1. Determine Test Metrics: Identify the metrics to be tested, such as acceptable response time or error rate.
Example: Defining a maximum acceptable response time of 2 seconds for any user request or 1 second for a specific request
2. Decide on Testing Scenarios: Define the scenarios to be tested, like an e-commerce checkout flow.
Example: Creating scenarios for Sales order entry, purchase order entry, general ledger inquiry, and payroll time entry etc.
3. Choose a Testing Platform: Select a suitable open-source/commercial solution, depends on your specific requirements
Example: Using JMeter to simulate user behavior and measure system performance under different load conditions.
4. Configure the Test Script: Build and customize the test script, simulating the expected load and scenarios.
Example: Writing a script in WebLOAD to simulate 1,000 users browsing and purchasing products simultaneously.
5. Run the Test: Execute the tests and monitor the results.
Example: Running the load test script during non-peak hours to minimize disruption.
6. Analyze Results: Identify bottlenecks and performance issues through detailed reports.
Example: Reviewing the test results to find that response times degrade significantly under load, indicating a need for optimization. there are two phases here, did we meet requirements? What is the data telling me about where to look for the problem?
7. Optimize and Retest: Address any issues and retest to ensure performance requirements are met.
Example: Optimizing database queries and running the test again to verify improvements, measurable objectives, like page time, are essential