The quick download:
Endpoint monitoring is the foundation of digital experience management in a distributed workforce.
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Remote and hybrid work has made the traditional perimeter irrelevant. Employees access business applications across dozens of device, network, and location combinations, and each introduces variables that affect the quality of the experience.
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A complete endpoint monitoring solution covers six core capabilities: application performance insight, device health, network monitoring, SLA analysis, user behavior analytics, and self-remediation.
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The biggest efficiency gain comes from pairing proactive alerting with user self-remediation, reducing IT ticket volume and accelerating resolution for problems users can fix themselves.
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Evaluate your current monitoring stack against all six components and identify which gaps leave your teams blind to user experience issues.
Endpoint monitoring
Endpoint monitoring assesses the quality of the user experience across desktops and mobile devices (also referred to as endpoints) to proactively uncover performance and availability issues. Depending on the context, endpoint monitoring may refer to the following:
- Security monitoring of end-user devices
- Monitoring of application programming interface (API) endpoints
- Digital experience monitoring (DEM) of applications used by employees and end-users
Endpoint monitoring in the security context involves analyzing end-user devices to identify misconfiguration or unauthorized network access. Powered by machine learning techniques such as anomaly detection, the services categorized under this definition of endpoint monitoring focus on defending against malicious activity.
API endpoint monitoring refers to monitoring an application programming interface to gain insight into the availability and performance of API calls. Since modern applications are built from microservices that access backend data via APIs, monitoring API endpoints has become the most reliable way to abstract performance monitoring of application infrastructure. We’ve devoted a separate article to explaining the various techniques used in API monitoring.
This article focuses on the third category referenced above, which defines endpoint monitoring in the context of digital experience monitoring (DEM). In this context, an effective endpoint monitoring solution must cover all aspects of the end-user experience to assist in troubleshooting device, network, and application issues. It should enable proactive monitoring of user experiences across applications from any device.
A complete endpoint monitoring solution covers six core capabilities:
| Component | What it is | Why it’s Important |
|---|---|---|
| Application Performance Insight | Visibility into users’ underlying application performance experience: latency, errors, network traffic, and availability | Pinpoints performance issues affecting the user experience across applications |
| Device Performance Monitoring | Visibility into the health and performance of user devices. These are commonly referred to as endpoints (e.g., work laptops) | Similar to application performance insight, this functionality shortens problem resolution time |
| Network Monitoring | Oversees active endpoints on the network to address VPN issues, network outages, device connectivity, and low network bandwidth | Provides an easy way to organize telemetry data and identify network bottlenecks for fast resolution of networking problems |
| Third-Party Service Level Agreements (SLA) Analysis | Analyzes SLA agreements to hold vendors accountable to optimal performance | Identifies problems in third-party platforms affecting the end-user experience |
| User Behavior Analytics | Provides insight into employee work trends: most-used applications, top device preferences, etc. | Visibility into application usage helps focus IT resources on addressing the issues with the most impact |
| Self-Remediation Capabilities | Gives employees visibility into intermittent network issues along with recommendations for remediation (i.e., troubleshooting steps) | Avoids wasting IT resources on problems that can be mitigated without additional support intervention |
The need for endpoint monitoring
A 2020 OwlLabs survey found that 70% of full-time U.S. workers were working from home at the time, and 77% wanted the option to continue working from home, a shift that has since become permanent for many organizations.
The workplace is now location-independent. Employees interact with business applications through systems outside the company’s purview.
What has fundamentally changed is that employees can go to work by logging onto a Monday morning meeting via a mobile phone while taking the subway to the office, completing their latest assignments on their employee laptops during their lunch break at a coffee shop, and ending their day by sending an email from a tablet while in a conference room at the office.
The simplicity of accessing applications across a single enterprise network has expanded to encompass a mix of public and private networks, often connected through a virtual private network (VPN). When an employee connects online via one of their devices, commonly referred to as an endpoint, many factors can affect the quality of the user experience.
This doesn’t just apply to employees: Any end-user accessing your business applications may be using one of dozens of permutations of access devices and network access points. Monitoring the quality of the modern user experience requires extending your monitoring strategy to include the endpoints themselves, a discipline known as endpoint monitoring.
Components of endpoint monitoring
An endpoint monitoring solution should be equipped to collect telemetry data from a user’s device, analyze it, and provide actionable metrics to resolve issues. LogicMonitor’s platform is built around these requirements, connecting endpoint telemetry with infrastructure metrics, logs, and traces so teams can correlate user experience issues with their underlying causes.
Overall user experience
A comprehensive endpoint monitoring platform analyzes user experience, endpoint (or device) performance, network performance, and application performance. LogicMonitor’s platform offers a dashboard view that provides a quantitative score for each of these metrics, with the ability to drill down and filter events. The experience score measures the overall user experience and is computed by taking the average of the endpoint (device), network, and application scores, as explained in the section below.

Device performance monitoring
The endpoint score is determined by factoring in CPU and memory usage, as well as WiFi strength. For example, if the user is accessing the company via VPN from a local coffee shop, the WiFi strength might be lower than in the office.
Device issues can be difficult for users to address on their own and may require assistance from an IT organization. For example, unusual memory consumption on a user’s laptop can indicate that closing unused applications could improve performance, but it may not be practical for a user to remedy a poor network connection or application issues.
Comparing data from a user’s machine against a historical baseline and a threshold helps detect issues early. The ability to triage problems using empirical data helps many users become more self-sufficient in resolving simple issues and reducing their dependence on IT organizations.
Network monitoring
The network score is computed by factoring in the round-trip time (RTT) and packet-loss metrics from ping tests and traceroutes. Latency and packet loss are also considered part of the network score.
LogicMonitor’s network monitoring helps you organize all your network devices by allowing you to assign human-readable names to their underlying IP addresses. This includes firewalls, proxies, servers, gateways, and other elements of network infrastructure. This improves device detection by allowing you to quickly identify known and unknown devices on your network. For example, from within the platform, you can add a range of IP addresses that should belong to a particular application and label them accordingly.
Additionally, you can set up and configure alerts that are based on metrics and a threshold value or range. You can specify whether the alert should be triggered by location data and whether it should be endpoint- or application-specific. For example, an alert can be configured to go off when a user experiences poor performance across three or more of their open applications. This can notify a support team with critical metadata about what happened, enabling you to diagnose problems quickly (company outage or isolated incident) and act on them in a timely fashion.
Application performance insight
The application score is calculated using Real-User Monitoring (RUM) data. Specifically, it’s scored based on how quickly a view becomes “visually complete” or the point at which all content has been fully loaded and is visible to users in the browser. This is a critical metric for identifying applications that aren’t behaving as expected.
Applications on a user’s machine generate metrics that show how well they’re performing. How well an application performs correlates with the number of errors, latency, and availability issues it experiences.
Collecting this data and viewing it on a dashboard facilitates differentiating user-centric issues from org-wide issues at the application level. When endpoint metrics are combined with infrastructure monitoring data, network path analysis, and traces, teams can pinpoint whether a performance issue originates on the device, in the network, or deeper in the application stack. Determining the course of action for troubleshooting is streamlined by enabling support engineers to detect and resolve issues rapidly.
User behavior analytics
Collecting and analyzing application usage data across the enterprise is required to optimize the user experience, but it also unlocks additional benefits. Companies can use this information to prioritize their application performance monitoring efforts by focusing on the most popular applications. They can also identify and avoid using applications with overlapping functionality, saving on licensing costs.
LogicMonitor’s endpoint monitoring enables customers to analyze how often and how much applications are used by employees. For example, take a popular application like Slack. Although Slack offers collaboration features similar to Microsoft Teams, some companies use both. This duplication of functionality may happen because the company’s engineering team adopted Slack before the rest of the company selected Teams as the standard corporate communication platform. LogicMonitor’s endpoint monitoring enables enterprises to pinpoint duplication, measure the volume of traffic on each competing application, and save money on licensing costs.
Application usage data can be collected from many popular applications from providers such as Atlassian, Google, Amazon AWS, Microsoft, and Slack.
Conclusion
Endpoint monitoring assesses the quality and performance of applications from the perspectives of end users and employees. When public networks and third-party systems sit between users and applications, visibility into the endpoints themselves is what connects infrastructure data to real user experience. Combined with infrastructure monitoring, Internet performance monitoring, and AI-assisted root cause analysis, endpoint monitoring helps teams trace issues from the user’s device through the Internet path to the underlying infrastructure, reducing blind spots across the full delivery chain.
Gain full visibility into endpoint performance, from device health to application experience.
Endpoint monitoring works best when device, network, and application data come together with infrastructure metrics, Internet path visibility, and AI-assisted correlation in one platform. LogicMonitor connects these layers so your team can trace issues from the end user to the underlying cause and resolve them before users feel the impact.
FAQs
What’s the difference between endpoint monitoring and endpoint security?
Endpoint monitoring in the digital experience context focuses on the performance and availability of applications as experienced from user devices. Endpoint security focuses on defending those devices against unauthorized access and malicious activity. Both disciplines use the term “endpoint,” but they address different problems.
Which metrics matter most for endpoint monitoring?
The core metrics are CPU usage, memory consumption, WiFi signal strength, round-trip time (RTT), packet loss, and application visual completeness. Together, these produce device, network, and application scores that represent the overall user experience.
How does endpoint monitoring help reduce IT support tickets?
By giving users visibility into common issues (such as weak WiFi or high memory usage) along with self-remediation steps, endpoint monitoring reduces the volume of tickets requiring IT intervention. Support teams can focus on complex, org-wide problems instead of one-off user issues.
Can endpoint monitoring track application usage across the organization?
Yes. User behavior analytics within endpoint monitoring captures which applications employees use, how often, and how much. This helps IT teams prioritize monitoring efforts, identify redundant tools, and reduce licensing costs.




