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JMeter Performance Engineering


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Length: 5 day (40 hours)

 

This course is a deep dive into the Performance Testing Life Cycle (PTLC) using Apache JMeter. You will move from recording basic web traffic to designing complex, high-concurrency scenarios that simulate real-world global traffic.

The curriculum covers not just "how to use the tool," but how to identify bottlenecks (CPU, Memory, Network), perform Distributed Testing (using multiple "slave" machines), and automate performance gates in CI/CD pipelines. By the end, you’ll be building self-healing performance scripts that provide actionable insights rather than just raw data.

Fundamental Testing Knowledge: Understanding of the STLC and why we test for speed, stability, and scalability.

Web Protocol Basics: A working knowledge of HTTP/HTTPS (Requests, Responses, Headers, Cookies, and Status Codes like 200, 404, 500).

Basic Scripting: Familiarity with variables and loops. Knowledge of Java or Groovy is a major plus for writing custom logic (JSR223).

Environment: A machine with Java JDK 21+ installed and at least 8GB RAM for local load simulation.

QA & Automation Engineers: Who want to add "Performance Testing" to their portfolio to reach Senior/Lead roles.

Performance Engineers: Moving from commercial tools (like LoadRunner) to open-source JMeter.

DevOps & SREs: Who need to automate performance benchmarks in the deployment pipeline.

System Architects: Aiming to understand how to design systems that handle peak traffic (e.g., Black Friday sales).

Course objectivesCourse outlines

Course objectives

After completing this course, students will be able to:

    • Plan & Strategize: Define Non-Functional Requirements (NFRs) and create a formal Performance Test Plan.
    • Master JMeter Components: Expertly use Thread Groups, Samplers, Listeners, Assertions, and Logic Controllers.
    • Handle Dynamic Data: Use Correlation (Regular Expression/JSON Extractors) and Parameterization (CSV Data Sets) to make scripts realistic.
    • Simulate Advanced Load: Implement Ramp-up/Ramp-down, Pacing, and Think Time to mimic human behavior.
    • Engineering & Analysis: Identify server-side bottlenecks and generate professional HTML Dashboard Reports.
    • Automation & Scaling: Run tests in Non-GUI mode, integrate with Jenkins/GitHub Actions, and execute distributed tests across a cloud-based Selenium/JMeter Grid.

Course outlines

    • Module 1: The Foundations of Performance
      • Types of Testing: Load, Stress, Endurance (Soak), Spike, and Scalability.
      • The "3 B's": Benchmarking, Baseline, and Bottlenecks.
      • Introduction to JMeter 5.6+ Architecture and Installation.
    • Module 2: Scripting & Recording
      • HTTP(S) Test Script Recorder: Capturing browser traffic the right way.
      • Correlation: Handling dynamic tokens, session IDs, and CSRF tokens.
      • Logic Controllers: If/While/Loop controllers to build complex user journeys.
    • Module 3: Data-Driven Testing & Assertions
      • Parameterization using CSV and Random Data Generators.
      • Assertions: Validating response code, size, and duration to ensure quality under load.
    • Module 4: Performance Monitoring & Reporting
      • Non-GUI Execution: Why and how to run tests from the command line.
      • HTML Dashboard Reports: Interpreting Latency, Throughput, and Error Rates.
      • Monitoring Server Health: Integrating with Prometheus & Grafana.
    • Module 5: Advanced & Modern JMeter (2026 Updates)
      • JSR223 & Groovy: Writing custom scripts for high-performance data processing.
      • CI/CD Integration: Breaking the build based on performance failure criteria.
      • AI in JMeter: Using AI to auto-generate NFRs and analyze test result trends.
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