/load-test

Run a load test against an API endpoint to measure throughput and identify breaking points.

Steps

1. Define load test parameters:
   • Target URL and HTTP method.
   • Concurrent connections (start low, ramp up).
   • Duration of the test.
   • Request payload and headers.
2. Select the load testing tool:
   • wrk or wrk2 for HTTP benchmarking.
   • k6 for scripted load tests.
   • ab (Apache Bench) for simple tests.
   • hey for quick Go-based load tests.
3. Run a warm-up phase with low concurrency (10 connections, 10 seconds).
4. Execute the main load test in stages:
   • Stage 1: Normal load (expected concurrent users).
   • Stage 2: Peak load (2x expected).
   • Stage 3: Stress test (increase until error rate > 5%).
5. Collect metrics at each stage:
   • Requests per second (throughput).
   • Latency distribution (P50, P95, P99).
   • Error rate and error types.
   • Resource utilization (CPU, memory) if accessible.
6. Identify the breaking point and bottleneck.
7. Generate a report with recommendations.

Format

Load Test: <METHOD> <endpoint>

| Stage | Concurrency | RPS | P50 (ms) | P99 (ms) | Errors |
|-------|-------------|-----|----------|----------|--------|
| Normal | 10 | 500 | 20 | 85 | 0% |
| Peak | 50 | 1200 | 45 | 200 | 0.1% |
| Stress | 200 | 800 | 500 | 2000 | 5.2% |

Breaking point: ~150 concurrent connections
Bottleneck: Database connection pool exhaustion

Recommendations:
  1. Increase connection pool size from 10 to 50
  2. Add connection queuing with backpressure

Rules

• Never run load tests against production without explicit permission.
• Always include a warm-up phase before measuring.
• Ramp up gradually; do not jump to maximum load immediately.
• Record baseline metrics before the test for comparison.
• Stop the test if error rate exceeds 10% to avoid cascading failures.