How do you design a performance testing plan for your app?

Here's a comprehensive guide to designing a performance testing plan: Define Goals and Objectives: Define clear objectives that align with your application's requirements and user expectations. Create Test Scenarios: Consider different scenarios such as normal usage, peak usage, and stress conditions. Identify key user workflows and transactions to simulate during testing. Define Test Environment: Set up a test environment that closely resembles the production environment in terms of hardware, software, network configuration, and data volume. Design Test Scripts: Develop test scripts to automate the execution of test scenarios.

Keep few point in mind -> perf objectives -> it's scope -> test approach -> test schedule -> acceptance criteria -> deliverables -> entry nd exit criteria -> risk, issues and dependencies

1) Identify the performance goals/objectives either functional or non-functional from the user perspective. 2) Determine the scope and environment of the application, including critical user scenarios, hardware, software and network configurations. 3) Choose performance metrics such as response time, throughput, memory disk, I/O etc. 4) Design the test scenarios and select testing tools based on your requirements.

Designing a performance testing plan for your app involves several key steps. Begin by identifying the performance metrics relevant to your application, such as response time, throughput, and resource utilization. Define realistic performance goals based on user expectations and business requirements. Determine the scope of testing, including the types of tests to be conducted (e.g., load, stress, endurance) and the target environments. Develop realistic scenarios and scripts that mimic real-world usage patterns. Establish a testing environment that closely resembles production conditions. Execute tests systematically, collect and analyze performance data, and identify bottlenecks or areas for optimization.

Goals & Scope: Define what to test (response times, user load) and focus areas (key features, user journeys). User Simulation: Craft realistic user scenarios (logins, purchases) using tools to create virtual users. Benchmarks: Set acceptable response times, throughput, and resource usage levels. Pick Tools: Choose tools (JMeter, LoadRunner) to generate load, monitor metrics, and analyze results. Mirror Production: Set up a test environment that closely resembles your production system for realistic testing. Test & Analyze: Run tests, identify bottlenecks (slowness, errors), and optimize app code based on results. Refine & Repeat: Continuously iterate by adjusting tests, benchmarks, and code to ensure optimal performance.

Key topics to consider while designing performance test plan 1. Identify the test environment. 2. Select the appropriate/suitable Performance Test tool. 3. Define Performance Metrics( Expected response time, resource utilisation, throughput, test data) 4. Identify the scenarios want to simulate during testing, peak load, normal usage, number of concurrent users, data volumes. 5. Design the tests for each scenarios. 6. Setup the test environment in terms of hardware, software and network configurations. 7. Execute the tests and analyse the results. 8. Update the test design based on the test results, and redo the test to fulfil the marked expectations.

Performance test planning generates a performance test plan document which contains following items: 1) Test Executor 2) Environment Details 3) Execution Date 4) Monitoring tools 5) Load Generator Details 6) Dependencies Out of above, the most important and critical step is setting up the environment for performance testing as performance test environment is separate from dev, QA and staging as you will be requiring production like servers to stimulate the production 3x behaviour. So one must need the complete hardware/software resources available for test run.

Before conducting the tests one must sanity test his/her application build that application is functionally stable. Then separate env. should be solely available for the test runs. Database, application and any other server involved, resources utilisation should be monitored before during and after the test run to identify any memory/connection/thread leakages which drastically impact the application performance.

Analyze response times. Check for error rates. Evaluate throughput. Review resource utilization. Assess scalability. Identify bottlenecks. Compare against benchmarks. Consider user experience feedback. Determine system stability. Recommend optimizations.

Present the findings and conclusions derived from performance testing, including key metrics, areas of improvement, and any identified issues or bottlenecks.

Define clear objectives and success criteria based on your app's requirements and user expectations. Identify critical scenarios to test, including user interactions and backend processes, ensuring a mix of light and heavy usage patterns. Choose appropriate performance testing tools that align with your app's technology stack and testing needs. Schedule tests during development and after significant changes, including load, stress, and scalability tests, to uncover different types of performance issues. Analyze test results to identify bottlenecks and areas for optimization. Continuously refine your testing plan based on findings and evolving app features to maintain and improve performance standards.