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Application performance monitoring (APM) is a process of monitoring and managing the performance and availability of software applications. APM tools are used to identify and troubleshoot issues that may be impacting the performance of an application, and to optimize the performance of an application in order to enhance user experience.
APM involves monitoring various metrics related to the application’s performance, including response time, throughput, error rate, and resource utilization. These metrics can be collected from various sources, such as the application itself, the underlying infrastructure, and external user experience monitoring tools.
APM tools provide real-time visibility into the application’s performance and allow for proactive identification and resolution of issues. They also offer features such as alerts, dashboards, and analytics to help teams quickly diagnose and resolve problems. By monitoring and optimizing application performance, APM can help organizations improve the reliability and availability of their applications, reduce downtime, and ultimately enhance user satisfaction.
This is part of an extensive series of guides about performance testing.
In this article:
Application performance monitoring is important for several reasons:
Application Performance Monitoring and Application Performance Management are related but distinct concepts in the field of software performance management.
Application Performance Monitoring is the process of monitoring and collecting data about the performance of an application in real-time, with the aim of identifying and diagnosing issues that may be affecting the application’s performance. These tools typically collect data on key performance metrics such as response time, latency, throughput, and error rates, and use this data to provide insights into how the application is performing. It focuses on the real-time monitoring and analysis of an application’s performance, with the aim of identifying and resolving issues before they impact end-users.
On the other hand, Application Performance Management is a broader concept that encompasses the entire process of managing an application’s performance, from development through to deployment and ongoing maintenance. It includes a range of activities such as performance testing, capacity planning, performance optimization, and continuous monitoring. It focuses on the overall management of an application’s performance throughout its lifecycle, with the aim of ensuring that it meets the required performance standards and user expectations.
APM works by constantly observing the performance of applications and checking whether they are behaving as expected. If the applications are not performing as expected, data is collected to identify the source of the issue. This data is then analyzed to determine the impact on the business, and the application environment is corrected to prevent similar problems from occurring in the future.
When configuring an APM platform, it is important to consider three categories of data: Metrics, Traces, and Log Files.
Although APM can provide valuable insights, monitored data and analytics may not always be sufficient to ensure adequate user experience. Performance management systems may need to combine monitoring data with automation and orchestration to bring a level of autonomy to problem remediation.
APM tools can track a variety of metrics to help assess the performance of an application. Here are some of the most commonly tracked metrics:
Response time
This metric measures how long it takes for an application to respond to a user request. It can be broken down into server response time, which is the time it takes for the server to process the request, and network latency, which is the time it takes for the request to travel across the network.
Throughput
This metric measures the amount of data that can be transferred between an application and its users or other systems over a period of time. It can help determine whether an application is able to handle the expected volume of traffic.
Error rate
This metric measures the percentage of requests that result in errors, such as server errors, client errors, or timeouts. By tracking the error rate, APM tools can help identify and resolve issues that may be impacting the user experience.
CPU utilization
This metric measures the percentage of CPU capacity being used by an application. High CPU utilization can indicate performance issues that may be affecting the application’s response time.
Memory utilization
This metric measures the amount of memory being used by an application. High memory utilization can indicate issues with memory leaks or inefficient code.
Network usage
This metric measures the amount of network bandwidth being used by an application. High network usage can indicate performance issues that may be affecting the application’s response time.
Disk usage
This metric measures the amount of disk space being used by an application. High disk usage can indicate issues with inefficient data storage or data retention policies.
Database queries
This metric measures the number of queries being executed against a database by an application. By tracking this metric, APM tools can help identify slow or inefficient queries that may be impacting performance.
Page load times
This metric measures the time it takes for a web page to load in a user’s browser. By tracking page load times, APM tools can help identify issues with slow-loading pages that may be affecting the user experience.
Transaction volume
This metric measures the number of transactions being processed by an application over a period of time. By tracking transaction volume, APM tools can help identify issues with scalability and capacity planning.
Uptime
This metric measures the amount of time an application is available and accessible to users. High uptime is critical for maintaining user satisfaction and avoiding potential revenue loss. APM tools can monitor uptime and alert teams if the application goes down or experiences issues that may impact availability.
There are several types of APM tools, including:
These tools collect metrics and other data directly from the application and its underlying infrastructure. This includes data such as server response time, network latency, CPU utilization, memory utilization, and disk usage. By collecting and analyzing this data, these tools can provide insights into an application’s performance and help identify issues that may be impacting its performance.
Application metrics-based APM Tools typically provide dashboards and visualizations that display performance data in real-time. They may also offer features such as alerting, which can notify teams if the application’s performance falls outside of acceptable ranges.
Learn more in our detailed guide to application performance metrics (coming soon)
These tools use code profiling to identify performance bottlenecks in an application’s code. Code profiling involves analyzing an application’s code execution to identify areas where performance improvements can be made.
Code profiling-based APM tools typically integrate with application development environments to help developers optimize an application’s performance. They may provide visualizations and recommendations that help identify the root cause of performance issues and suggest solutions to address them.
Advanced tools perform continuous profiling, meaning they automatically profile applications to identify performance issues and optimization opportunities. For example, Granulate’s Continuous Profiler can help you optimize application performance on an ongoing basis across any environment, at any scale.
These tools monitor network traffic to identify issues that may be impacting an application’s performance. It is typically performed by network performance monitoring tools that can analyze network traffic data to identify issues such as high latency, network congestion, and packet loss that may be affecting the application’s response time. (Learn more in our blog about network congestion control).
These tools may also offer features such as network mapping and visualization, which can help teams identify network topology and performance issues.
Learn more in our detailed guide to application performance monitoring tools (coming soon)
The dashboard is the window into an application’s performance, so it’s important to ensure that it displays the most relevant and useful information. A customized dashboard can display metrics such as response time, error rate, and user satisfaction. It’s important to select the metrics that are most important to your organization and configure the dashboard accordingly.
Alert policies can help ensure that issues are identified and addressed quickly. It’s important to configure alert policies based on the severity of the issue and the people who need to be notified. For example, a critical issue may need to be escalated to senior management, while a less severe issue may only require notification to the development team.
The end user experience is critical to the success of an application, so it’s important to factor it into APM. This can include metrics such as page load times, response times, and user satisfaction. By monitoring these metrics, teams can identify issues that may be impacting the end user experience and take corrective action.
APM tools can be complex, so it’s important to ensure that personnel are trained to work with them effectively. This can include providing training on how to configure alerts, interpret metrics, and troubleshoot issues. By ensuring that personnel are trained, organizations can ensure that APM tools are used effectively to optimize application performance.
Together with our content partners, we have authored in-depth guides on several other topics that can also be useful as you explore the world of performance testing.
Authored by Cloudinary
Authored by Cloudinary
Authored by Granulate
The First Real-Time Continuous Optimization Solution