JMeter or LoadRunner Performance Testing Fundamentals

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Duration 3 Days – 21 hrs

 

Overview

 

The JMeter or LoadRunner Performance Testing Fundamentals Training Course is designed to provide participants with a practical foundation in performance testing concepts, test planning, script creation, workload modeling, test execution, monitoring, analysis, and reporting using either Apache JMeter or OpenText LoadRunner.

 

This course introduces participants to the principles of performance testing, including load testing, stress testing, spike testing, endurance testing, scalability testing, and volume testing. Participants will learn how to identify performance requirements, design realistic test scenarios, create and execute performance test scripts, analyze response times and throughput, identify bottlenecks, and prepare performance test reports.

The course can be delivered using Apache JMeter for open-source performance testing or OpenText LoadRunner for enterprise-grade performance testing environments. The training is suitable for software testing teams, QA engineers, performance testers, developers, DevOps teams, and IT professionals involved in validating application performance and reliability.

 

Objectives

 

  • Understand performance testing concepts, objectives, and common terminology.
  • Differentiate between load testing, stress testing, spike testing, endurance testing, scalability testing, and volume testing.
  • Identify performance requirements, service-level expectations, and key performance indicators.
  • Design realistic performance test scenarios based on user behavior and business processes.
  • Create basic performance test scripts using JMeter or LoadRunner.
  • Apply parameterization, correlation, assertions, checkpoints, and think time.
  • Configure virtual users, workload models, ramp-up, duration, and test data.
  • Execute performance tests and monitor application behavior under load.
  • Interpret response time, throughput, error rate, latency, transactions per second, and resource utilization.
  • Identify common performance bottlenecks in application, database, network, and server layers.
  • Prepare performance test summary reports with findings and recommendations.
  • Apply performance testing best practices in software delivery and production readiness validation.

 

Target Audience

 

  • QA testers and software testers
  • Performance testers
  • Test automation engineers
  • Manual testers transitioning to performance testing
  • Software developers
  • DevOps engineers
  • Site reliability engineers
  • Application support teams
  • Systems administrators
  • Database administrators
  • IT operations teams
  • Technical leads and project teams involved in application release validation
  • Organizations implementing performance testing as part of quality assurance or DevOps practices

 

Prerequisites

 

  • Basic understanding of software testing concepts
  • Basic knowledge of web applications and client-server architecture
  • Familiarity with HTTP, APIs, browsers, and application workflows
  • Basic knowledge of databases, servers, or networks is helpful
  • Basic scripting or programming awareness is helpful but not required
  • No prior JMeter or LoadRunner experience is required

 

 Course Outline

 

Day 1: Performance Testing Fundamentals and Tool Introduction

 

Module 1: Introduction to Performance Testing

  • What is performance testing?
  • Importance of performance testing in software quality
  • Performance testing in SDLC, Agile, and DevOps
  • Performance testing versus functional testing
  • Performance testing objectives
  • Common performance risks
  • Performance testing roles and responsibilities

 Module 2: Types of Performance Testing

  • Load testing
  • Stress testing
  • Spike testing
  • Endurance or soak testing
  • Scalability testing
  • Volume testing
  • Baseline testing
  • Capacity testing
  • Choosing the right test type based on business needs

Module 3: Performance Metrics and KPIs

  • Response time
  • Throughput
  • Transactions per second
  • Hits per second
  • Error rate
  • Latency
  • Concurrent users versus simultaneous users
  • CPU, memory, disk, and network utilization
  • Apdex and user experience indicators
  • Service-level agreements and performance acceptance criteria

 Module 4: Performance Test Planning

  • Understanding business processes
  • Identifying critical user journeys
  • Defining test scope and objectives
  • Gathering non-functional requirements
  • Creating workload models
  • Defining user load, ramp-up, duration, and pacing
  • Test data requirements
  • Environment readiness checklist
  • Entry and exit criteria for performance testing

 Module 5: Introduction to JMeter or LoadRunner

  • Overview of Apache JMeter
  • Overview of OpenText LoadRunner
  • Tool selection considerations
  • Tool architecture and components
  • Test plan or script structure
  • Recording and scripting concepts
  • Test execution workflow
  • Result collection and reporting overview

 

Day 2: Scripting, Test Design, and Execution

 

Module 6: Creating Basic Performance Test Scripts

  • Creating a test plan or script
  • Recording user actions
  • Adding requests or transactions
  • Organizing scripts by business flow
  • Adding transaction names
  • Validating recorded scripts
  • Running a basic test
  • Reviewing initial results

 Module 7: Parameterization and Test Data Management

  • Purpose of parameterization
  • Replacing hard-coded values
  • Using external test data files
  • Creating realistic user variation
  • Managing usernames, passwords, search values, and transaction data
  • Data reuse and uniqueness considerations
  • Test data preparation checklist

 Module 8: Correlation and Dynamic Data Handling

  • What is correlation?
  • Why dynamic values cause script failure
  • Common dynamic values: session IDs, tokens, hidden fields, request IDs
  • Identifying dynamic values
  • Manual and automatic correlation concepts
  • Validating correlation
  • Troubleshooting failed scripts

 Module 9: Assertions, Checkpoints, and Error Handling

  • Purpose of assertions and checkpoints
  • Validating response content
  • Validating status codes
  • Handling redirects
  • Handling failed transactions
  • Logging and debugging scripts
  • Common scripting errors
  • Script reliability best practices

 Module 10: Workload Modeling and Test Execution

  • Designing realistic user load
  • Concurrent users and transaction mix
  • Ramp-up and ramp-down strategy
  • Think time and pacing
  • Test duration planning
  • Load distribution
  • Running controlled load tests
  • Monitoring test execution
  • Capturing errors and observations during execution

 

 Day 3: Monitoring, Analysis, Reporting, and Best Practices

 

Module 11: Performance Monitoring Fundamentals

  • Why monitoring is important during performance testing
  • Application server monitoring
  • Web server monitoring
  • Database monitoring
  • Network monitoring
  • Cloud resource monitoring overview
  • Infrastructure metrics to observe
  • Application logs and error tracking
  • Coordinating with operations and development teams

 Module 12: Results Analysis

  • Understanding performance test results
  • Analyzing response time trends
  • Analyzing throughput
  • Identifying error patterns
  • Comparing baseline and load test results
  • Finding bottlenecks
  • Correlating application behavior with infrastructure metrics
  • Recognizing common performance issues

 Module 13: Bottleneck Identification

  • Application-level bottlenecks
  • Database bottlenecks
  • API bottlenecks
  • Network latency issues
  • Server resource constraints
  • Poor configuration or capacity limits
  • Third-party dependency issues
  • Slow transactions and high-error scenarios
  • Prioritizing performance issues by business impact

 Module 14: Performance Test Reporting

  • Purpose of performance test reporting
  • Executive summary
  • Test objectives and scope
  • Test environment details
  • Workload model summary
  • Key metrics and observations
  • Issues and bottlenecks
  • Recommendations and next steps
  • Pass/fail assessment based on acceptance criteria

 Module 15: Performance Testing Best Practices

  • Start performance testing early
  • Align tests with business-critical scenarios
  • Use realistic data and workload models
  • Validate scripts before load execution
  • Establish baseline results
  • Monitor all critical layers
  • Avoid testing in unstable environments
  • Retest after tuning
  • Maintain reusable test assets
  • Integrate performance testing into CI/CD where applicable

 Module 16: Practical Performance Testing Workshop

  • Define a performance testing objective
  • Identify critical business transactions
  • Build a basic JMeter or LoadRunner script
  • Apply parameterization
  • Apply correlation where needed
  • Configure workload settings
  • Execute a sample load test
  • Analyze the test results
  • Identify performance issues
  • Prepare a sample performance test report

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