What tools should I use for load testing?

k6 for developer-friendly scripting, Locust for Python-based tests, JMeter for comprehensive GUI-based testing, and Artillery for Node.js projects.

How many concurrent users should I test for?

Test for 2-3x your expected peak traffic. If you expect 1000 concurrent users, test up to 3000 to find your headroom.

Should I load test in production?

Only with careful controls. Use feature flags to route test traffic, run during low-traffic windows, and have rollback ready. A staging environment matching production is preferred.

Load Testing Checklist

Validate your application can handle production traffic with structured load testing covering test design, execution, and capacity planning.

Checklist: Load Testing (engineering)

Load testing verifies your application can handle expected and peak traffic without degradation. Finding performance limits before users do prevents outages, revenue loss, and reputation damage. This checklist covers the full load testing lifecycle from planning through remediation.

Checklist Items

Define load testing objectives [critical]: Set specific goals: target concurrent users, acceptable response time percentiles, and throughput requirements.
Create realistic test scenarios [critical]: Model actual user behavior patterns including login, browse, search, and purchase flows with realistic think times.
Set up a production-like test environment [critical]: Use infrastructure matching production configuration to avoid false results from environment differences.
Prepare test data [important]: Generate sufficient test accounts, products, and records to match production data volume and distribution.
Establish performance baselines [important]: Run baseline tests to measure current performance before applying optimizations or changes.
Monitor all system layers during tests [important]: Track CPU, memory, disk I/O, network, database queries, and application metrics during test execution.
Run ramp-up and sustained load tests [important]: Gradually increase load to find the breaking point, then sustain peak load for 30-60 minutes to check stability.
Test auto-scaling behavior [recommended]: Verify auto-scaling triggers correctly and new instances receive traffic within acceptable timeframes.
Run spike tests [recommended]: Simulate sudden traffic spikes to verify the system handles rapid load increases without crashing.
Document results and capacity limits [recommended]: Record maximum throughput, P95/P99 latencies at each load level, and identified bottlenecks.

Common Mistakes

Testing from a single location: Use distributed load generation from multiple regions to simulate realistic geographic traffic patterns.
Ignoring the database during load tests: Database is usually the first bottleneck. Monitor query performance, connection pool usage, and lock contention.
Testing only happy paths: Include error scenarios, retries, and edge cases in load tests. Error handling paths often perform differently under load.

Frequently Asked Questions

What tools should I use for load testing?: k6 for developer-friendly scripting, Locust for Python-based tests, JMeter for comprehensive GUI-based testing, and Artillery for Node.js projects.
How many concurrent users should I test for?: Test for 2-3x your expected peak traffic. If you expect 1000 concurrent users, test up to 3000 to find your headroom.
Should I load test in production?: Only with careful controls. Use feature flags to route test traffic, run during low-traffic windows, and have rollback ready. A staging environment matching production is preferred.