Do we have to test in production to be realistic?

No. Test in a production-like environment with production traffic shape, sanitized data, and the same infra limits (rate limits, TLS, WAF). Then validate with a small production canary (1–5%) behind flags. You want realism and safety, not chaos.

How do we avoid testing with PII?

Replay shape, not content. Sample field distributions (e.g., payload sizes, SKU counts), generate synthetic identifiers, and validate schema. Never lift-and-shift logs. Lock down test data with short TTLs and access controls.

When do we stop scaling up and start fixing architecture?

If autoscaling increases cost faster than it restores SLOs, or if p99 tail remains high despite scaling 3–4x, you’re at the architectural ceiling. Address cacheability, DB access patterns, and service fan-out before adding more cores.

Which load tool should we pick?

k6 for developer-friendly scripting and thresholds; Locust if you like Python and stateful flows; Gatling if you want JVM perf; Artillery for quick API tests. The tool matters less than realistic models and good telemetry.

How much time should we budget for this?

For one critical flow, plan 2–4 weeks: 3–5 days to define SLOs and build workloads, 3–5 days to wire telemetry and CI, and the rest for two optimization cycles with canaries. Subsequent flows go faster.

Performance-optimization · Oct 19, 2025 · 10 minute read

Stop Load Testing Hello World: Validate Real User Behavior Under Stress

If your load test doesn’t hit the cart, the feed, and the login flows, it’s performance theater. Here’s the strategy I use to validate system behavior when it actually matters—and the optimizations that move real business metrics.

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Stop Load Testing Hello World: Validate Real User Behavior Under Stress

Key takeaways

Implementation checklist