How do you handle performance issues and bottlenecks that emerge during endurance testing?

As part of any testing in an organization I would start working on Requirement Gathering and Performance Test plan document to define the objectives of the endurance test, including the goals, scope, and success criteria. Determining what aspects of the system's performance and stability needs to be evaluated during the endurance test. Identifying critical user workflows or business processes that are commonly performed. Prioritizing workflows based on their importance to users, impact on business operations, and potential performance implications.

Many teams don't realize the importance of software endurance tests until they encounter some major memory issues in production. In such situations, it is recommended to try to replicate the issue in performance test environment with transactions and user load [exact or scaled down based on environment configuration] for which issue was observed. We used JMeter for endurance testing, Splunk and AppDynamics for monitoring, jcmd command to capture heap dumps of java application and YourKit profiler for analyzing memory leak issues. Open-source tools like Eclipse MAT or IBM HeapAnalyzer are also helpful for getting more insights. Involvement of development team is really helpful in these activities.

Monitor system metrics, analyze performance data, identify bottlenecks, optimize code and configurations, and retest to ensure improvements in endurance and scalability.

During endurance testing, it is common to encounter performance issues and bottlenecks that can affect the system's overall performance. Here are some steps you can take to handle these issues: Identify the source of the problem: The first step is to identify the source of the performance issue or bottleneck. This can involve analyzing performance metrics, logs, and other system data to pinpoint the cause of the problem. Replicate the issue: Once you have identified the source of the problem, you should try to replicate it in a controlled testing environment to better understand its impact on the system's performance. Evaluate potential solutions: After replicating the issue, you should evaluate potential solutions to address the problem.

In addition I’ve seen a lot of value in having the customer periodically run test cases because sometimes the human touch builds confidence that a stack of graphs cannot

Simply conducting performance testing is insufficient; we must also apply engineering principles by thoroughly analyzing the results. For endurance testing, this entails examining various metrics such as CPU usage, memory leaks, high response times, connection leaks, thread leaks, database utilization, hits per second, duplicate calls, bad SQL queries, long-running queries, server unresponsiveness over time, and specific error types. By analyzing these metrics, we can pinpoint application bottlenecks and devise solutions to address them, a process that can be carried out both during and after endurance tests

Analyze performance metrics to identify anomalies, trends, or patterns that may indicate performance bottlenecks. I would look for correlations between different metrics and performance issues to pinpoint potential root causes. Isolating specific components or subsystems of the system to narrow down the scope of investigation. Test each component independently to determine whether the performance issue is localized to a specific part of the system.

You should also use the technical expertise that's available to you to help isolate root cause. DBA's, Technical Architects, Network engineers, Developers etc can all help.

After implementing solutions or fixes to address performance issues identified during an endurance test, it's essential to test and validate these changes to ensure they effectively improve system performance and stability. Prepare test environment with the new fixes, define test scenarios, execute tests and monitor performance metrics. Make sure the required objectives and goals are met with the new fixes after testing.

Post fix: Check the memory utilization,weather its increasing over a period of time&not coming down .Monitor the Garbage collection cycle , once it happens weather memory is coming down .Check from heap side which area is increasing ( young & old generation ) .Take a heap dump , compare it with the dump when fix was not implemented .You can use MAT analyzer check the object taking highest memory , check the dominator tree , shallow & retained heap for objects , leak suspects .Once you have validated performing above analysis , confirmed that issue is fixed .Post that again execute your test suite compare it with old results check KPI's - CPU utilization , response time etc to validate that the fix provided has not introduced any regression