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Performance Testing

Performance testing is a critical discipline in software engineering focused on evaluating the speed, responsiveness, stability, and scalability of applications under various workloads. It helps identify bottlenecks, ensure system reliability, and validate that performance requirements are met before production deployment.

🛠️ Types of Performance Testing​

  • Load Testing: Measures system behavior under expected user loads. Detects bottlenecks and verifies scalability.
  • Stress Testing: Evaluates system stability and error handling under extreme or breaking-point conditions.
  • Soak (Endurance) Testing: Assesses system performance and memory leaks over extended periods.
  • Spike Testing: Observes system response to sudden, sharp increases in load.
  • Scalability Testing: Determines the system’s ability to scale up (vertical/horizontal) with increased load.
  • Capacity Testing: Identifies the maximum number of users or transactions the system can handle.

⚙️ Key Metrics​

  • Response Time: Time taken to receive a response after sending a request.
  • Throughput: Number of requests processed per unit time (e.g., requests/sec).
  • Latency: Delay between request initiation and first byte received.
  • Error Rate: Percentage of failed requests.
  • Resource Utilization: CPU, memory, disk I/O, and network usage during tests.
  • Concurrent Users/Sessions: Number of active users or sessions during the test.
  • Transactions per Second (TPS): Number of completed transactions per second.

🧪 Tools & Frameworks​

  • Apache JMeter: Java-based, GUI and CLI, supports HTTP, WebSockets, JDBC, JMS, etc.
  • Gatling: Scala-based, code-driven, real-time metrics, HTTP/S, WebSockets.
  • k6: JavaScript scripting, CLI, cloud integration, modern APIs.
  • Locust: Python-based, distributed, user behavior scripting.
  • Artillery: Node.js, YAML/JS scripting, HTTP, WebSockets.
  • wrk: High-performance HTTP benchmarking tool.
  • Siege: CLI-based HTTP load tester.

📝 Example: JMeter CLI Test​

# Run a JMeter test plan with 100 users for 10 minutes
jmeter -n -t test_plan.jmx -l results.jtl -Jusers=100 -Jduration=600

# Analyze results
jmeter -g results.jtl -o ./report

📊 Result Analysis​

  • JMeter HTML Reports: Visualize response times, throughput, error rates, percentiles.
  • Grafana + InfluxDB/Prometheus: Real-time dashboards for resource and application metrics.
  • Custom Scripts: Parse logs, aggregate metrics, and generate custom reports.

🛡️ Best Practices​

  • Test in a production-like environment (hardware, network, data).
  • Use realistic test data and user scenarios.
  • Warm up the system before measuring.
  • Monitor both application and infrastructure metrics.
  • Automate performance tests in CI/CD pipelines.
  • Analyze results for trends, not just single runs.
  • Profile and optimize code based on findings.

📚 Useful Links​