What Is Application Performance Monitoring? How to Measure App Performance

By Staff Contributor on January 3, 2020

One of the most important functions of an IT infrastructure is to ensure apps are working properly. When a user interacts with the network, a slow application can immediately drag down their quality of experience and can have a potentially damaging impact on business productivity. Slow and unreliable applications can also hamper your productivity, cut profits, and seriously damage the quality of your brand.

Before I start, let’s clarify some definitions. Application performance monitoring is a subset of the broader field of application performance management (APM). Although the two terms address similar topics, APM offers management-specific functionalities, while monitoring tools are all about visibility and awareness. The focus here is on APM application performance monitoring and the tools to help you improve your current monitoring efforts. I also review the features of SolarWinds® Server & Application Monitor (SAM) if you’re looking for a straightforward yet comprehensive APM approach.

How Does Application Performance Monitoring Work?
How to Measure Application Performance
How Do APM Software Tools Work?
Why I Use SolarWinds SAM
What to Know About Application Performance Monitoring

How Does Application Performance Monitoring Work?

It’s no surprise application performance monitoring requires you to collect performance data from your apps. This includes user experience information, data about app interactions and dependencies, the functionality of apps within a virtual ecosystem, and other app-level information. When you’re monitoring dozens or hundreds of applications, it can be quite a task to access all that information.

In today’s highly distributed IT environment, you need to be able to monitor all apps, including virtualized apps and applications in hybrid cloud environments. Virtualized applications can be a challenge to monitor because you must have visibility into not just the application but into the virtual servers (which lie below the application layer) and a hypervisor platform (below the virtual servers).

Application performance monitoring also needs to include several additional factors. All applications rely on lower-layer components to function, so relevant metrics may include network traffic information, syslog, storage, memory, and more. You may need insight into application servers, operating systems, database servers, virtualization management tools, web servers, mail servers, and more.

When it comes to application performance monitoring, you may be trying to answer a variety of questions, including the following:

  • Is the application responding correctly, such as in a way allowing it to function?
  • Is the user experiencing only an appropriate level of latency?
  • Are all backend processes supporting applications in an optimal way?
  • What part of the application or network architecture could be causing transaction bottlenecks?
  • Is the problem in storage, user access, or connectivity? Is it the resources themselves or their configurations?
  • Are there errors in the application code?

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How to Measure Application Performance

How to Measure Application Performance

Metrics are a crucial aspect of your application performance monitoring system. It’s important to track multiple components of your system and take several different perspectives if you want to be able to accurately and quickly pinpoint the root cause of lags. This requires automated visibility, made possible through a comprehensive application monitoring software program. Although not a complete list, you should consider the following aspects for effective application monitoring:

User experience: Focusing on end-user experience provides insight into the actual impact of system issues. The application performance index, or “Apdex” score, uses an equation to calculate satisfaction, based on fast, sluggish, slow, and failed requests. Similarly, average response time and error rates are critical for understanding what your end user is actually experiencing when they use an application.

Application traffic: Understanding request rate, or traffic, can provide insight into performance. Correlate request relates with other metrics to see what happens in periods of high usage (sudden drops can also signal issues). It can help to use an application usage monitor to predict and prepare for traffic spikes possibly overwhelming servers and networks.

Physical and virtual servers: You should monitor the baseline aspects of your system your applications depend on, which means analyzing both physical and virtual servers for excessive CPU load, low storage, virtual resource allocation, and potential hardware issues. For instance, the following are some key metrics for IOPS throughput for the server, which can reveal latency and connectivity issues:

  • Logical disk average: disk queuing
  • Average and maximum IOPS write/read
  • IOPS latency write/read
  • IOPS total

Application dependencies: Understanding dependencies between parts of your system is critical for pinpointing bottlenecks. Dependencies can be revealed through comparing multiple metrics types—like status, events, and statistics—and through analyzing various components at the same time, including nodes, volumes, and applications. It can be especially useful to see timeline visualizations of your chosen elements.

Storage and resource capacity: Storage resources, like hard disks, memory, or CPU, might be the cause of a capacity shortage causing your application to malfunction. It’s useful if you can track not just current storage shortages, but also forecast and prepare for future workload management.

Caching layer metrics. Your caching layer is a storage layer which allows for quick data retrieval, in exchange for temporary data storage. Since caching uses a secondary storage location (aside from your main data bank), when your apps retrieve data they often access it through the caching layer. If your app is having difficulty retrieving data, it’s necessary to understand the time series-based performance metrics of your caching layer, and to diagnose any bottlenecks in data retrieval from your caching layer.

Load balancing metrics. Load balancers can be a helpful tool to distribute network traffic in an optimal way. Load balancers can take many different forms, from virtualized load monitors to hardware to software integrations. The idea behind a load balancer is that it deploys a diverse variety of tactics to direct traffic flow in the smoothest way possible, which can deliver a more streamlined performance for your complex network. A malfunction in the load balancer could cause a glitch traffic flow and affect your application performance.

Beyond these elements, application performance monitoring may also consider aspects like:

  • Slow SQL queries: If your database queries aren’t optimized, a lag here could slow down application functioning.
  • Transactions: Transaction monitoring helps you see and test the impact of code changes.
  • Application availability: If you’re monitoring a web app, use HTTP checks to see if your application is online and available. Ensuring uptime is part of many service level agreements, so this metric can be critical.

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How Do APM Software Tools Work?

Application performance monitoring software offers admins the information they need to catch issues, pinpoint root causes, and quickly resolve the situation. These tools are useful because they automate the process and even provide alerts on incoming data. These performance monitoring tools are typically built on some key functionalities, including the following:

Protocols. Application performance monitoring tools might use several protocols, including UDP, TCP, SNMP, and WMI to gather real-time information about managed application and infrastructure components. APM monitoring tools typically make “calls” to servers to request key data. SNMP polling data can be useful, although some of the best performance metrics are time series-based, because they offer more granular detail for everything from CPU and memory to response latency and user patterns. A successful monitoring tool will provide insight into your entire application stack across your network’s servers and app containers. 

Syslog. You can detect and diagnose performance issues using these event records. Syslog messages can be live-monitored with app monitoring software analytics tools. There are many sources of log data to help measure app performance—app servers, database servers, hypervisors, firewalls, and more. Understand the components of your systems contributing to app function and analyze their syslog data accordingly.

Templates. At first, the number of components required for app monitoring might seem overwhelming—how can I identify every single aspect of the server which might affect app usage? How can I know I’m not forgetting anything? Templates are typically designed to pull specific metrics for dozens of the most commonly used business applications. These preset templates offer comprehensive performance monitoring from a centralized control panel.

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Why I Use SolarWinds SAM

For the most comprehensive application performance monitoring, my first choice is SolarWinds Server & Application Monitor. After searching and searching for a program offering the right combination of server and application performance monitoring tools for understanding both individual system components and application dependencies, SAM was able to provide the much-needed peace of mind—and help get my time back.


With predefined application monitoring templates for over 1,200 systems and apps, SAM helps you identify which aspects of your multilayered system to monitor. Once you’ve settled on the right targets, SAM provides continuous app monitoring across your app stack, which means any problem spots can be detected and diagnosed as quickly as possible. SAM also provides out-of-the-box monitoring for multi-vendor apps which might be difficult to monitor otherwise, with the ability to track both real-time and historical metrics you can then use to set custom alerts for instant awareness into trouble spots.

No matter what application you’re running on your stack, chances are good SAM can provide seamless monitoring. But, on the chance your server is running an app SAM doesn’t know, SAM provides a painless setup for monitoring custom applications—whether they’re operating on your server or in the cloud. This allows for a high degree of flexibility in your app monitoring capabilities.


In addition to the above features, SolarWinds SAM offers a proprietary performance analysis dashboard view (PerfStack) to help you visualize app monitoring from a centralized dashboard. PerfStack includes highly useful features such as troubleshooting, real-time alerts, and automated issue reports. It can even make suggestions on your app solutions based on data-driven analytics.

The best part is you can try out SolarWinds SAM risk-free during a fully-functional, free 30-day trial to see if it is the best application performance monitoring solution for your needs.

What to Know About Application Performance Monitoring

Application performance monitoring might seem like a behemoth. First, you need to identify all the relevant parts of your multilayer system. Then, you need to continuously monitor them for potential issues (like bottlenecks and capacity shortages) capable of harming your app functionality. Then, if one of your apps is malfunctioning, you need to be able to pinpoint the source of the issue and troubleshoot your roadblock.

Clearly, app performance monitoring demands a comprehensive tool to automate the process and take the burden off IT managers. To achieve this goal, SolarWinds SAM is my definitive choice for a comprehensive and reliable app monitoring software. To keep your system in top shape, IT pros need a tool to make app monitoring as painless as possible.

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