What is the difference between load, stress, and spike testing?

Load testing checks behaviour at expected peak traffic. Stress testing pushes past that to find the breaking point. Spike testing applies a sudden surge to see how the system handles bursts. This builder covers load and stress style runs by letting you set the peak user count and ramp.

Why use a ramp-up instead of starting at full load?

A gradual ramp-up lets connection pools, caches, and autoscalers warm up the way they would in production, and it helps you see at which load level latency starts to degrade. Slamming full load instantly mostly tests cold-start behaviour rather than steady-state capacity.

What thresholds should I set?

Common targets are a p95 latency under a few hundred milliseconds and an error rate under 1%, but the right numbers come from your SLOs. The plan records explicit thresholds so the run has an objective pass/fail rather than a vibe check.

Why is p95 latency better than average?

Averages hide the slow tail — a few very slow requests barely move the mean but ruin real users' experience. The p95 (or p99) shows what your slowest 5% see, which is where outages and timeouts actually start.

Which tool should I use?

k6 is scriptable in JavaScript and great in CI, JMeter has a mature GUI and plugin ecosystem, and Locust is Python-based and easy to distribute. The plan is tool-agnostic and includes a config note for whichever you select.

Load Testing Plan Builder

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Plan a load test that produces a real pass or fail

A load test without defined objectives and thresholds just produces graphs nobody can act on. A good plan states what you are validating, the exact traffic profile, the transactions to exercise, and the latency and error-rate limits that mean pass or fail. This builder assembles that plan so the run is reproducible and reviewable.

How it works

You set the objective, peak virtual users, ramp-up and steady-state durations, the key transactions with their traffic mix, and explicit thresholds for p95 latency and error rate. The tool composes a Markdown plan: objectives, a load profile (ramp to peak, hold, ramp down), a transaction table, pass/fail thresholds, and a configuration note for your chosen tool — k6, JMeter, or Locust. It normalises the transaction weights so they describe a realistic traffic mix rather than an arbitrary list.

Tips and example

Derive thresholds from your SLOs, e.g. p95 < 300ms and error rate < 1%, not from round numbers.
Ramp up over minutes, hold at peak for a meaningful steady state (10–15 min), then ramp down to observe recovery.
Weight transactions like production: if 70% of traffic is read and 30% is write, model that split.
Run against a production-like environment with realistic data volumes — a load test on an empty database lies.