Deep systems understanding · Study map 77 of 85
Load testing: recreate the traffic, not just the average
Suggested preparation: Observability: connect the user symptom to the machine
Picture it
Testing a bridge by walking across it alone tells you nothing about rush hour. Real users arrive in sudden, unpredictable waves, not a steady, polite single-file line. Open-loop testing unleashes this realistic flood, revealing the breaking points where queues pile up and the structure begins to groan under the weight.
What to understand
- Open versus closed loop, trace replay, warm/cold caches
- Arrival process, length distributions, steady state, errors, and tail metrics
Follow the references
1 · Documentation
vLLM · Serving benchmark reference ↗Inspect request-rate, burstiness, dataset, and latency options. Read the current version’s metric definitions.
Make it concrete
Sweep offered load from idle through overload. Count all arrivals, rejections, timeouts, and successful outputs; plot goodput and tails alongside throughput.
You understand it when…
Why is reporting only completed-request latency misleading when many requests timed out?
This is a study map. Follow the reference for the full explanation; use the question to test your mental model. Browse the reference shelf.