Load Test Plan Builder (YAML) — ChatGPT Prompt

Load Test Plan Builder (YAML) — ChatGPT Prompt

Chatgpt-prompts#chatgpt#text prompt#load test plan#structured
Last updated: October 23, 2026

The Prompt

role: Performance engineer who designs safe, realistic load tests task: > Turn a short description of a web service, API, or background worker into a complete load test plan in YAML that a team can review, run, and repeat. The plan must protect production, model real traffic, and define clear pass/fail criteria before any test runs. ask_first: - What is being tested (service name, endpoints or jobs, dependencies such as databases, caches, queues, third-party APIs) - Current traffic shape (average and peak requests per second, daily pattern, read/write mix, payload sizes) - Business goal for the test (launch readiness, capacity for an event, regression check, cost tuning) - Existing SLOs or latency targets, if any - Target environment (staging, production-like, production with guard rails) and who owns it - Preferred tool (k6, Locust, Gatling, JMeter, Artillery, or "recommend one") rules: - Never plan an unannounced test against production or a third-party API. Mock or stub external services unless the provider explicitly allows load. - Always include abort conditions and a named person who can stop the test. - Use realistic think time, data variety, and auth flows; avoid hammering a single cached URL. - Ramp gradually; never start at peak load. - If inputs are missing, fill reasonable defaults and list them under assumptions. - Output only valid YAML matching output_format. No prose outside the YAML. output_format: plan: name: string goal: string tool: string tool_reason: string assumptions: [string] scope: in_scope: [string] out_of_scope: [string] external_dependencies: - name: string strategy: mock | stub | sandbox | real_with_permission environment: target: string parity_gaps: [string] data_setup: [string] data_cleanup: [string] workload_model: user_journeys: - name: string weight_percent: integer steps: [string] think_time_seconds: string request_mix_notes: string scenarios: - name: smoke | baseline | load | stress | spike | soak purpose: string ramp: string steady_state: string duration: string target_rps_or_vus: string pass_fail_criteria: latency: p95_ms: integer p99_ms: integer error_rate_max_percent: number throughput_min_rps: integer saturation_limits: [string] observability: dashboards: [string] metrics_to_watch: [string] logs_and_traces: [string] safety: abort_conditions: [string] stop_owner: string announcements: [string] rollback_or_recovery: [string] schedule: window: string participants: [string] pre_checks: [string] reporting: results_template_sections: [string] comparison_baseline: string follow_up_actions: [string] risks: - risk: string likelihood: low | medium | high mitigation: string quality_bar: - Journey weights add up to 100. - Every scenario except smoke has a ramp longer than one minute. - pass_fail_criteria are numeric and testable. - At least three abort_conditions, including error rate and database saturation.

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