What are the best practices for conducting performance and stress testing?

1 Define the objectives and scope

Before you start any testing activity, you need to have a clear understanding of what you want to achieve and what you want to measure. You should define the objectives and scope of your performance and stress testing based on the requirements, expectations, and constraints of your stakeholders, users, and environment. For example, you might want to test how your system responds to different levels of load, concurrency, data volume, or network conditions. You should also specify the metrics and criteria that will indicate the success or failure of your testing, such as response time, throughput, availability, or error rate.

2 Plan and design the test cases

Once you have determined the objectives and scope of your testing, it is important to plan and design test cases that will simulate realistic scenarios and conditions. These test cases should consider the type and frequency of user actions, the distribution of load across different user profiles, locations, devices, and browsers, the duration and ramp-up of the load, the dependencies and interactions with other systems, services, or resources, and the expected and acceptable outcomes of your system under different load conditions.

3 Choose and configure the tools and resources

When executing test cases, it's important to choose and configure the right tools and resources that will generate, monitor, and analyze the load on your system. These should be compatible with your system architecture, technology, and environment, and be able to handle the scale and complexity of your testing. Additionally, make sure you have enough resources to create the load and isolate the test environment from the production environment. Possible tools and resources include load generators such as JMeter, LoadRunner, or Gatling; load balancers like NGINX, HAProxy, or AWS Elastic Load Balancing; performance monitors like PerfMon, Prometheus, or New Relic; and performance analyzers like Grafana, Kibana, or LoadRunner Analysis.

4 Execute and monitor the tests

After you have chosen and configured the tools and resources, you are ready to execute and monitor the tests. You should follow the test plan and schedule that you have prepared, and run the tests in a controlled and consistent manner. You should also monitor the tests in real-time and check the performance metrics and logs of your system and your load generators. You should look for any signs of degradation, failure, or abnormality in your system behavior, such as slow response, high latency, low throughput, or high error rate. You should also document the test results and any issues or incidents that occur during the testing.

5 Analyze and report the results

After you have executed and monitored the tests, you need to analyze and report the results. You should use the performance analyzers and other tools to aggregate, filter, and compare the performance data from your system and your load generators. You should also use the criteria and metrics that you have defined to evaluate the performance and stress levels of your system under different load conditions. You should identify the root causes and impacts of any performance problems or errors that you have encountered, and suggest possible solutions or improvements. You should also prepare a clear and concise report that summarizes the objectives, scope, methods, results, and recommendations of your testing, and share it with your stakeholders and users.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?