k6 Performance Testing

This project is focused on learning and practicing performance testing with k6.

---

Performance Testing Workflow

My general performance-testing workflow is:

1. Understand Requirements
        ↓
2. Identify Critical User Scenarios
        ↓
3. Define Performance Goals / SLAs
        ↓
4. Select Test Type
        ↓
5. Create k6 Test Script
        ↓
6. Configure Load Profile
        ↓
7. Organize Requests Using Groups
        ↓
8. Add Tags
        ↓
9. Define Thresholds
        ↓
10. Execute Test
        ↓
11. Monitor Application & Infrastructure
        ↓
12. Analyze Metrics
        ↓
13. Identify Bottlenecks
        ↓
14. Report Results

---

Project Structure

k6-performance-testing/
│
├── Building HTTP requests for APIs/
│   ├── http-get.js
│   ├── http-post.js
│   ├── http-put.js
│   └── login.js
│
├── K6 Fundamentals/
│   ├── first-script.js
│   ├── smoke-test.js
│   ├── load-test.js
│   ├── group-test.js
│   ├── custome-metrics.js
│   └── test-tags.js
│
├── k6 Scenarios/
|   ├── scenario-eg1.js
|   ├── gracefulStop-test.js
|   ├── production-workload.js
│
├── k6 Cloud/
│
├── Using parameters in k6 scripts/
|   ├── external-json.js
|   ├── external-csv.js
│   └── users.json
│
└── README.md

What I Learned

Through this project, I have gained practical experience with k6 and performance testing, including:

• Creating and structuring k6 performance test scripts
• Building HTTP GET, POST, and PUT requests
• Working with JSON request bodies and payloads
• Configuring HTTP request headers
• Implementing API authentication
• Working with Bearer tokens
• Extracting data from API responses
• Sending authenticated API requests
• Configuring Virtual Users (VUs) and test duration
• Running Smoke and Load tests
• Understanding different types of performance testing
• Working with k6 built-in metrics
• Creating and using custom metrics
• Understanding Trend, Counter, Gauge, and Rate metrics
• Analyzing Average, Median, P90, P95, and P99
• Defining performance requirements using thresholds
• Organizing requests and business flows using groups
• Measuring complete business-flow performance using group_duration
• Categorizing and filtering metrics using tags
• Using tags with thresholds
• Understanding the difference between individual request performance and complete business-flow performance
• Building a structured and reusable performance-testing workflow

---

Next Steps

I plan to continue extending this project by learning and implementing:

• Advanced k6 CLI usage
• Parameterizing k6 scripts
• Environment-based configuration
• Advanced authentication flows
• Data-driven performance testing
• More complex API business flows
• Advanced k6 scenarios and executors
• CI/CD integration
• GitHub Actions integration
• Jenkins integration
• k6 Cloud
• Distributed load testing
• Performance regression testing
• Advanced performance reporting and result analysis

---

Goal

The goal of this project is to build a strong practical understanding of performance testing with k6.

I am gradually progressing from writing basic HTTP requests to:

HTTP Requests
      ↓
API Authentication
      ↓
Test Scripts
      ↓
Performance Test Types
      ↓
Metrics & Analysis
      ↓
Groups & Tags
      ↓
Thresholds
      ↓
Advanced Scenarios
      ↓
CI/CD Integration
      ↓
Cloud & Distributed Load Testing

Ultimately, I aim to build realistic, maintainable, and reusable performance tests and integrate them into CI/CD pipelines and cloud-based performance-testing environments.