Advance Performance Engineering - for Leaders, with Gen AI

Learn and build strong foundations in performance Engineering, with leadership insights and Intro to PE with Gen-AI

This course covers the fundamental concepts of Application Performance Engineering, Requirements Gathering, Performance Test planning and execution and Results Analysis.

The course is aimed for those whoever has the responsibility towards the application performance testing ./ non-functional aspects of the software products like the products owners, deliver managers and heads, Test Engineers / Test Leads / Test Managers and even IT heads or CTOs.

This course very useful for those who want to choose a career or change career into Performance Testing / Performance Engineering.

This course will give the confidence and fundamental knowledge in the Performance testing area, to clear any level of interviews.

Course Contents:

1. Introduction to Performance Testing and AI

1.1. Introduction to Performance Testing

1.2. Types of Performance Testing

1.3. Know the Terminology

1.4. Recap

2. Performance Testing - What, NOT, Why, When and How

2.1. WHAT and WHAT NOT is Performance Testing

2.2. Reason and Objectives of Performance Testing - the WHY

2.3. Determine when and What type of Performance Testing to be conducted

2.4. Performance Testing Lifecycle and HOW it is done

3. Performance Monitoring Metrics

3.1. Application Performance Metrics

3.2. Server-Side Metrics

3.3. Database Performance Metrics

3.4. Network Performance Metrics

3.5. Application Logs, Errors, Filesystem utilization

4. Application Performance Monitoring (APM)

4.1. APM Introduction - benefits, features, Sample report screenshots

4.2. Some APM tools and report samples

4.4. Monitoring checklist

- Ensure all components and interfaces are covered

- Prepare a list of monitoring counters

- Enable monitoring from before starting the test and end after the testing is completed.

5. Performance Monitoring using Operating System Commands - The Practical

5.1. OS commands for APM - Introduction

5.2. Linux - ps command

5.3. Linux - top command

5.4. Linux - vmstat command

5.5. Linux - iotop command

5.6. Linux - netstat command

{5.7. Linux commands - summary and conclusion}

5.8. Windows server monitoring

6. Demystifying Performance Testing: Myths, Pillars, and Insights

6.1. Performance Testing - Some Myths and Realities

6.2. Performance Testing - three pillars

6.3. Performance testing - thumb rules and hypothesis

7. Performance Requirements Gathering - An extensive How-to-do analysis

7.1. Performance Requirements Gathering - Introduction

7.2. Two types of Performance Requirements

7.3. Application Level Requirements Gathering - Part1

7.4. Application Level Requirements Gathering - Part2

7.5. Testing Level Requirements Gathering

7.6. A simple performance requirements gathering questionnaire

7.7. An extensive Performance Requirements Gathering template for download

8. Elements of Performance Test planning

8.1. Project overview / release overview.

8.2. Objectives and purpose of Performance Testing.

8.3. Conduct Assessment on PT required or NOT

8.4. Test coverage - In-scope / Out-scope

8.5. PT vs Prod Environment Comparison

8.6. Workload modeling

8.7. Determine what performance test types are required

8.8. Monitoring Framework

8.9. Test Data Requirements

8.10. Performance Test Project Management Elements

9. Assess the need for the Performance Test - how to determine whether PT is required or not

10. Production scenarios for testing:

- Exceptional scenarios

- Failure scenarios

- Spike scenario

- Rendezvous scenario

- In-scope and Out-of-scope Scenarios

- Alert jobs - triggered based on the condition is MET.

- Any offline jobs to be triggered.

11. Performance Test execution

- Some performance testing tools, how it works, tool architecture

- Demo performance Testing with LoadRunner (optional)

- Demo performance Testing with JMeter

- Reading the results (LR summary or JMeter results summary)

12. Results Analysis

- Translation of results back to Production reality

- Extrapolation methods

- Breaking point analysis

- Recommendations (for product's performance roadmap)

13. The Future of Performance Engineering

- Performance Engineering with GenAI - Model

- Performance Engineering with GenAI - Where it can go wrong