Software Testing - Load Testing

1. What is Load Testing?

Load Testing is a type of performance testing that checks how a system behaves under expected real-world user load.
The purpose is to verify that the application can handle the projected number of users, transactions, or data volumes without performance degradation.

In simple words:

Load Testing checks how the system performs when many users use it at the same time, but under normal expected conditions — not beyond limits.

2. Objective of Load Testing

The main goals are:

✔ Ensure system performance under expected load

(max concurrent users, typical traffic)

✔ Identify performance bottlenecks

(slow APIs, heavy queries, slow response times)

✔ Validate reliability and responsiveness

during normal peak usage

✔ Confirm infrastructure capacity

(server size, database configuration, caching, network limits)

✔ Help plan scaling and resource allocation

(based on the results)

3. When to Perform Load Testing

  • Before major releases

  • When new features are added

  • Before marketing campaigns / seasonal traffic

  • During infrastructure changes (e.g., server migration)

  • Before going live with a new website or app

4. What load testing measures

Important metrics include:

Performance Metrics

  • Response time

  • Throughput (requests per second)

  • Concurrent users

  • Request execution time

  • Latency

Resource Metrics

  • CPU usage

  • Memory usage

  • Disk I/O

  • Network usage

  • Database performance

Operational Metrics

  • Error rate

  • Timeout rate

  • Server utilization

  • Bottleneck detection

5. Load Testing Workflow (Step-by-Step)

Step 1 — Identify performance requirements

  • How many users are expected simultaneously?

  • What is acceptable response time?

  • What workload needs to be tested?

Step 2 — Design test scenarios

Examples:

  • 1,000 users browsing product pages

  • 200 users adding items to cart

  • 150 users checking out

Step 3 — Test data preparation

  • User accounts

  • Test input data

  • Database state

Step 4 — Choose load testing tools

(Examples below)

Step 5 — Execute tests

Apply increasing load until it reaches the expected user volume.

Step 6 — Monitor environment

Check:

  • Server health

  • Database performance

  • API responsiveness

Step 7 — Analyze results

Identify:

  • Slow components

  • Failure points

  • Optimization opportunities

Step 8 — Re-test after optimization

6. Load Testing Example

Scenario: E-commerce website

Expected:

  • 1,000 concurrent users during peak sale.

Test:

  • Simulate 1,000 users browsing, searching products, adding to cart.

Metrics observed:

  • Homepage load time: 1.5 sec

  • Search API: 320 ms

  • Add-to-cart: 450 ms

  • Error rate: 1.2%

If response time is within acceptable range and no major errors → Load test PASSED.

7. Popular Load Testing Tools

Open-Source Tools

  • JMeter (Apache)

  • Locust

  • Gatling

  • k6

  • Tsung

Cloud-Based Tools

  • BlazeMeter

  • LoadRunner Cloud

  • AWS Performance Testing tools

  • Azure Load Testing

Enterprise Tools

  • HP LoadRunner

  • Neoload

8. Load Testing vs Stress Testing (Important Difference)

Feature Load Testing Stress Testing
Purpose Test at expected load Test beyond maximum load
Goal Confirm system performance under normal use Determine breaking point
Load level Normal / expected Extreme / unexpected
Outcome Stability and performance verification Identify system limits and failures

9. Common Mistakes in Load Testing

  • Not preparing realistic test data

  • Testing only at low load values

  • Testing on weak or small test environments

  • Ignoring database performance

  • Not monitoring infrastructure

  • Running tests without setting clear KPIs

10. Best Practices

  • Test with realistic user behavior

  • Use proper ramp-up and ramp-down times

  • Always test in a production-like environment

  • Monitor both client-side and server-side metrics

  • Re-run load tests after each optimization

  • Correlate logs, metrics, and test scripts for accurate insights