1. What is Performance Testing?
Definition:
Performance testing is a type of non-functional testing that evaluates how a software application performs under a certain workload. It measures speed, responsiveness, stability, and scalability.
Key Goal: Ensure the application meets performance requirements under expected and peak conditions.
Why Important:
- Identify bottlenecks in the system.
- Ensure smooth user experience under heavy load.
- Optimize resource usage (CPU, memory, bandwidth).
- Prevent crashes, slowdowns, or failures in production.
2. Key Performance Metrics
| Metric | Description |
|---|---|
| Response Time | Time taken to respond to a user request |
| Throughput | Number of transactions processed per second |
| Latency | Delay between sending a request and receiving a response |
| Concurrency | Number of users the system can handle simultaneously |
| Resource Utilization | CPU, memory, disk, and network usage |
| Error Rate | Number of failed requests under load |
3. Types of Performance Testing
- Load Testing
- Measures system behavior under expected normal load.
- Example: 1000 users logging in simultaneously.
- Stress Testing
- Tests system under extreme load to see breaking point.
- Example: 5000 users hitting the server.
- Spike Testing
- Sudden increase or decrease in load to test stability.
- Example: Traffic suddenly spikes from 100 to 1000 users.
- Endurance / Soak Testing
- Test system performance over a long period.
- Checks for memory leaks or degradation.
- Scalability Testing
- Measures how well the system scales with increased load.
- Helps in planning server or cloud resources.
4. Performance Testing Process
- Requirement Gathering
- Identify performance goals (response time, throughput, max users).
- Test Planning
- Define scope, environment, tools, and schedule.
- Test Environment Setup
- Prepare servers, network, databases, and monitoring tools.
- Test Script Development
- Create scripts for user actions (login, search, checkout, etc.).
- Test Execution
- Run tests using performance testing tools.
- Monitoring & Data Collection
- Monitor CPU, memory, network, and logs during the test.
- Analysis & Reporting
- Analyze metrics, identify bottlenecks, and suggest improvements.
5. Popular Performance Testing Tools
| Tool | Key Features |
|---|---|
| JMeter | Open-source, supports load, stress, and functional testing |
| LoadRunner | Enterprise-level tool, detailed monitoring and reporting |
| Gatling | Open-source, good for high-performance scenarios |
| BlazeMeter | Cloud-based JMeter alternative for large-scale testing |
| NeoLoad | Supports web, mobile, and cloud applications |
6. Best Practices in Performance Testing
- Test early and often – don’t wait for production.
- Use realistic test data and scenarios.
- Monitor all resources – CPU, memory, disk, network.
- Simulate real-world conditions – users, network speed, geographic location.
- Document performance benchmarks for future comparison.
- Collaborate with developers to fix bottlenecks quickly.
- Run tests on a staging environment similar to production.
7. Summary
- Performance Testing ensures applications are fast, reliable, and scalable.
- Key types include Load, Stress, Spike, Endurance, and Scalability testing.
- Metrics like response time, throughput, and resource utilization are crucial.
- Tools like JMeter, LoadRunner, and Gatling are widely used.
- Following best practices prevents performance issues in production.