What is APM?

• Application Performance Monitoring (APM) Definition

  Application Performance Monitoring (APM) Definition

  Application performance monitoring (APM) is a continuous process of monitoring the availability of mission-critical applications. This includes tracking performance metrics and trends to proactively identify and resolve performance bottlenecks and provide a seamless end-user experience.
• Importance of APM

  Importance of APM

  In today’s hyper-connected digital world, enterprises depend on many mission-critical applications to create value. Rising end-user expectations for high availability, real-time response management, and consistent application performance are rapidly becoming critical for business success. Though business applications may appear simple to use on the front end, at the back end, these applications are highly complex, as they have millions of lines of code and are hosted across hybrid environments.

  A proactive approach to application performance monitoring is necessary to manage and control factors impacting the performance of an application. It helps you detect and fix coding errors or software bugs, hosting and network performance, and database slowdowns, among other factors.

  Here are some key reasons why APM is highly critical for modern businesses.

  • Gain More Visibility Into App Performance: APM ensures a unified view across the complete application stack to provide comprehensive transparency. Different functional teams can collaborate better and manage applications across highly distributed, multi-cloud environments with clear visibility. It helps streamline front-end monitoring, back-end monitoring, and IT infrastructure monitoring to overcome any potential operational bottlenecks or service disruptions.
  • Ensure Business Continuity: Application unavailability or unplanned downtime hit the bottom line, as enterprises run the risk of losing business. With a comprehensive APM approach, enterprises can get real-time insights to proactively respond to potential issues and restore applications to a normal state. Real-time response helps businesses become more agile and resilient during unprecedented scenarios.
  • Troubleshoot Issues in Real Time: Application performance monitoring helps IT teams deep-dive into issues and quickly analyze the root cause of a specific performance issue. Real-time tracking of performance metrics helps in faster anomaly detection, and instant root cause analysis reduces mean time to resolution (MTTR). Instant root cause discovery helps address problems before they impact the end-user experience.
  • Enhance End-User Experience: By tracking metrics such as load time, response time, and downtime, APM helps monitor the end-user experience throughout their digital journey. An APM approach leverages real user monitoring to trace an actual user's experience on the system in real time or employs synthetic monitoring to simulate user transactions and test in different environments. This comprehensive monitoring helps address end-user issues faster and keep them using the application while improving user satisfaction.
• APM capabilities and key metrics

  APM capabilities and key metrics

  APM capabilities typically fall into three key segments:

  1. Digital Experience Monitoring (DEM): A monitoring strategy to optimize applications and streamline digital touchpoints to deliver a seamless user experience.
  2. Application Discovery, Tracing, and Diagnostics: A comprehensive process for discovering application topology, tracing user requests as they navigate applications, and analyzing performance issues.
  3. Application Analytics: Performing real-time analysis and reporting to gain insights into application performance and customer experience should be a continuous process. It helps provide root cause analysis whenever there’s a performance issue and helps businesses prevent the problem from occurring again.

  Organizations are turning to APM to ensure each business application runs seamlessly by identifying issues hampering the end-user experience, correlating data to see a bigger picture, and troubleshooting issues instantly. Because of this, it’s essential to understand how to use the following data types to optimize application performance and minimize downtime:

  • Logs: Applications and related infrastructure usually generate default log messages, which come in handy while identifying errors, resource constraints, or timeouts from a database. Using log data helps different teams drill down and gain context while resolving issues. 
  • Traces: Transaction traces accommodate detailed information related to particular system requests or end-user requests. They allow you to map the user’s journey from the front end to the back end to identify the exact line of code or database query hindering application performance.
  • End-User Experience KPI Metrics: Drastically changing user expectations for a smooth digital journey and better service quality require application-dependent businesses to implement dynamic end-user experience monitoring. It’s becoming a critical success factor for companies. Here’s a list of some key end-user experience metrics:
    • User Satisfaction/Apdex Scores: This is a measure of a user’s general level of satisfaction while using an application.
    • Average Response Time: This is the amount of time an application takes to return a request to a user.
    • Error Rate: This is the number of times an error occurs in a day.
    • Request Rate: This is a measure of the traffic an application receives. It helps monitor the impact of increases/decreases in traffic on the success of an application.
    • Application Availability: This is a measure of application uptime to check the overall time an app remains online and available.
  • Infrastructure KPI Metrics: Enterprises also need to monitor their infrastructure performance to achieve the business goal of delivering superior digital service to end users. Below are a few key infrastructure metrics businesses need to monitor:
    • CPU Utilization: This is a measure of CPU usage on a server. It’s either calculated per server or as an aggregate across all the individually deployed instances.
    • Memory Utilization: This is a measure of memory usage across various applications.
    • Queue Length: This is an essential metric for more complex data pipelines to monitor backpressure, which may cause a slowdown or data loss.
• APM tools

  APM tools

  Though most businesses and IT services companies monitor the performance of applications, they often struggle to get a unified view of the complete application stack due to the underlying traditional fragmented approach to application performance management. Such teams don’t have end-to-end visibility of the environment and can’t correlate events for effective analysis and faster issue resolution.

  Modern APM software ensures complete observability, breaks down operational silos, and enables different functions to collaborate, correlate, and analyze data using artificial intelligence and machine learning techniques to resolve performance issues in real time. Unlike traditional monitoring tools, intelligent APM tools empower companies with an integrated monitoring experience. An APM solution must provide end-to-end observability across the environment by including logs, traces, performance metrics, and end-user behavior in a single platform. A comprehensive performance monitoring solution integrates end-user experience monitoring with log and event data, metrics, and traces for in-depth visibility into applications and their resources.

  Many APM solutions are available in the market focusing on specific application monitoring needs. Organizations should choose an APM software offering the following capabilities while intelligently automating problem discovery, root cause analysis, and infrastructure monitoring to effectively mitigate issues.

  • End-User Experience Monitoring: An APM solution should track the digital experience of application users to pinpoint instances where end users experience slowness, downtime, or errors. It should combine synthetic and real user monitoring to gain complete visibility and ensure enhanced troubleshooting.
  • Transaction Profiling: An APM solution should analyze the transaction flow through each application architecture tier to uncover bottlenecks. It should also allow IT teams to easily trace business transactions through the back-end database to dig deeper, with detailed distributed waterfall traces, exception tracking, and live code profiling to better diagnose underperforming application transactions.
  • Application Code-Level Diagnostics: If transaction tracing reveals issues in the application server, it’s imperative to check whether there’s a problem in the application code. An effective APM tool helps pinpoint the exact line of code causing performance issues.