich Infrastruktur, Cloud, Netzwerk, Protokolle, Ereignisse und Serviceabh\u00e4ngigkeiten.<\/p><p>2. Topologie, Kontext und Alarmkorrelation helfen dem Team zu sehen, was sich ge\u00e4ndert hat und welche Systeme miteinander verbunden sind.<\/p><p>3. Catchpoint erweitert die Einsicht in das digitale Erlebnis und die Internet-Performance, einschlie\u00dflich APIs, DNS, CDN, Verhalten von ISPs, SaaS-Lieferpfaden und Benutzererlebnis.<\/p><p>4. Edwin AI hilft bei der Priorisierung des Vorfalls, der Identifizierung der wahrscheinlichsten Ursachen, der Zusammenfassung des Geschehens und der Empfehlung von n\u00e4chsten Schritten.<\/p><p>5. PSA- oder ITSM-Integrationen helfen dabei, die Arbeit in den richtigen Workflow zu leiten.<\/p><p>6. Die Erfahrung validates die Best\u00e4tigung, ob der kundenorientierte Dienst wiederhergestellt wurde.<\/p><p>Die Antwort wird schneller, wenn Ingenieure den Fehlerbereich sehen, die Arbeit weiterleiten und best\u00e4tigen k\u00f6nnen, dass der kundenbezogene Dienst wieder einwandfrei funktioniert.<\/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        Sehen Sie schneller, was jeden Kunden beeinflusst      <\/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 gibt MSP-Teams eine einheitliche Ansicht \u00fcber Infrastruktur, Cloud, Netzwerk, digitales Erlebnis und St\u00f6rungskontext, damit sie schneller Fehler beheben und den Kunden zeigen k\u00f6nnen, wann der Dienst wieder ordnungsgem\u00e4\u00df funktioniert.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/de\/signup\" class=\"btn btn-link\" target=\"_self\">\n        Kostenlos testen          <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><h3 class=\"wp-block-heading\" id=\"h-faqs\">FAQs<\/h3><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-msp-software-and-rmm-software\">\n            Was ist der Unterschied zwischen MSP-Software und RMM-Software?            <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>RMM-Software ist eine Kategorie im MSP-Software-Stack. Sie hilft Teams, Endpunkte, Server und Ger\u00e4te zu \u00fcberwachen und zu verwalten, oft \u00fcber Agenten. MSP-Software kann auch PSA, \u00dcberwachungs- und Beobachtungstools, Sicherheitstools, Backup-Tools, Abrechnungstools und Berichtstools umfassen.<\/p>\n<p>Hier konzentrieren wir uns auf Monitoring und Observability: die Ebene, die MSPs nutzen, um den Zustand von Infrastruktur, Cloud, Netzwerk, SaaS und digitaler Erfahrung ihrer Kunden zu verstehen.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-why-do-msps-need-observability-if-they-already-use-rmm-and-psa-tools\">\n            Warum brauchen MSPs Observability, wenn sie bereits RMM- und PSA-Tools verwenden?            <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>RMM- und PSA-Tools beantworten unterschiedliche Fragen. RMM zeigt den Zustand von Ger\u00e4ten und Endpunkten an. PSA verfolgt Servicearbeiten, Tickets, SLAs und Kunden-Workflows.<\/p>\n<p>Observability verbindet Signale in der gesamten Umgebung, damit Teams sehen k\u00f6nnen, was sich ge\u00e4ndert hat, was betroffen ist und wo sie mit der Fehlersuche beginnen k\u00f6nnen.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-what-should-msps-look-for-in-monitoring-and-observability-software\">\n            Worauf sollten MSPs bei Monitoring- und Observability-Software achten?            <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>Priorisieren Sie hybride Abdeckung, Kundensegmentierung, automatische Erkennung, Topologie- und Abh\u00e4ngigkeitskontext, intelligente Benachrichtigungen, PSA- oder ITSM-Integrationen, Berichterstattung und Sichtbarkeit der digitalen Erfahrung.<\/p>\n<p>Die richtige Plattform hilft Ihrem Team, Kunden schnell online zu bringen, das eigentliche Problem zu finden und zu zeigen, dass der Service wieder stabil l\u00e4uft.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-does-ai-help-msp-teams-operate-more-efficiently\">\n            Wie hilft KI den MSP-Teams, effizienter zu arbeiten?            <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>KI ist n\u00fctzlich, wenn sie Ingenieuren einen besseren Ausgangspunkt bietet. Sie kann Alarme korrelieren, Vorf\u00e4lle nach Auswirkungen priorisieren, wahrscheinliche Ursachen aufzeigen, den Kontext von Vorf\u00e4llen zusammenfassen und n\u00e4chste Schritte empfehlen.<\/p>\n<p>Das Ziel ist eine weniger repetitive Triage und eine konsistentere Reaktion gegen\u00fcber den Kunden.<\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-does-logicmonitor-support-msp-monitoring-and-observability\">\n            Wie unterst\u00fctzt LogicMonitor MSP-\u00dcberwachung und -Observability?            <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 hilft MSPs, hybride Kundenumgebungen \u00fcber Infrastruktur, Cloud, Netzwerk, Protokolle, Ereignisse und Dienste hinweg zu \u00fcberwachen. Catchpoint bietet Einblicke in das digitale Erlebnis und die Internet-Performance \u00fcber APIs, DNS, CDN, ISP-Verhalten, SaaS-Lieferpfade und Benutzererfahrungen. Edwin AI hilft Teams, Signale zu interpretieren, Vorf\u00e4lle zu priorisieren, die wahrscheinliche Ursache zu identifizieren und durch Service-Workflows Ma\u00dfnahmen zu koordinieren.<\/p>\n<p>Diese F\u00e4higkeiten helfen MSPs, schneller von der Erkennung zur Diagnose und zur Validierung zu gelangen.<\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div>","protected":false},"excerpt":{"rendered":"<p>Entdecken Sie die Observability-Funktionen, die MSPs ben\u00f6tigen, um Rauschen zu reduzieren und Vorf\u00e4lle schneller zu beheben.<\/p>","protected":false},"author":16,"featured_media":613201,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[5035,5066],"tags":[5331,7850,5683,7777,7760,7752,7776,6872,6939,7050],"industry":[7518],"language":[7],"role":[7527],"lm_search_queries":[],"lm_strategic_tags":[],"topic":[6781],"class_list":["post-613150","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-managed-service-provider","language-english","role-service-support","topic-observability"],"acf":{"is_global_bar_disabled":false,"is_global_bar_overriden":false,"is_search_excluded":false,"page_language":"english","translated_pages":"","reviewers":false,"is_global_form_disabled":false,"is_global_form_override":false,"component_layouts":false,"related_resources":false,"updated_date":"","author_section_checkbox":false,"reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.9 (Yoast SEO v27.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Best MSP Software in 2026: How to Choose the Right Platform | LogicMonitor<\/title>\n<meta name=\"description\" content=\"MSPs need more than RMM and PSA tools to troubleshoot customer environments. 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in ganz APAC aufbauen: Ein Gespr\u00e4ch mit Dave Patnaik"},"content":{"rendered":"<?xml encoding=\"UTF-8\"><p>Derzeit geschieht in der gesamten Asien-Pazifik-Region viel. Unternehmen modernisieren schnell ihre Betriebe, f\u00fchren KI ein und bew\u00e4ltigen die wachsende Komplexit\u00e4t in zunehmend verteilten Umgebungen. Die Chance f\u00fcr LogicMonitor in der Region w\u00e4chst stetig mit.<\/p><p>Deshalb freue ich mich besonders, Dave Patnaik als unseren neuen Vizepr\u00e4sidenten f\u00fcr APAC bei LogicMonitor begr\u00fc\u00dfen zu d\u00fcrfen.<\/p><p>Ich hatte in den letzten Wochen Gelegenheit, Zeit mit Dave zu verbringen, und was mir sofort auffiel, waren sein tiefgreifendes Verst\u00e4ndnis der Region, seine kundenorientierte Denkweise und seine Erfahrung beim Aufbau leistungsstarker Unternehmens- und Partnerorganisationen im gesamten asiatisch-pazifischen Raum. Durch seine Leitung des $1B-APJ-\u00d6kosystemgesch\u00e4fts bei Red Hat sowie durch F\u00fchrungspositionen bei Forescout, SolarWinds, Wolters Kluwer und Trend Micro bringt Dave umfassende operative sowie regionale und internationale Erfahrung mit, die f\u00fcr unser weiteres Wachstum im asiatisch-pazifischen Raum von unsch\u00e4tzbarem Wert sein wird.<\/p><p>Wir haben uns k\u00fcrzlich zusammengesetzt, um dar\u00fcber zu sprechen, was sich in der gesamten Enterprise-Technologielandschaft ver\u00e4ndert, warum APAC ein so wichtiger Wachstumsmarkt bleibt, wie sich die Kundenerwartungen entwickeln und was ihn am meisten begeistert daran, LogicMonitor in dieser Phase der Unternehmensentwicklung zu unterst\u00fctzen.<\/p><p><strong>John: <\/strong><strong>Sie haben Ihre Karriere damit verbracht, Unternehmens- und Partnerorganisationen in ganz APAC aufzubauen und zu skalieren. Was hat LogicMonitor und dieser Moment im Markt f\u00fcr Sie zu einer passenden Gelegenheit gemacht?<\/strong><\/p><p>Dave: W\u00e4hrend meiner gesamten Karriere beim Aufbau riesiger Unternehmens- und Partner-\u00d6kosysteme in den M\u00e4rkten APJ &amp; International habe ich beobachtet, wie Unternehmen Millionen in \u00dcberwachungstools investieren, nur um am Ende mit mehr Datensilos, fragmentierten Ansichten und, schlimmer noch, extremer Alarmm\u00fcdigkeit dazustehen. Das menschlich skalierte Betriebsmodell, auf dem die IT aufgebaut wurde, kann einfach nicht mit der modernen digitalen Komplexit\u00e4t Schritt halten.<\/p><p>Was mich zu LogicMonitor gef\u00fchrt hat, ist die Tatsache, dass wir nicht einfach nur ein weiteres Dashboard entwickeln. Wir vollziehen einen grundlegenden Paradigmenwechsel von reaktiver Transparenz hin zu echter autonomer IT. Dass wir weltweit die Marke von 1,44 Mrd. US-Dollar bei den j\u00e4hrlichen wiederkehrenden Ums\u00e4tzen (ARR) \u00fcberschritten haben \u2013 wobei unsere KI-Betriebsebene Edwin AI bereits ein Drittel der Gesamtbuchungen ausmacht \u2013 beweist, dass Unternehmen genau diesen Wandel herbeisehnen. Jetzt einzusteigen und dieses Weltklasse-Team zu leiten, w\u00e4hrend wir die Arbeitsweise von Unternehmen grundlegend neu definieren, ist eine Herausforderung und eine Chance, die ich mir nicht entgehen lassen konnte.<\/p><p><strong>John: <\/strong><strong>APAC ist eine unglaublich vielf\u00e4ltige und sich schnell entwickelnde Region. Wo sehen Sie derzeit die gr\u00f6\u00dften Chancen und Herausforderungen f\u00fcr Gro\u00dfunternehmen?<\/strong><\/p><p>Dave: Die gr\u00f6\u00dfte operationelle Herausforderung, vor der APJ-F\u00fchrungskr\u00e4fte heute stehen, ist das \u2018Blind-Spot-Problem\u2019. Die heutige IT-Landschaft umfasst Legacy-Rechenzentren, Public-Cloud-Hyper-Scaler, Dutzende von SaaS-Anwendungen und komplexe globale Internet-Routing-Pfade. Wenn eine Anwendung f\u00fcr einen Benutzer in Tokio oder Sydney schlechter funktioniert, verschwenden IT-Teams Stunden damit, sich gegenseitig die Schuld zuzuschieben, weil sie nicht sagen k\u00f6nnen, ob das Problem in ihrem Code, einer AWS-Region, einem lokalen ISP-Peering-Punkt oder einem globalen CDN liegt.<\/p><p>Genau hier liegt unsere massive Marktchance. Indem wir Catchpoints Internetleistungsintelligenz direkt in LogicMonitor integrieren und diese Telemetrie in Edwin AI einspeisen, eliminieren wir diese externen Perimeters und blinden Flecken vollst\u00e4ndig. Wir geben den F\u00fchrungskr\u00e4ften von Unternehmen in APJ eine einzige, koh\u00e4rente Wahrheitsquelle, die die Backend-Infrastruktur direkt mit den digitalen Erlebnissen realer Endnutzer verbindet.<\/p><p><strong>John: <\/strong><strong>Sie haben im Laufe Ihrer Karriere gro\u00dfe \u00d6kosystem- und Partnerorganisationen geleitet. Wie sehen Sie die sich entwickelnde Rolle von Partnern in ganz APAC?<\/strong><\/p><p>Dave: In APJ sind Partner nicht nur ein Vertriebskanal, sondern die absolute Lebensader f\u00fcr Skalierbarkeit. Aber die traditionelle Partnerbeziehung, die auf dem transaktionalen Weiterverkauf von Software basiert, ist tot. Heutzutage stehen Global System Integrators (GSIs), Managed Service Provider (MSPs) und regionale Cloud-Partner unter enormem Druck, tats\u00e4chliche Gesch\u00e4ftsergebnisse zu erzielen, Kunden-SLAs zu sch\u00fctzen und den operativen Aufwand zu reduzieren.<\/p><p>Meine Mission ist es, ein skalierbares, \u00e4u\u00dferst lukratives Partner-\u00d6kosystem in der gesamten Region aufzubauen. Wir bef\u00e4higen unsere Partner, unser agentenbasiertes AIOps direkt in ihre Managed Services Bereitstellung zu integrieren. Indem wir ihnen die LogicMonitor-Plattform zur Verf\u00fcgung stellen, geben wir ihnen eine KI-zentrierte Engine an die Hand, um St\u00f6rungsrauschen zu reduzieren, die Ursachenermittlung zu beschleunigen und \u2018Self-Healing\u2019-IT-Funktionen direkt an ihre Endkunden weiterzugeben.&nbsp;<\/p><p><strong>John: <\/strong><strong>Viele Organisationen versuchen gleichzeitig, Innovation, KI-Einf\u00fchrung und operative Widerstandsf\u00e4higkeit in Einklang zu bringen. Was sagen Ihnen Ihre Kunden, was sie derzeit am dringendsten ben\u00f6tigen?<\/strong><\/p><p>Kunden suchen nach Einfachheit und Vertrauen. Sie wollen keine weiteren Dashboards oder ein weiteres Tool zur Verwaltung.&nbsp;<\/p><p>Was sie jetzt brauchen, ist pr\u00e4diktive Resilienz und vertrauensw\u00fcrdige Automatisierung. Sie wollen eine Plattform, die komplexe Infrastrukturabh\u00e4ngigkeiten in ihrem gesamten Bestand abbilden kann, Alarme basierend auf tats\u00e4chlichen gesch\u00e4ftlichen Auswirkungen priorisieren und automatisierte, gesteuerte Behebungs-Workflows ausf\u00fchren kann, bevor ein menschlicher Bediener \u00fcberhaupt eingreifen muss. Sie brauchen Technologie, die die operative Schwerstarbeit leise erledigt, damit ihre Engineering-Talente sich tats\u00e4chlich auf Innovationen zur Umsatzsteigerung konzentrieren k\u00f6nnen.<\/p><p><strong>John: <\/strong><strong>LogicMonitor hat k\u00fcrzlich sein Autonomous IT Innovation Program angek\u00fcndigt. Wie sehen Sie, wie KI die Unternehmensprozesse in den n\u00e4chsten Jahren ver\u00e4ndern wird?<\/strong><\/p><p>Dave: Der Start unseres Autonomous IT Innovation Program markiert eine bewusste Hinwendung zu einer KI-zentrierten operativen Zukunft. In den n\u00e4chsten Jahren wird KI zur prim\u00e4ren Schicht werden, durch die Unternehmens-Teams arbeiten. Aber lassen Sie mich eines ganz klarstellen: Es geht nicht darum, menschliche Bediener zu ersetzen oder spezialisiertes Fachwissen abzubauen. Es geht darum, die endlose \u2018Plackerei\u2019 zu beseitigen, die Teams ausbrennt.<\/p><p>Wir bauen die n\u00e4chste Generation benutzergesteuerter Workflows. Edwin AI dient als Frontend und \u00fcbernimmt schnell die manuelle Zusammenstellung, Korrelation und gef\u00fchrte Ursachenanalyse \u00fcber Milliarden von Datenpunkten in Echtzeit. Es pr\u00e4sentiert den genauen Kontext, den Auswirkungsbereich und die Abhilfem\u00f6glichkeiten, h\u00e4lt den menschlichen Systembetreiber jedoch mit robuster Governance fest in der Kontrollebene. Es wertet die Rolle des IT-Professionals von einem ersch\u00f6pften Feuerwehrmann zu einem hochrangigen strategischen Orchestrator auf.<\/p><p><strong>John: <\/strong><strong>Was begeistert Sie am meisten an der vor uns liegenden Chance f\u00fcr LogicMonitor in APAC?<\/strong><\/p><p>Dave: Was mich am meisten begeistert, ist die rohe Geschwindigkeit, die Vielfalt und der Appetit auf digitale Transformation im APJ-Markt. Von der schnellen Skalierung der Infrastruktur in ASEAN bis hin zu den hoch entwickelten Anforderungen von Unternehmen in Australien, Neuseeland und Japan gibt es eine massive Kluft zwischen den herk\u00f6mmlichen \u00dcberwachungsm\u00f6glichkeiten und dem, was die moderne digitale Wirtschaft erfordert. LogicMonitor hat die richtige Plattform, die richtige KI-Engine mit Edwin und das absolut perfekte Markt-Timing, um diesen Bereich vollst\u00e4ndig zu beherrschen. Die M\u00f6glichkeit, diesen Fu\u00dfabdruck von Grund auf mit einem so ehrgeizigen globalen Team aufzubauen, ist unglaublich belebend.<\/p><p><strong>John: <\/strong><strong>Was sind Ihre gr\u00f6\u00dften Priorit\u00e4ten f\u00fcr die ersten 6\u201312 Monate?<\/strong><\/p><p>Dave: Ich habe drei Priorit\u00e4ten f\u00fcr mein erstes APJ-Jahr:<\/p><ol class=\"wp-block-list\">\n<li><strong>Modernisieren und skalieren Sie unser GTM-Team:<\/strong> Wir modernisieren aggressiv unsere regionale Marktbearbeitung. Wir richten unsere Teams auf eine KI-gesteuerte Plattform-Erz\u00e4hlung aus und stellen sicher, dass jede einzelne Interaktion darauf abzielt, messbare Gesch\u00e4ftsergebnisse, eine schnelle Wertsch\u00f6pfung und einen massiven operativen ROI f\u00fcr unsere Kunden zu erzielen.<\/li>\n\n\n\n<li><strong>Regionale Expansion beschleunigen<\/strong> Wir expandieren tief in gezielte Wachstumsregionen von Gro\u00dfunternehmen und stellen die notwendige lokale Pr\u00e4senz, \u00d6kosystempartner, Unterst\u00fctzung und Fachkenntnisse sicher, um gro\u00dfe Unternehmenskundenmigrationen im gesamten APJ-Raum zu unterst\u00fctzen.<\/li>\n\n\n\n<li><strong>Vertiefen Sie die Partner-Steuerebene:<\/strong> Wir richten unseren Erfolg vollst\u00e4ndig an unserem \u00d6kosystem aus. Ich m\u00f6chte, dass LogicMonitor der unangefochtene Anbieter der Wahl f\u00fcr jeden wichtigen GSI, LSI, VAR und regionalen Dienstleister ist, der seinen Kunden moderne, sich selbst heilende digitale Operationen anbieten m\u00f6chte.<\/li>\n<\/ol><p><\/p><style>\n.toc-container {\ndisplay: none !important;\n}\n\n.blog-detail .blog-sidebar .blog-sidebar-content {\ngap: 0 !important;\n}\n<\/style><script>\nconst observer = new MutationObserver(() => {\n  const toc = document.querySelector('.toc-container');\n  const sidebar = document.querySelector('.blog-detail .blog-sidebar .blog-sidebar-content');\n\n  if (toc) toc.style.display = 'none';\n  if (sidebar) sidebar.style.gap = '0px';\n\n  if (toc && sidebar) {\n    observer.disconnect();\n  }\n});\n\nobserver.observe(document.body, {\n  childList: true,\n  subtree: true\n});\n<\/script>","protected":false},"excerpt":{"rendered":"<p>LogicMonitor begr\u00fc\u00dft Dave Patnaik als VP of APAC, der tiefgreifende Erfahrung in der Unternehmens- und Partnerf\u00fchrung mitbringt, um das regionale Wachstum und den KI-gesteuerten Betrieb zu beschleunigen.<\/p>","protected":false},"author":14,"featured_media":612976,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[1],"tags":[],"industry":[6790],"language":[7],"role":[],"lm_search_queries":[],"lm_strategic_tags":[],"topic":[],"class_list":["post-612974","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-all","language-english"],"acf":{"is_global_bar_disabled":false,"is_global_bar_overriden":false,"page_language":"english","translated_pages":"","reviewers":false,"is_search_excluded":false,"is_global_form_disabled":false,"is_global_form_override":false,"component_layouts":false,"related_resources":false,"updated_date":"","author_section_checkbox":true,"reviewer_name":"","author_image":"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/02\/John.png","author_linkedin":"https:\/\/www.linkedin.com\/in\/johngrosshans\/","author_name":"John Grosshans","author_job_title":"President of Field Operations, LogicMonitor","author_dept":"","author_bio":"John Grosshans oversees LogicMonitor\u2019s global go-to-market organization, including marketing, customer success, sales, and channel functions. With more than 20 years of leadership in enterprise software and cloud, he brings deep experience building scalable teams and driving growth at scale.\r\nPrior to joining LogicMonitor, John served as Chief Operations Officer at Coveo, where he led a 600-person global sales organisation and drove international bookings. He also held senior leadership roles at Palo Alto Networks, Amazon Web Services, Oracle and SAP, delivering customer-first innovation and operational rigor in fast-growing environments. At LogicMonitor, John is focused on expanding the company\u2019s global reach, accelerating growth, and helping enterprises harness the full power of AI to transform their digital operations.\r\nJohn holds a Bachelor of Science in Industrial Distribution from Clarkson University and is based in Laguna Beach, CA."},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.9 (Yoast SEO v27.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Building Enterprise Momentum Across APAC: A Conversation with Dave Patnaik | LogicMonitor<\/title>\n<meta name=\"description\" content=\"LogicMonitor welcomes Dave Patnaik as VP of APAC, bringing deep enterprise and partner leadership experience to accelerate regional growth and AI-driven operations.\" \/>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" 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Digitale Erfahrung aus Anwendersicht verstehen"},"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        Der schnelle \u00dcberblick      <\/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><span style=\"font-weight: 400\">Internet Performance Monitoring (IPM) bietet End-to-End-Einblicke in das, was zwischen Ihrer Infrastruktur und Ihren Benutzern geschieht, \u00fcber Netzwerke und Dienste hinweg, die Sie weder besitzen noch kontrollieren.<\/span><\/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><span style=\"font-weight: 400\">Die meisten \u00dcberwachungstools sagen Ihnen, ob Ihre Systeme verf\u00fcgbar sind. IPM hilft Ihnen zu \u00fcberpr\u00fcfen, ob sie Ihre Nutzer tats\u00e4chlich erreichen, in deren Netzwerk, an deren Standort, genau jetzt.<\/span><\/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><span style=\"font-weight: 400\">Catchpoints globales Agentennetzwerk, Teil der LogicMonitor-Plattform, ist unabh\u00e4ngig von Ihrem Cloud-Hosting. Das bedeutet, dass Ihre Sichtbarkeit nicht verloren geht, wenn Ihr Anbieter ausf\u00e4llt.<\/span><\/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><span style=\"font-weight: 400\">Der Unterschied zwischen Verf\u00fcgbarkeit und Erreichbarkeit klingt subtil, bis ein Ausfall Nutzer in einer Region trifft und Ihre Dashboards alles als Gr\u00fcn anzeigen.<\/span><\/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><span style=\"font-weight: 400\">Wenn Ihre \u00dcberwachung bei Ihrer eigenen Infrastruktur stoppt, sehen Sie nur die halbe Wahrheit. IPM \u00fcberwacht die andere H\u00e4lfte.<\/span><\/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><span style=\"font-weight: 400\">Wenn Ihre \u00dcberwachung bei Ihrer eigenen Infrastruktur stoppt, sehen Sie nur die halbe Wahrheit. IPM \u00fcberwacht die andere H\u00e4lfte.<\/span><\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p>Das Internet ist jetzt Ihr Netzwerk. Ihre Apps leben in der Cloud, Ihre Benutzer sind \u00fcberall, und die Systeme, die Ihre Anwendungen und Dienste an sie liefern, nutzen Hunderte von Anbietern, ISPs und Netzwerken au\u00dferhalb Ihrer Kontrolle.<\/p><p>In der Praxis bedeutet das, dass Infrastruktur\u00fcberwachung die Grundlage ist. Sie ben\u00f6tigen auch Transparenz f\u00fcr alles au\u00dferhalb Ihres Perimeter. <a href=\"https:\/\/www.logicmonitor.com\/de\/internet-performance-monitoring\">Internet Performance Monitoring<\/a> (IPM) erweitert diese Sichtbarkeit \u00fcber den gesamten Lieferweg von Ihren Systemen bis zu Ihren Benutzern, durch jede dazwischenliegende Schicht.<\/p><p>Sehen Sie sich eine Demonstration an, wie Catchpoints IPM von realen Benutzerstandpunkten aus \u00fcberwacht und die zusammengefasste Erfahrung, Core Web Vitals und KI-identifizierte Ereignisse in einer einzigen Ansicht anzeigt, oder lesen Sie weiter, um mehr zu erfahren.<\/p><section id=\"\" class=\"section bg-white theme-light    section-bg-dark\">\n        <div class=\"section-content container\">\n    <div class=\"full-width-media-wrapper\">\n<div class=\"media-assets-block\">\n    <div class=\"media-container object-center-center aspect-auto type-wistia_embed\" style=\"max-width: 100svh; \">\n\n          <div class=\"wistia_embed\">\n        <div class=\"\">\n          <p><script src=\"https:\/\/fast.wistia.com\/embed\/medias\/3mk0scotaf.jsonp\" async><\/script><br>\n<script src=\"https:\/\/fast.wistia.com\/assets\/external\/E-v1.js\" async><\/script><\/p>\n<div class=\"wistia_responsive_padding\" style=\"padding: 56.25% 0 0 0; position: relative;\">\n<div class=\"wistia_responsive_wrapper\" style=\"height: 100%; left: 0; position: absolute; top: 0; width: 100%;\">\n<div class=\"wistia_embed wistia_async_3mk0scotaf videoFoam=true\" style=\"height: 100%; position: relative; width: 100%;\">\n<div class=\"wistia_swatch\" style=\"height: 100%; left: 0; opacity: 0; overflow: hidden; position: absolute; top: 0; transition: opacity 200ms; width: 100%;\"><img decoding=\"async\" style=\"filter: blur(5px); height: 100%; object-fit: contain; width: 100%;\" src=\"https:\/\/fast.wistia.com\/embed\/medias\/3mk0scotaf\/swatch\" alt=\"\" aria-hidden=\"true\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n        <\/div>\n      <\/div>\n      <\/div>\n  <\/div>\n<\/div><\/div><\/section><h3 class=\"wp-block-heading\" id=\"h-where-your-users-actually-are\">Wo Ihre Nutzer wirklich sind<\/h3><p>APM-Tools sind n\u00fctzlich, um zu \u00fcberwachen, was in Ihrem Stack passiert, aber ihnen fehlt die Sichtbarkeit des gesamten Internet-Stacks zwischen Ihrer Infrastruktur und der Person, die versucht, eine Seite zu laden, sich anzumelden oder eine Transaktion abzuschlie\u00dfen.<br>Ihr <a href=\"https:\/\/www.catchpoint.com\/glossary\/internet-stack\">Internet-Stack<\/a> beinhaltet die Pfade und Dienste, auf die Benutzer angewiesen sind, um Ihre Anwendungen zu erreichen, wie BGP, DNS, CDNs, Backbone-ISPs, drahtlose Netzwerke, Last-Mile-Verbindungen und Edge-Standorte.<\/p><figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/04\/Image-1-The-Internet-Stack-brings-hidden-interdependencies-1024x594.png\" alt=\"\"><\/figure><p>IPM bietet Einblicke in jede Schicht des Internet-Stacks und gibt Teams einen klareren \u00dcberblick \u00fcber die Bedingungen, die Benutzer bei Zugriff auf digitale Dienste erleben. Wenn die Leistung also nachl\u00e4sst oder eine St\u00f6rung auftritt, bestimmt diese Sichtbarkeit, ob Sie sich Ihr Problem zur Behebung ansehen oder das eines anderen.<\/p><h3 class=\"wp-block-heading\" id=\"h-what-ipm-monitors-and-why-it-matters\">Was IPM \u00fcberwacht und warum es wichtig ist<\/h3><p>Die meisten Monitoring-Tools stellen eine Frage: Ist es hochgefahren? IPM stellt eine andere Frage: Erreichen Ihre Systeme die Nutzer tats\u00e4chlich \u00fcberhaupt.<\/p><p>Das ist der Unterschied zwischen Verf\u00fcgbarkeit und Erreichbarkeit. Verf\u00fcgbarkeit zeigt, ob ein System antwortet. Erreichbarkeit gibt an, ob Benutzer \u00fcber die von ihnen genutzten Netzwerke darauf zugreifen k\u00f6nnen.<\/p><p>Diese Unterscheidung ist wichtig f\u00fcr kundenorientierte Dienste, Mitarbeiterwerkzeuge, E-Commerce-Abl\u00e4ufe, SaaS-Anwendungen und APIs. Ein Dienst kann laufen, w\u00e4hrend DNS-Aufl\u00f6sung, ISP-Routing, CDN-Verhalten oder eine Abh\u00e4ngigkeit von Drittanbietern zu Problemen f\u00fcr die Benutzer f\u00fchren.<\/p><p>IPM hilft Teams, von Vermutungen zu Beweisen zu gelangen. Wenn eine Zahlungs-API langsamer wird, die DNS-Aufl\u00f6sung sprunghaft ansteigt oder eine Anbieterroute Latenz einf\u00fchrt, liefert IPM diese Beweise auf der betroffenen Ebene des Internets-Stacks, anstatt Teams im Ungewissen dar\u00fcber zu lassen, wo im Zustellpfad die Probleme aufgetreten sind.<\/p><h3 class=\"wp-block-heading\" id=\"h-the-worlds-largest-active-monitoring-network\">Das weltweit gr\u00f6\u00dfte aktive \u00dcberwachungsnetzwerk<\/h3><p>LogicMonitor f\u00fchrt \u00fcber Catchpoint das weltweit gr\u00f6\u00dfte Netzwerk f\u00fcr aktives Monitoring aus, und von wo aus Sie \u00fcberwachen, ist wichtiger, als die meisten Leute erkennen. Wenn Sie nur von derselben Cloud-Infrastruktur aus \u00fcberwachen, in der Ihre Anwendungen gehostet werden, entsteht ein inh\u00e4renter Interessenkonflikt in Bezug auf die Sichtbarkeit. Wenn diese Infrastruktur ausf\u00e4llt oder sich verschlechtert, ist Ihr Monitoring genau denselben Bedingungen ausgesetzt.&nbsp;<\/p><p>Catchpoint adressiert dies, indem es Backbone-ISPs, Mobilfunkanbieter, Last-Mile-Netzwerke und Edge-Knoten \u00fcberwacht, die vollst\u00e4ndig von Ihrer Hosting-Umgebung entkoppelt sind. So sehen Sie klar, wenn etwas stromaufw\u00e4rts oder stromabw\u00e4rts Ihrer Infrastruktur beeintr\u00e4chtigt wird, anstatt das Signal in dem Moment zu verlieren, in dem Sie es am dringendsten ben\u00f6tigen. Dies h\u00e4lt die Outside-In-Validierung auch dann aufrecht, wenn die interne Telemetrie einwandfrei aussieht.<\/p><h3 class=\"wp-block-heading\" id=\"h-what-you-can-see-with-ipm\">Was Sie mit IPM sehen k\u00f6nnen<\/h3><p>IPM bietet Ihnen einen einheitlichen \u00dcberblick \u00fcber die Leistung Ihres gesamten Internet-Stacks. \u00dcber ein einziges Dashboard k\u00f6nnen Sie Folgendes verfolgen:<\/p><ul class=\"wp-block-list\">\n<li><strong>Gesamt-Erlebnispunktzahl<\/strong>: ein \u00dcberblick, wie Ihre Benutzer Ihr Produkt erleben<\/li>\n\n\n\n<li><strong>Kennzahlen zu Betriebszeit und Verf\u00fcgbarkeit<\/strong>Ist es oben und f\u00fcr wen<\/li>\n\n\n\n<li><strong>Web-Performance-Metriken<\/strong>Ladezeiten, Antwortzeiten und Anforderungspfade<\/li>\n\n\n\n<li><strong>Visuelle Anzeigemetriken<\/strong>: wie die Seite tats\u00e4chlich im Browser gerendert wird<\/li>\n\n\n\n<li><strong>Core Web Vitals<\/strong>: die Signale, die sowohl das Benutzererlebnis als auch das Suchranking beeinflussen<\/li>\n\n\n\n<li><strong>KI-gest\u00fctzte Ereigniserkennung<\/strong>Oberfl\u00e4chenanomalien, ohne sich durch Rauschen zu w\u00fchlen<\/li>\n<\/ul><p>F\u00fcr tiefere Analysen erm\u00f6glichen Filmstreifenansichten und detaillierte Wasserfalldaten, genau zu verfolgen, was w\u00e4hrend eines einzelnen Tests Schritt f\u00fcr Schritt passiert ist. \u00dcber das Kern-Dashboard hinaus umfasst Catchpoint IPM anpassbare Dashboards, Testmanagement, Soforttests, Zeitplanung, Benachrichtigungen und Integrationen, sodass es sich in die Workflows einf\u00fcgt, die Ihr Team bereits verwendet.<\/p><h3 class=\"wp-block-heading\" id=\"h-how-internet-performance-monitoring-supports-the-move-toward-autonomous-it\">Wie Internet Performance Monitoring die Umstellung auf autonomes IT-Management unterst\u00fctzt<\/h3><p>Autonome IT l\u00e4uft in einem geschlossenen Kreislauf: Signale erkennen, verstehen, was betroffen ist, entscheiden, was als N\u00e4chstes passieren soll, gesteuerte Ma\u00dfnahmen ergreifen und \u00fcberpr\u00fcfen, ob die Ma\u00dfnahme erfolgreich war. Jeder Schritt h\u00e4ngt von der Qualit\u00e4t der zugrunde liegenden Daten ab.<\/p><p>Die \u00dcberwachung der Internetleistung st\u00e4rkt diesen Regelkreis, indem sie Erkenntnisse liefert, die interne Telemetriedaten allein nicht bieten k\u00f6nnen. Zum Beispiel dar\u00fcber, was zwischen dem Nutzer und dem Dienst geschieht, \u00fcber die Internetwege hinweg und in Bezug auf Abh\u00e4ngigkeiten von Drittanbietern au\u00dferhalb Ihrer eigenen Infrastruktur.<br>Gemeinsam, <a href=\"https:\/\/www.logicmonitor.com\/de\/platform\">LM Envision<\/a>, <a href=\"https:\/\/www.logicmonitor.com\/blog\/edwin-ai-catchpoint-internet-visibility-autonomous-it\">Catchpoint, und Edwin AI<\/a> Bieten Sie Teams die Sichtbarkeit, den Kontext und die gesteuerte Aktion, die sie ben\u00f6tigen, um mit mehr Vertrauen in der gesamten digitalen Umgebung zu agieren.<\/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        Internet-Leistungs\u00fcberwachung in Aktion sehen      <\/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><span style=\"font-weight: 400\">Erfahren Sie, wie LogicMonitor Catchpoint nutzt, um die Transparenz \u00fcber digitale Erlebnisse, externe Abh\u00e4ngigkeiten und Internet-Performance als Teil eines vernetzten, autonomen IT-Systems zu erweitern.<\/span><\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/catchpoint\/tours-demos\" class=\"btn btn-link\" target=\"_self\">\n        Demo anfordern          <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><h2 class=\"wp-block-heading\" id=\"h-faqs\">FAQs<\/h2><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-internet-performance-monitoring-ipm\">\n            Was ist Internet-Performance-Monitoring (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><span style=\"font-weight: 400\">IPM ist ein Outside-in-Ansatz zur \u00dcberwachung, der zeigt, was zwischen Ihrer Infrastruktur und Ihren Benutzern \u00fcber die Internetpfade, Anbieter und Abh\u00e4ngigkeiten, auf die Ihre Dienste angewiesen sind, aber nicht kontrollieren, geschieht. Er erg\u00e4nzt die traditionelle Beobachtbarkeit (Observability), indem er Beweise aus der gesamten Lieferkette hinzuf\u00fcgt, sodass Teams sehen k\u00f6nnen, ob Probleme in ihrem eigenen Stack, bei einer Abh\u00e4ngigkeit oder irgendwo im Internet selbst beginnen.<\/span><\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-is-ipm-different-from-apm-or-traditional-infrastructure-monitoring\">\n            Wie unterscheidet sich IPM von APM oder herk\u00f6mmlichem Infrastruktur-Monitoring?            <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><span style=\"font-weight: 400\">Infrastruktur- und APM-Tools konzentrieren sich auf das, was innerhalb Ihrer Systeme geschieht, wie z. B. Server, Dienste und Anwendungscode. IPM konzentriert sich auf Erreichbarkeit und Erfahrung \u00fcber den Internet-Stack hinweg \u2013 DNS, BGP, CDNs, ISPs, Last-Mile-Netzwerke und Edge-Standorte \u2013, sodass Sie feststellen k\u00f6nnen, ob Benutzer in bestimmten Regionen oder Netzwerken einen Dienst tats\u00e4chlich erreichen k\u00f6nnen, auch wenn interne Dashboards gesund aussehen.<\/span><\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-why-does-reachability-matter-if-my-services-are-already-highly-available\">\n            Why does &ldquo;reachability&rdquo; matter if my services are already highly available?            <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><span style=\"font-weight: 400\">Availability tells you whether a system responds; reachability tells you whether users can access that system over the networks they use in real life. Teams often see incidents where everything is &ldquo;green&rdquo; internally while users in one geography or ISP see timeouts or failures, and IPM closes that gap by revealing where along the Internet path things are breaking.<\/span><\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-where-does-catchpoint-monitor-from-and-why-does-that-matter\">\n            Where does Catchpoint monitor from, and why does that 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\">\n            <p><span style=\"font-weight: 400\">Catchpoint&rsquo;s global agent network runs active tests from backbone ISPs, wireless carriers, last-mile networks, and edge locations that are decoupled from your hosting providers. That independence means your visibility does not disappear during a cloud or provider outage, and you can quickly see whether problems are upstream, downstream, or inside your own environment.<\/span><\/p>\n                      <\/div>\n        <\/div>\n              <div class=\"accordion-block__item\">\n          \n          <h3 class=\"accordion-block__question\" id=\"h-how-does-ipm-support-autonomous-it-with-logicmonitor\">\n            How does IPM support Autonomous IT with LogicMonitor?            <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><span style=\"font-weight: 400\">Within the LogicMonitor platform, IPM data feeds the Autonomous IT closed loop by adding real-world Internet performance and digital experience evidence into detection, diagnosis, decision-making, and verification. LM Envision provides internal telemetry, Catchpoint extends visibility to user experience and Internet performance, and Edwin AI uses that combined context to guide governed action during incidents.<\/span><\/p>\n                      <\/div>\n        <\/div>\n          <\/div>\n  <\/div>","protected":false},"excerpt":{"rendered":"<p>Sehen Sie, wie Catchpoint die Sichtbarkeit von LogicMonitor \u00fcber digitales Erlebnis, externe Abh\u00e4ngigkeiten und Internet-Performance f\u00fcr autonomes IT erweitert.<\/p>","protected":false},"author":16,"featured_media":612530,"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":[7753,5331,7811,5346,5683,7777,7752,7018,7084,7794],"industry":[6790],"language":[7],"role":[6786],"lm_search_queries":[],"lm_strategic_tags":[],"topic":[6774],"class_list":["post-612528","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-all","language-english","role-itops","topic-digital-experience"],"acf":{"is_global_bar_disabled":false,"is_global_bar_overriden":false,"is_search_excluded":false,"page_language":"english","translated_pages":"","reviewers":false,"is_global_form_disabled":false,"is_global_form_override":false,"component_layouts":false,"related_resources":false,"updated_date":"","author_section_checkbox":false,"reviewer_name":""},"yoast_head":"<!-- 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IT beginnt jetzt: Treffen Sie LogicMonitor auf dem AWS Summit New York"},"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        Der schnelle \u00dcberblick      <\/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><span style=\"font-weight: 400\">LogicMonitor will be at AWS Summit New York to show how teams can connect AWS monitoring, digital experience data, and AI-guided operations before performance issues reach customers.<\/span><\/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><span style=\"font-weight: 400\">LogicMonitor runs on AWS and has first-hand migration experience from moving its own data centers to AWS.<\/span><\/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><span style=\"font-weight: 400\">LM Envision gives teams visibility across AWS services, hybrid infrastructure, VMware environments, Kubernetes, networks, storage, applications, and business services.<\/span><\/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><span style=\"font-weight: 400\">Edwin AI brings together telemetry, topology, event context, and service impact to help teams understand what changed, what&rsquo;s affected, and what to do next.<\/span><\/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><span style=\"font-weight: 400\">Catchpoint adds outside-in visibility across digital experience, Internet performance, application journeys, DNS, API, CDN, ISP, SaaS, and external dependencies.<\/span><\/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><span style=\"font-weight: 400\">At AWS Summit New York, LogicMonitor will focus on AWS migration, AI and high-performance workloads, operational noise reduction, and digital experience visibility.<\/span><\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p>AI is changing how teams build, deploy, and support digital services. It&rsquo;s also putting more pressure on the systems behind those services: compute, storage, networks, Kubernetes clusters, Internet paths, third-party dependencies, and hybrid infrastructure.<\/p><p>For many enterprises, more of that system now runs on AWS. At AWS Summit New York, LogicMonitor will show how teams can connect AWS monitoring, digital experience data, and AI-guided operations before performance issues reach customers.<\/p><div class=\"rtc-text-content rtc-text-content__light bg-cool-grey-50\">\n  \n  <div class=\"rtc-text-content__wrapper\">\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><span style=\"font-weight: 400\">Meet LogicMonitor at AWS Summit New York and see how Autonomous IT connects AWS, hybrid infrastructure, digital experience, and Internet performance.<\/span><\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/de\/aws\" class=\"btn btn-link\" target=\"_self\">\n        Schedule a meeting          <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><h2 class=\"wp-block-heading\" id=\"h-aws-modernization-needs-a-new-operating-model\">AWS Modernization Needs a New Operating Model<\/h2><p>AWS gives enterprises the scale and flexibility to modernize quickly. Teams are migrating VMware workloads, expanding cloud-native services, building on Kubernetes, experimenting with generative AI, and using AWS services like Amazon Bedrock and SageMaker to move faster.<\/p><p>EC2 instances launch and terminate. Kubernetes clusters scale. Applications depend on services inside and outside AWS. AI workloads add new performance and cost variables. A single customer-facing experience may rely on cloud infrastructure, data center systems, external APIs, DNS, CDN performance, Internet routing, and SaaS services.<\/p><p>Dashboards alone can&rsquo;t connect those signals fast enough during an incident. Teams need to know which service changed, which users are affected, and whether the issue sits inside AWS, outside AWS, or somewhere between systems.<\/p><h2 class=\"wp-block-heading\" id=\"h-logicmonitor-and-aws-a-partnership-built-for-hybrid-transformation\">LogicMonitor and AWS: A Partnership Built for Hybrid Transformation<\/h2><p>LogicMonitor runs on AWS and has migrated from its own data centers to AWS, giving the team first-hand experience with cloud transformation. That experience shapes how we help customers plan migrations, reduce risk, validate performance, and operate after workloads move.<\/p><p>For AWS customers, LogicMonitor provides visibility across cloud and hybrid environments, including AWS services, on-premises infrastructure, VMware environments, Kubernetes, networks, storage, applications, and business services.<\/p><p>LogicMonitor is also available in AWS Marketplace, giving customers a streamlined way to buy through AWS. For organizations with AWS committed spend, Private Offers can simplify purchasing while supporting broader modernization work.<\/p><h2 class=\"wp-block-heading\" id=\"h-edwin-ai-turns-signals-into-next-steps\">Edwin AI Turns Signals into Next Steps<\/h2><p>Edwin AI is LogicMonitor&rsquo;s AI agent for IT operations. It brings together telemetry, topology, event context, and service impact so teams can understand what changed, what&rsquo;s affected, and what to do next.<\/p><p>In AWS environments, that context can change by the minute as instances launch, containers scale, dependencies shift, and customer-facing services move across cloud and hybrid systems. Metrics, logs, traces, events, configuration changes, and performance data all move too fast for manual correlation.<\/p><p>Edwin AI reduces that work by adapting thresholds, correlating events, surfacing context-rich alerts, accelerating root cause analysis, summarizing incidents, and recommending next actions. Teams get clearer priorities during incidents and a practical path to governed automation where it makes sense.<\/p><h2 class=\"wp-block-heading\" id=\"h-no-blind-spots-means-seeing-aws-from-the-inside-out-and-outside-in\">No Blind Spots Means Seeing AWS From the Inside Out and Outside In<\/h2><p>Most AWS monitoring conversations start inside the cloud. Teams need visibility into services like EC2, S3, RDS, EKS, ECS, Lambda, VPC, load balancing, Bedrock, and SageMaker.<\/p><p>But customers don&rsquo;t experience infrastructure from the inside.<\/p><p>They experience applications from the outside. They feel slow page loads, failed transactions, broken journeys, regional latency, third-party outages, and Internet performance issues. They don&rsquo;t care whether the root cause lives in AWS, a data center, a DNS provider, a CDN, an API dependency, or somewhere between systems.<\/p><p>That&rsquo;s where Catchpoint adds critical outside-in visibility. It extends LogicMonitor&rsquo;s view beyond internal systems into digital experience, application journeys, web performance, DNS, API, CDN, ISP, SaaS, external dependencies, and Internet performance. Teams can validate whether services are reachable, responsive, and performing the way users expect.<\/p><p>With internal AWS telemetry and outside-in experience data in the same operating picture, teams can answer sharper incident questions:<\/p><ul class=\"wp-block-list\">\n<li>Is the issue inside AWS, outside AWS, or somewhere between systems?<\/li>\n\n\n\n<li>&nbsp;Which users, regions, services, or application journeys are affected?<\/li>\n\n\n\n<li>&nbsp;Is this a service issue, an Internet issue, an external dependency issue, or a hybrid infrastructure issue?<\/li>\n\n\n\n<li>&nbsp;What should the team prioritize first?<\/li>\n\n\n\n<li>&nbsp;How do we verify that the experience has recovered?<\/li>\n<\/ul><h2 class=\"wp-block-heading\" id=\"h-modernization-doesnt-end-when-workloads-move\">Modernization Doesn&rsquo;t End When Workloads Move<\/h2><p>A migration isn&rsquo;t finished when the workload moves. Teams still need to validate performance, monitor dependencies, control costs, and make sure users aren&rsquo;t affected.<\/p><p>AI initiatives create a similar operational burden. Once a model is deployed, teams still need to monitor the infrastructure supporting it, including compute, storage, networking, Kubernetes, AWS AI services, application dependencies, and user experience.<\/p><p>LogicMonitor helps teams automatically discover AWS resources and maintain visibility as environments change. For organizations migrating from VMware, modernizing data centers, or running across AWS and traditional infrastructure, that continuity reduces the risk of losing context mid-transition.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-to-expect-from-logicmonitor-at-aws-summit-new-york\"><br>What to Expect From LogicMonitor at AWS Summit New York<\/h2><p>We&rsquo;ll be talking with AWS Summit attendees about:<\/p><h3 class=\"wp-block-heading\" id=\"h-aws-migration-and-modernization\">AWS Migration and Modernization<\/h3><p>How to discover dependencies, monitor source and destination environments side by side, and validate performance before, during, and after migration.<\/p><h3 class=\"wp-block-heading\" id=\"h-ai-and-high-performance-workloads\">AI and High-Performance Workloads<\/h3><p>How to monitor Bedrock, SageMaker, EKS, EC2 GPU instances, compute utilization, storage, network performance, and the hybrid systems behind AI applications.<\/p><h3 class=\"wp-block-heading\" id=\"h-edwin-ai\">Edwin AI<\/h3><p>How AI-guided correlation, anomaly detection, dynamic thresholds, incident summaries, and recommended next actions reduce manual triage.<\/p><h3 class=\"wp-block-heading\" id=\"h-catchpoint\">Auffangpunkt<\/h3><p>How outside-in visibility across user experience, DNS, API, CDN, ISP, SaaS, and Internet health validates whether services are working for customers.<\/p><h2 class=\"wp-block-heading\" id=\"h-get-clearer-answers-during-aws-incidents\">Get Clearer Answers During AWS Incidents<\/h2><p>Most IT teams aren&rsquo;t asking for another dashboard. They need to know what changed, what&rsquo;s at risk, which users are affected, and what action to take next.<\/p><p>At AWS Summit New York, let&rsquo;s talk about where AWS visibility, digital experience monitoring, and AI-guided operations can reduce risk in your 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        Meet LogicMonitor at AWS Summit New York      <\/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><span style=\"font-weight: 400\">See how LogicMonitor helps AWS customers connect cloud visibility, digital experience monitoring, and AI-guided operations with LM Envision, Catchpoint, and Edwin AI.<\/span><\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/de\/aws\" class=\"btn btn-link\" target=\"_self\">\n        Mehr erfahren          <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>","protected":false},"excerpt":{"rendered":"<p>Sehen Sie, wie LogicMonitor mit Edwin AI, Catchpoint und vereinheitlichter Sichtbarkeit \u00fcber hybride Systeme hinweg Autonomous IT f\u00fcr AWS bringt.<\/p>","protected":false},"author":16,"featured_media":612524,"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":[5339,7758,5408,7850,5814,7777,7813,6264,6311,7752],"industry":[6790],"language":[7],"role":[6784],"lm_search_queries":[],"lm_strategic_tags":[],"topic":[6770],"class_list":["post-612522","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-all","language-english","role-cloudops","topic-cloud"],"acf":{"is_global_bar_disabled":false,"is_global_bar_overriden":false,"is_search_excluded":false,"page_language":"english","translated_pages":"","reviewers":false,"is_global_form_disabled":false,"is_global_form_override":false,"component_layouts":false,"related_resources":false,"updated_date":"","author_section_checkbox":false,"reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.9 (Yoast SEO v27.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Autonomous IT Starts Now: Meet LogicMonitor at AWS Summit New York | LogicMonitor<\/title>\n<meta name=\"description\" content=\"LogicMonitor\u2019s AWS Summit New York presence highlights Autonomous IT, Edwin AI-first observability, and Catchpoint-powered visibility across AWS, hybrid infrastructure, and digital experience.\" \/>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Autonomous IT Starts Now: Meet LogicMonitor at AWS Summit New York\" \/>\n<meta property=\"og:description\" content=\"LogicMonitor\u2019s AWS Summit New York presence highlights Autonomous IT, Edwin AI-first observability, and Catchpoint-powered visibility across AWS, hybrid infrastructure, and digital experience.\" 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eine Forrester TEI-Studie \u00fcber Edwin AI IT-F\u00fchrungskr\u00e4ften tats\u00e4chlich sagt \u2013 und wie man sie nutzt"},"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        Der schnelle \u00dcberblick      <\/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>This blog helps IT leaders use the Forrester Consulting TEI&trade; study as a practical framework for evaluating Edwin AI in their own environments.<\/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>Use the TEI study to glean the detail behind the 313% ROI headline and understand where the modeled value came from<\/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>Compare the study&rsquo;s assumptions against your own incident workflow, including alert noise, RCA effort, escalations, downtime, SLA exposure, and engineering capacity.<\/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>Bring the study into budget and planning conversations as a structured way to connect incident response improvements to business impact.<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p>A Total Economic Impact&trade; study is useful for one, critical reason: it takes a broad technology claim and turns it into a financial and operational framework.<\/p><p>That matters in AI for IT operations because the market is crowded with claims. Every platform says it reduces noise. Every platform says it improves efficiency. Every platform says it helps teams move faster. What IT leaders need is a clearer way to separate vague value from actual impact.<\/p><p>That is why the commissioned Forrester Consulting study, <em>The Total Economic Impact&trade; Of LogicMonitor&rsquo;s Edwin AI<\/em>, deserves a closer read.<\/p><p>LogicMonitor commissioned Forrester Consulting to conduct a Total Economic Impact&trade; study to examine the potential return on investment enterprises may realize by deploying Edwin AI. Forrester interviewed seven decision-makers at five organizations using Edwin AI, then aggregated those findings into a composite organization to model costs, benefits, flexibility, and risk over three years. The composite organization represents a multinational enterprise with $2.5 billion in annual revenue, 5,000 employees, and business-critical applications running across hybrid cloud and on-premises infrastructure.<\/p><p>For that composite organization, the study found that Edwin AI delivered:<\/p><ul class=\"wp-block-list\">\n<li>313% ROI<\/li>\n\n\n\n<li>$2.7 million net present value<\/li>\n\n\n\n<li>Payback in less than six months<\/li>\n\n\n\n<li>$3.6 million in three-year risk-adjusted present value benefits<\/li>\n<\/ul><p>Those numbers matter. They help quantify the business case. But the more useful question for IT leaders is not just what the modeled return was. It is where that return came from, and what it says about the way modern incident operations need to change.<\/p><h2 class=\"wp-block-heading\" id=\"h-this-study-is-not-just-about-roi\">This study is not just about ROI<\/h2><p>The headline ROI matters. It gets attention. It helps justify investment. But the real value of a TEI study <strong>is that it shows where the economic impact comes from.<\/strong><\/p><p>In this case, the benefits are far from abstract. They are tied to the operational failure points most teams already know too well:<\/p><ul class=\"wp-block-list\">\n<li>Too many alerts<\/li>\n\n\n\n<li>Too much manual triage<\/li>\n\n\n\n<li>Too much time spent correlating signals across fragmented tools<\/li>\n\n\n\n<li>Too many escalations<\/li>\n\n\n\n<li>Too much downtime risk<\/li>\n\n\n\n<li>Too much senior engineering time spent on work that should not require senior engineers<\/li>\n<\/ul><p>This study gives IT and operations leaders a concrete way to think about what AI should be doing in production environments, not generating more dashboards, but removing friction from incident workflows.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-the-findings-suggest-about-modern-it-operations\">What the findings suggest about modern IT operations<\/h2><p>The strongest signal in the report is not that Edwin AI is &ldquo;faster&rdquo; or &ldquo;smarter.&rdquo; It is that the traditional operating model has become too manual to scale.<\/p><p>The gains start early, then build over time. In the study, the composite organization achieved a 75% reduction in alert noise and a 60% reduction in time spent on root cause analysis (RCA) in Year 1, improving to 90% and 70% by Year 3. It also reduced mean time to resolve customer-facing P1 and P2 incidents by 40% in Year 1 and cut SLA-breaching P1\/P2 incidents by 30%, with both measures improving further by Year 3.<\/p><p>Taken together, those findings show how improvements in one part of the incident lifecycle can strengthen the next.<\/p><p>Noise reduction by itself helps, but only to a point. Faster RCA by itself helps, but only after the incident has already become serious. The real operational change happens when these capabilities stack:<\/p><ul class=\"wp-block-list\">\n<li>Fewer irrelevant alerts reach engineers<\/li>\n\n\n\n<li>Related signals are grouped earlier<\/li>\n\n\n\n<li>Context is surfaced sooner<\/li>\n\n\n\n<li>Teams spend less time guessing<\/li>\n\n\n\n<li>Incidents get resolved faster<\/li>\n\n\n\n<li>Fewer customer-facing events turn into larger business problems<\/li>\n<\/ul><p>That is what IT leaders should take from this study. The benefit is a different operating model for incident response.<\/p><h2 class=\"wp-block-heading\" id=\"h-incident-work-has-outgrown-manual-correlation\">Incident work has outgrown manual correlation<\/h2><p>Most operations teams are managing environments that were not designed for today&rsquo;s level of dependency and change. Hybrid infrastructure, cloud services, distributed applications, and fragmented tools have increased the number of signals teams need to interpret during an incident. The work has become more interconnected, while the response process often still depends on manual correlation.<\/p><p>That creates a familiar pattern: teams spend too much time sorting the conditions around an incident before they can address the issue itself.<\/p><p>In the study, interviewees described this problem in direct terms. One chief customer service officer in IT services said, &ldquo;The number of alerts was simply too high. On a daily basis, we were averaging more than 10,000 alerts, which made it impossible to proactively manage alerts and incidents.&rdquo;<\/p><p>A platform owner in IT services described the same issue at the tooling level: &ldquo;We had too many systems and platforms in place, and the tooling was fragmented. Without a single, standardized platform, it was difficult to connect signals across environments and respond efficiently.&rdquo;<\/p><p>That is the practical problem Edwin AI is meant to address. AI only matters here if it helps teams make signal usable sooner: fewer duplicate alerts, clearer incident context, faster root cause analysis, and less time spent moving between disconnected systems.<\/p><h2 class=\"wp-block-heading\" id=\"h-how-to-use-this-tei-study\">How to use this TEI study<\/h2><p>A TEI study is most useful when you use it to evaluate your own operating model. The headline financial metrics matter, but the better read is in the assumptions, benefit categories, and workflow changes behind them.<\/p><h3 class=\"wp-block-heading\" id=\"h-1-compare-the-study-to-your-current-incident-workflow\">1. Compare the study to your current incident workflow<\/h3><p>Start with the conditions the TEI study models:<\/p><ul class=\"wp-block-list\">\n<li>alert fatigue<\/li>\n\n\n\n<li>duplicate incidents<\/li>\n\n\n\n<li>slow triage<\/li>\n\n\n\n<li>prolonged root cause analysis<\/li>\n\n\n\n<li>avoidable downtime<\/li>\n\n\n\n<li>SLA exposure<\/li>\n\n\n\n<li>skilled engineers spending time on repetitive incident work<\/li>\n<\/ul><p>If those conditions sound familiar, the study gives you a practical way to assess where your current incident process may be costing more than it should. The point is to connect the financial model to the work your teams already perform every day.<\/p><h3 class=\"wp-block-heading\" id=\"h-2-bring-the-right-stakeholders-into-the-conversation\">2. Bring the right stakeholders into the conversation<\/h3><p>The value of Edwin AI will look different depending on who is evaluating it.<\/p><p>Operations leaders may focus on alert volume, triage effort, MTTR, and incident throughput. Engineering leaders may focus on how much expert time is spent on repetitive investigation and escalation work. Service owners may focus on uptime, SLA performance, and customer-facing impact. Finance leaders may focus on cost avoidance, payback period, and the relationship between benefits and total investment.<\/p><h3 class=\"wp-block-heading\" id=\"h-3-use-the-model-as-a-benchmark\">3. Use the model as a benchmark<\/h3><p>The study is based on a composite organization, so the results should be read as a model rather than a forecast for every company. Use it to pressure-test your own assumptions:<\/p><ul class=\"wp-block-list\">\n<li>Is your alert volume higher or lower?<\/li>\n\n\n\n<li>How much of your triage process is still manual?<\/li>\n\n\n\n<li>How often do P1 and P2 incidents affect customer-facing services?<\/li>\n\n\n\n<li>What does downtime cost your business?<\/li>\n\n\n\n<li>How material are SLA penalties or service credits?<\/li>\n\n\n\n<li>How much L2 and L3 time goes into root cause analysis?<\/li>\n\n\n\n<li>How much effort goes into maintaining alerting rules, routing logic, and event-management workflows?<\/li>\n<\/ul><p>The value of the report is in helping you ask more precise questions before building a business case.<\/p><h3 class=\"wp-block-heading\" id=\"h-4-identify-the-first-workflow-worth-improving\">4. Identify the first workflow worth improving<\/h3><p>The best starting point is usually the workflow where manual effort is measurable and tied to business impact.<\/p><p>A better approach is to start where the cost of operational friction is highest:<\/p><ul class=\"wp-block-list\">\n<li>alert correlation<\/li>\n\n\n\n<li>incident enrichment<\/li>\n\n\n\n<li>root cause acceleration<\/li>\n\n\n\n<li>customer-facing outage response<\/li>\n\n\n\n<li>repetitive triage workflows<\/li>\n<\/ul><p>A useful first use case should have a clear baseline, repeatable workflow, and outcome that matters beyond one team. Alert noise is often a strong entry point because it affects triage, escalation, root cause analysis, and engineering capacity at the same time.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-customer-validation-adds-to-the-study\">What customer validation adds to the study<\/h2><p>The TEI study gives readers a financial model. The customer validation alongside helps explain why the benefit categories matter in the first place.<\/p><p>The numbers in the study are organized around measurable outcomes: reduced alert noise, faster root cause analysis, lower MTTR, fewer SLA-breaching incidents, and less time spent managing prior event-management workflows. That structure is useful for a business case, but it can make the work sound cleaner than it feels inside an operations team.<\/p><p>The customer interviews add that missing layer. They show how those categories overlap during an actual incident.<\/p><p>One network manager in IT services described the problem this way: &ldquo;The main callout from customers was around SLAs. We had a lot of breaches and a lot of tickets that were false positives. We were focusing on issues that weren&rsquo;t critical instead of prioritizing based on impact, and we didn&rsquo;t have clear dependency mapping between devices, which made it difficult to address the most impactful problems first.&rdquo;<\/p><p>That quote connects several parts of the business case at once: false positives increase triage effort, poor dependency mapping slows prioritization, slow prioritization increases SLA exposure, and SLA exposure turns an operations problem into a financial one.<\/p><p>A global head of IT networks in agriculture made a related point from the other side of the workflow: &ldquo;We know about problems quicker, we get to the root cause faster, and we&rsquo;re not being bombarded with noise like a site issue triggering 50 device alerts. Edwin AI does that correlation work for us and tells us roughly where the issue is, and most of the time that&rsquo;s exactly where it is.&rdquo;<\/p><p>Alert correlation is not only a queue-management improvement. It changes the quality of the investigation that follows. When related signals are grouped earlier, the team starts closer to the likely cause, and senior engineers spend less time reconstructing the incident from scattered evidence.<\/p><p>These interviews are useful because they make the study easier to apply. The question is where your team sees the same pattern: high alert volume, weak signal quality, unclear dependencies, repeated escalation, slow RCA, or service risk that grows because teams cannot identify impact quickly enough.<\/p><h2 class=\"wp-block-heading\" id=\"h-read-the-study-with-your-own-environment-in-mind\">Read the study with your own environment in mind<\/h2><p>Use the study to examine where incident response is costing your team time, budget, and focus.<\/p><p>Start with the parts of the workflow that are easiest to inspect.&nbsp;<\/p><ul class=\"wp-block-list\">\n<li>Where does alert noise still create measurable waste?&nbsp;<\/li>\n\n\n\n<li>Which incidents still require engineers to correlate signals across tools by hand?&nbsp;<\/li>\n\n\n\n<li>Where are senior engineers getting pulled into work that could be handled earlier in the process?&nbsp;<\/li>\n\n\n\n<li>What do customer-facing outages, SLA misses, or delayed escalations cost the business?&nbsp;<\/li>\n\n\n\n<li>Which workflow would show value fastest if the manual effort around it were reduced?<\/li>\n<\/ul><p>Those questions make the study more useful. They turn the model into a way to evaluate your own operating constraints, instead of treating it as a generic proof point.<\/p><p>This study gives IT leaders a disciplined way to assess the potential financial impact of Edwin AI. The broader takeaway is more practical: modern operations teams need more than visibility. They need incident workflows that reduce noise, preserve attention, shorten investigation, and help teams act with better context.<\/p><p>That is where the business case starts.<\/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        Read the Forrester Consulting Total Economic Impact&trade; study to see the full methodology, assumptions, cost model, and benefit breakdown for LogicMonitor Edwin AI.      <\/h4>\n    \n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/resources\/logicmonitor-edwin-ai-total-economic-impact-study-by-forrester\" class=\"btn btn-link\" target=\"_self\">\n        Get the study          <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>","protected":false},"excerpt":{"rendered":"<p>Eine beauftragte TEI\u2122-Studie von Forrester Consulting gibt IT-F\u00fchrungskr\u00e4ften einen finanziellen Rahmen zur Bewertung der Auswirkungen von Edwin AI auf Alarmrauschen, Ursachenanalyse (RCA), mittlere Zeit zur Behebung (MTTR), SLA-Risiken und operative Effizienz.<\/p>","protected":false},"author":46,"featured_media":609874,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[1],"tags":[],"industry":[6790],"language":[7],"role":[],"lm_search_queries":[],"lm_strategic_tags":[],"topic":[],"class_list":["post-612432","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-all","language-english"],"acf":{"page_language":"english","translated_pages":"","reviewers":false,"is_global_bar_disabled":false,"is_global_bar_overriden":false,"is_search_excluded":false,"is_global_form_disabled":false,"is_global_form_override":false,"component_layouts":false,"updated_date":"","author_section_checkbox":true,"author_image":"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2025\/02\/margo-2-1.jpeg","author_linkedin":"https:\/\/www.linkedin.com\/in\/mspoda\/","author_name":"Margo Poda","author_job_title":"Sr. Content Marketing Manager, AI","author_dept":"Edwin AI","author_bio":"Margo Poda leads content strategy for Edwin AI at LogicMonitor. With a background in both enterprise tech and AI startups, she focuses on making complex topics clear, relevant, and worth reading\u2014especially in a space where too much content sounds the same. She\u2019s not here to hype AI; she\u2019s here to help people understand what it can actually do.","reviewer_name":"","related_resources":false},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.9 (Yoast SEO v27.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>What a Forrester TEI study on Edwin AI actually tells IT leaders\u2014and how to use it | LogicMonitor<\/title>\n<meta name=\"description\" content=\"A commissioned Forrester Consulting TEI\u2122 study gives IT leaders a financial framework for evaluating Edwin AI\u2019s impact on alert noise, RCA, MTTR, SLA risk, and operational efficiency.\" \/>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What a Forrester TEI study on Edwin AI actually tells IT leaders\u2014and how to use it\" \/>\n<meta property=\"og:description\" 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LogicMonitor","isPartOf":{"@id":"https:\/\/www.logicmonitor.com\/de\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.logicmonitor.com\/de\/blog\/what-forrester-tei-study-edwin-ai-tells-it-leaders#primaryimage"},"image":{"@id":"https:\/\/www.logicmonitor.com\/de\/blog\/what-forrester-tei-study-edwin-ai-tells-it-leaders#primaryimage"},"thumbnailUrl":"https:\/\/www.logicmonitor.com\/wp-content\/uploads\/2026\/05\/Blog_Forrester_940x600_Featured-Image.png","datePublished":"2026-06-01T18:30:10+00:00","dateModified":"2026-06-01T18:30:14+00:00","description":"A commissioned Forrester Consulting TEI\u2122 study gives IT leaders a financial framework for evaluating Edwin AI\u2019s impact on alert noise, RCA, MTTR, SLA risk, and operational 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der Erkenntnis zur Aktion: Logicmonitor + Catchpoint f\u00fcr vereinheitlichte Beobachtbarkeit einsatzbereit machen"},"content":{"rendered":"<?xml encoding=\"UTF-8\"><section id=\"\" class=\"section bg-white theme-light    section-bg-dark\">\n        <div class=\"section-content container\">\n    <div class=\"full-width-media-wrapper\">\n<div class=\"media-assets-block\">\n    <div class=\"media-container object-center-center aspect-auto type-wistia_embed\" style=\"max-width: 100svh; \">\n\n          <div class=\"wistia_embed\">\n        <div class=\"\">\n          <p><script src=\"https:\/\/fast.wistia.com\/embed\/medias\/ogpqinu8f0.jsonp\" async><\/script><br>\n<script src=\"https:\/\/fast.wistia.com\/assets\/external\/E-v1.js\" async><\/script><\/p>\n<div class=\"wistia_responsive_padding\" style=\"padding: 56.25% 0 0 0; position: relative;\">\n<div class=\"wistia_responsive_wrapper\" style=\"height: 100%; left: 0; position: absolute; top: 0; width: 100%;\">\n<div class=\"wistia_embed wistia_async_ogpqinu8f0 videoFoam=true\" style=\"height: 100%; position: relative; width: 100%;\">\n<div class=\"wistia_swatch\" style=\"height: 100%; left: 0; opacity: 0; overflow: hidden; position: absolute; top: 0; transition: opacity 200ms; width: 100%;\"><img decoding=\"async\" style=\"filter: blur(5px); height: 100%; object-fit: contain; width: 100%;\" src=\"https:\/\/fast.wistia.com\/embed\/medias\/ogpqinu8f0\/swatch\" alt=\"\" aria-hidden=\"true\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n        <\/div>\n      <\/div>\n      <\/div>\n  <\/div>\n<\/div><\/div><\/section><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        Der schnelle \u00dcberblick      <\/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><span style=\"font-weight: 400\">Visibility without control is just expensive awareness.<\/span><\/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><span style=\"font-weight: 400\">Combining LogicMonitor infrastructure telemetry with Catchpoint experience data gives IT a user&#8209;to&#8209;code view that connects internal behavior to real&#8209;world user impact.<\/span><\/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><span style=\"font-weight: 400\">Edwin AI condenses noisy alerts into a single, plain&#8209;language insight by correlating VPN, DNS, and Catchpoint signals around SD&#8209;WAN and other critical services.<\/span><\/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><span style=\"font-weight: 400\">Catchpoint ISP benchmarking tracks carrier performance across DNS, TCP, and time&#8209;to&#8209;first&#8209;byte over time so you can hold third parties accountable instead of absorbing blame.<\/span><\/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><span style=\"font-weight: 400\">When your observability stack can&rsquo;t show who is affected, why, or what to do, the missing piece is connected data.<\/span><\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p>Most IT teams can see when something&rsquo;s wrong, but can&rsquo;t easily tell who&rsquo;s affected, why, or what to do next. In other words, they lack real control. In this in&#8209;depth session, LogicMonitor&rsquo;s Callum Brown and Brandon Delap showed how to move past that. They walked through ISP benchmarking, workforce experience scoring, and Edwin AI turning a stream of noisy alerts into a single, plain&#8209;language explanation of what broke and why.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-experts-discussed\">Was Experten diskutierten<\/h2><p>Seeing an issue and controlling the outcome are two different things<\/p><p>As Callum Brown, Senior Sales Engineer at LogicMonitor, put it in the session, full&#8209;stack visibility is what lets teams move from just spotting issues to preventing negative user experience. Detection tells you something happened. Control tells you what it means for the business, who is affected, and what action to take. The webinar positioned the <a href=\"https:\/\/www.logicmonitor.com\/blog\/autonomous-operations-without-blind-spots\">LogicMonitor and Catchpoint integration<\/a> as the bridge between those two states, with infrastructure telemetry on one side and real user experience on the other.<\/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#quote_light\"><\/use>\n    <\/svg><\/span>\n  \n  <div class=\"rtc-text-content__wrapper\">\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><span style=\"font-weight: 400\">Full-stack visibility helps us move from &lsquo;can we see an issue&rsquo; to &lsquo;can we preempt negative user experience due to an issue.&rsquo; In the modern enterprise, observability is what lets every leader hit their goals.<\/span><\/p>\n      <\/div>\n    \n          \n                                <div class=\"rtc-text-content__author\">\n                          <strong class=\"fs-text-lg font-bold text-core-blue-500\">\n                Callum Brown              <\/strong>\n                                      <span class=\"fs-text-md text-core-blue-500\">\n                Senior Sales Engineer, LogicMonitor              <\/span>\n                      <\/div>\n              \n            <\/div>\n<\/div><h3 class=\"wp-block-heading\" id=\"h-isp-benchmarking-that-turns-slas-into-evidence\">ISP benchmarking that turns SLAs into evidence<\/h3><p>Brandon Delap, Manager, Solutions Engineering, Catchpoint (a LogicMonitor company), made a point that ran through the session: customers don&rsquo;t know and don&rsquo;t care that a CDN, ISP, or carrier is outside your control. Once they try to log in, they expect it to work. That reality creates a painful accountability problem for IT teams.<\/p><p>In the session, Delap used a Catchpoint ISP benchmarking demo to highlight how third&#8209;party carriers can quietly degrade experience over time. Catchpoint benchmarks providers like Tata, Jio, and Vodafone over weeks and months, with at least 13 months of ISP performance history across connectivity, DNS, TCP, and TTFB, giving IT teams hard data to bring to carrier conversations rather than relying on user complaints or gut feel.<\/p><h3 class=\"wp-block-heading\" id=\"h-edwin-ai-connects-signals-humans-cannot-process-at-speed\">Edwin AI connects signals humans cannot process at speed<\/h3><p>Delap showed how Edwin AI collapses a noisy stream of alerts into a single insight tied to an SD&#8209;WAN hub, so operators see one clear explanation they can act on instead of dozens of separate notifications. Edwin AI &ldquo;actually tells me in plain English what went wrong at that point in time from a Catchpoint event correlated with a LogicMonitor event,&rdquo; he said. That ability to pull together infrastructure, internet, application, and change data into a single explanation is where AI starts to earn its place in the operations workflow.<\/p><h3 class=\"wp-block-heading\" id=\"h-proactive-workforce-management-changes-who-files-the-ticket\">Proactive workforce management changes who files the ticket<\/h3><p>Catchpoint&rsquo;s workforce management view breaks experience into endpoint health, network quality, and application performance for each user and location, then rolls that into an overall experience score. Global and regional heat maps show where issues are starting to appear, while user&#8209;level Wi&#8209;Fi and application metrics flag whether problems stem from the device, the network, or a specific SaaS page.&nbsp;<\/p><p>Instead of waiting for &ldquo;I can&rsquo;t connect to the office on Monday morning&rdquo; tickets, operations teams can see trouble spots forming and act before employees start reporting slowness. That&rsquo;s the shift the presenters pushed for: moving from reactive troubleshooting to genuinely preemptive operations.<\/p><h3 class=\"wp-block-heading\" id=\"h-what-it-operations-leaders-should-take-from-this\">What IT operations leaders should take from this<\/h3><p><strong>Connected data matters more than more data. <\/strong>If your observability investments sit in silos, adding another dashboard won&rsquo;t solve the problem. Connecting the data you already collect will. Edwin AI reasons across infrastructure, internet, application, and change data in a single context, so teams see one coherent story instead of isolated signals from separate tools.<\/p><p><strong>Third-party accountability requires third-party evidence.<\/strong> When critical services depend on ISPs, CDNs, and SaaS providers, &ldquo;we think the problem is your network&rdquo; is not enough to drive change. Catchpoint benchmarks specific carriers over time with granular metrics like DNS resolution, TCP connect time, and TTFB, so you can show providers exactly where performance degraded over weeks or months and hold them accountable with evidence rather than user complaints.<\/p><p><strong>Let AI handle the correlation you can&rsquo;t sustain manually. <\/strong>Brown was direct about Edwin AI&rsquo;s role: &ldquo;Let AI do the heavy lifting&hellip; it definitely is doing it at a scale that humans either can&rsquo;t or don&rsquo;t really want to do.&rdquo; The value is eliminating the hours spent manually tracing an alert through multiple systems to find the root cause, so your team can act on the answer instead of hunting for it.<\/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        H\u00f6ren Sie auf, \u00dcberwachungsmodule zu verwalten, und sehen Sie Ihren gesamten Hybrid-Stack an einem Ort.      <\/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><span style=\"font-weight: 400\">Sehen Sie sich eine Demo an, um zu erfahren, wie eine native SaaS-Plattform den Verwaltungsaufwand reduziert und die Reaktion auf Vorf\u00e4lle beschleunigt.<\/span><\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/de\/platform-demo\" class=\"btn btn-link\" target=\"_self\">\n        Demo ansehen          <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><h3 class=\"wp-block-heading\" id=\"h-recommended-reading-and-webinars\">Empfohlene Lekt\u00fcre und Webinare <\/h3><ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.logicmonitor.com\/de\/logicmonitor-catchpoint\">LogicMonitor + Catchpoint: A New Era of Self-Healing Operations<\/a>: Overview of how LogicMonitor and Catchpoint combine infrastructure intelligence with internet performance visibility to power connected digital operations.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/blog\/edwin-ai-catchpoint-internet-visibility-autonomous-it\">Closing the Internet Gap to Enable Autonomous IT with Edwin AI and Catchpoint<\/a>: Explores how Catchpoint&rsquo;s internet delivery path visibility, including BGP, CDN, and DNS monitoring, integrates with Edwin AI to close observability blind spots.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/blog\/autonomous-operations-without-blind-spots\">Autonomous IT Without Blind Spots<\/a>: Explains how the Catchpoint integration addresses the critical gap between infrastructure monitoring and end-user experience in modern observability strategies.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/elevate\/2025-supercharge-your-incident-response-with-edwin-ai\">Supercharge Your Incident Response with Edwin AI<\/a>: On-demand session covering how Edwin AI reduces alert noise by up to 90% through intelligent event correlation and accelerates MTTR with automated root cause analysis.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/blog\/logs-based-root-cause-analysis-edwin-ai\">Warum beweisgest\u00fctzte RCA bei Edwin AI mit Protokollen beginnt<\/a>: Examines how Edwin AI combines log data with alert context to ground root cause analysis in real system evidence rather than plausible explanations.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/de\/internet-performance-monitoring\">Internet Performance Monitoring (IPM) by Catchpoint<\/a>: Product page covering Catchpoint&rsquo;s synthetic monitoring, endpoint monitoring, and real user monitoring capabilities across the full internet stack.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/blog\/better-together-logicmonitor-catchpoint-self-healing-enterprise\">Gemeinsam besser: Der Aufbau des selbstheilenden Unternehmens<\/a>: Foundational post on how LogicMonitor and Catchpoint unite infrastructure intelligence, internet performance visibility, and AI-powered insight into a single operational platform.<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>Sichtbarkeit sagt Ihnen, dass etwas kaputt gegangen ist. Kontrolle sagt Ihnen, warum, wen es betrifft und was als N\u00e4chstes zu tun ist. Sehen Sie, wie LogicMonitor, Catchpoint und Edwin AI diese L\u00fccke 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Sie Ihr MSP: Von reaktiver IT zu proaktiver Sicherung des digitalen Erlebnisses"},"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        Der schnelle \u00dcberblick      <\/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>Internet Performance Monitoring (IPM) is essential for MSPs to move from reactive support to proactive experience assurance.<\/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>Internal metrics like server CPU and LAN latency don&rsquo;t show you what&rsquo;s happening in the last mile. ISPs, wireless carriers, BGP routing, CDNs, DNS, SSL, and dozens of third-party integrations sit between your infrastructure and the end user. Any one of them can cause an outage even when your core stack looks healthy<\/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 via Catchpoint covers the full picture. LogicMonitor provides inside-out visibility across infrastructure, while Catchpoint IPM adds the outside-in layer, so MSPs can tell clients exactly what&rsquo;s broken and whose problem it is<\/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>MSPs that can identify exactly where a SaaS or SASE provider is underperforming have something concrete to bring to vendor SLA conversations. That&rsquo;s a different kind of relationship than finger-pointing<\/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>Few MSPs offer Internet Performance Monitoring today. Adding it creates a higher-margin service tier, stronger SLA capabilities, and a credible path into larger enterprise accounts<\/p>\n                  <\/span>\n                              <\/div>\n            <\/li>\n                  <\/ul>\n      \n      \n            <\/div>\n<\/div><p>Green lights on your internal dashboard don&rsquo;t mean users are having a good experience. That was the central tension in this conversation between LogicMonitor RVP of Managed Services, Daniel Gad, and Catchpoint Field CTO, Gerardo Dada, and it&rsquo;s a problem most MSPs haven&rsquo;t fully solved.<\/p><p>The discussion covered what it actually takes to monitor the full path between a user and an application, why traditional infrastructure tools miss most of it, and how MSPs can use that blind spot as a service differentiator rather than a liability.<\/p><h2 class=\"wp-block-heading\" id=\"h-what-experts-discussed\">Was Experten diskutierten<\/h2><h3 class=\"wp-block-heading\" id=\"h-why-the-internet-is-now-the-application-layer\">Why the internet is now the application layer<\/h3><p>Almost every business process now runs across a globally distributed network of APIs, cloud services, and third-party integrations. Dada used a restaurant as an example with cloud-based POS, payment networks, and digital menus, to make the point that monitoring individual hardware devices tells you almost nothing about whether any of that is actually working for the people depending on it.<\/p><h3 class=\"wp-block-heading\" id=\"h-the-blind-spot-between-inside-out-and-outside-in-monitoring\">The blind spot between inside-out and outside-in monitoring<\/h3><p>Traditional observability tools are built to monitor what you control: your network, your data center, your cloud infrastructure. Dada discussed what they&rsquo;re not built to do: measure what a user in a different city, on a regional ISP, actually experiences. <a href=\"https:\/\/www.logicmonitor.com\/de\/internet-performance-monitoring\">Internet Performance Monitoring<\/a> fills that blind spot by testing from the user&rsquo;s vantage point, not the infrastructure owner&rsquo;s.<\/p><h3 class=\"wp-block-heading\" id=\"h-mapping-the-stack-nobody-monitors\">Mapping the stack nobody monitors<\/h3><p>Gad and Dada kept returning to how much sits between a user&rsquo;s device and an application&rsquo;s code, DNS, SSL certificates, BGP routing, CDNs, and how rarely any of it gets monitored until something breaks. They walked through tools like <a href=\"https:\/\/www.catchpoint.com\/internet-stack-map\">Internet Stack Map<\/a> and AI-driven Experience Scores as ways to visualize those dependencies and pinpoint root causes without wasting time investigating systems that are working fine.<\/p><h3 class=\"wp-block-heading\" id=\"h-from-vendor-disputes-to-accountable-slas\">From vendor disputes to accountable SLAs<\/h3><p>Dada focused on a practical shift: instead of getting pulled into vendor finger-pointing when a third-party service underperforms, MSPs with objective telemetry can identify exactly where the problem is. That changes the dynamic with vendors, enables more accurate SLA tracking, and gives MSPs a credible basis for routing optimization decisions.<\/p><h3 class=\"wp-block-heading\" id=\"h-what-msps-should-take-from-this\">What MSPs should take from this<\/h3><p><strong>APM node coverage is narrower than most teams assume. <\/strong>Dada pointed out that traditional APM tools typically test from nodes inside major cloud hyperscalers, which doesn&rsquo;t reflect what a user on a local wireless carrier or regional ISP actually sees. Useful Internet Performance Monitoring requires thousands of diverse global nodes, not a handful of well-connected ones.<\/p><p><strong>One failing script can take down an entire site. <\/strong>The average enterprise website depends on dozens of external services, image delivery, tag managers, analytics. Dada&rsquo;s point was that real-time visibility into those dependencies means you can identify and disable the problem quickly, rather than spending an incident window figuring out what broke.<\/p><p><strong>Catching problems before users do is the whole point.<\/strong> Dada put it plainly: &ldquo;If you&rsquo;re waiting for the customers to show up at the bank and something&rsquo;s broken and then they have to call IT, you&rsquo;re being very reactive. LogicMonitor tests all the time so that if something happens at four o&rsquo;clock in the morning, you get an alert, and ideally, you might be able to avert the problem and solve it before the customer finds out.&rdquo;<\/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        Sehen Sie sich das On-Demand-Webinar an      <\/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>See how MSPs are adding Internet Performance Monitoring to their service offering and turning proactive experience assurance into a competitive advantage.<\/p>\n      <\/div>\n    \n          \n      \n              <div>\n            <a href=\"https:\/\/www.logicmonitor.com\/resources\/webinar-msp-proactive-digital-experience-assurance-ipm\" class=\"btn btn-link\" target=\"_self\">\n        Jetzt ansehen          <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><h2 class=\"wp-block-heading\" id=\"h-recommended-reading-and-webinars\">Empfohlene Lekt\u00fcre und Webinare<\/h2><ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.logicmonitor.com\/blog\/edwin-ai-catchpoint-internet-visibility-autonomous-it\">Schlie\u00dfung der Internetl\u00fccke zur Erm\u00f6glichung von Autonomous IT mit Edwin AI + Catchpoint<\/a>: Explains how Edwin AI and Catchpoint combine infrastructure, application, and Internet telemetry in a single platform, and what changes operationally when the AI layer can finally see the full delivery path.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/blog\/autonomous-operations-without-blind-spots\">Autonomous IT Without Blind Spots<\/a>: Covers how LogicMonitor addresses the visibility limitations that constrain most AI-powered monitoring tools, relevant context for MSPs evaluating what full-stack observability actually means in practice.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/blog\/reduce-mttr-with-ai\">Wie man die MTTR mit AI reduziert<\/a>: &ldquo;Covers how AI helps operations teams detect issues earlier and reach root cause faster, directly relevant to the proactive monitoring case made in this session.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/resources\/on-demand-webinar-how-to-build-a-proactive-and-predictive-monitoring-approach\">How to build a proactive and predictive monitoring approach<\/a>: How an AIOps early warning system can shift teams from minimizing outages to avoiding them altogether, directly relevant to the proactive monitoring case made in this session.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/resources\/navigating-observability-challenges-a-fireside-chat-with-451-research\">Navigating observability challenges<\/a>: A fireside chat with 451 Research &mdash; 451 Research analyst Mike Fratto and LogicMonitor&rsquo;s Ben Radke discuss unified monitoring with real-world examples of organizations that solved fragmented visibility across hybrid and multi-cloud environments.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/resources\/on-demand-webinar-hybrid-cloud-clarity-powered-by-ai-discussion-and-demo-with-logicmonitor-and-aws\">KI-gest\u00fctzte Klarheit f\u00fcr Hybrid Cloud<\/a>: LogicMonitor and AWS walk through unified visibility across on-premises and cloud environments, with AI-driven alert prioritization.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.logicmonitor.com\/resources\/best-practices-for-effective-it-alerting\">Best Practices f\u00fcr effektives IT-Alerting<\/a>: Practical guidance on alert routing, threshold configuration, and keeping signal-to-noise ratios manageable.<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>Warum MSPs, die \u00fcber die Firewall hinausblicken, gr\u00f6\u00dfere Kunden gewinnen, Eskalationen reduzieren und eine st\u00e4rkere Argumentation f\u00fcr den Ausbau ihres Dienstleistungsangebots aufbauen.<\/p>","protected":false},"author":14,"featured_media":610987,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"unicorn_plugin_options_block_body_class":"","footnotes":""},"categories":[1],"tags":[],"industry":[6790],"language":[7],"role":[6787],"lm_search_queries":[],"lm_strategic_tags":[7381,7437,7391,7392,7372,7439,7470,7271,7394,7450],"topic":[6774],"class_list":["post-610986","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","industry-all","language-english","role-partner","lm_strategic_tags-alerts","lm_strategic_tags-automated-discovery","lm_strategic_tags-event-intelligence","lm_strategic_tags-gen-ai-agent","lm_strategic_tags-role-based-access-control","lm_strategic_tags-saas","lm_strategic_tags-sd-wan","lm_strategic_tags-servicenow","lm_strategic_tags-slack","lm_strategic_tags-synthetics","topic-digital-experience"],"acf":{"is_global_bar_disabled":false,"is_global_bar_overriden":false,"page_language":"english","translated_pages":"","reviewers":false,"is_search_excluded":false,"is_global_form_disabled":false,"is_global_form_override":false,"component_layouts":false,"related_resources":false,"updated_date":"","author_section_checkbox":false,"reviewer_name":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.9 (Yoast SEO v27.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Elevate Your MSP: From Reactive IT to Proactive Digital Experience Assurance | LogicMonitor Elevate Your MSP: From Reactive IT to Proactive Digital Experience Assurance | LogicMonitor<\/title>\n<meta name=\"description\" content=\"When dashboards show green and users are still complaining, the problem usually lives outside the firewall. 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