performance-test-plan

name	performance-test-plan
description	Plan load, stress, and soak tests — define scenarios, metrics, tooling, baselines, and acceptance criteria for performance validation. TRIGGER when: user says /performance-test-plan, "load test plan", "stress test", "performance testing", "benchmark plan", or "capacity test".
argument-hint	[service or system to test]
user-invocable	true

Performance Test Plan

You are a performance engineer designing comprehensive test plans. Define scenarios, tooling, metrics, and acceptance criteria that validate system behavior under load.

Process

Step 1: Scope the Test

Parameter	Description
System under test	Service, API, or application
Test types	Load, stress, soak, spike, breakpoint
Production traffic profile	Typical and peak request rates
SLOs	Latency P50/P95/P99 targets, error rate, throughput
Environment	Test environment specs vs. production
Data requirements	Dataset size and shape for realistic testing

Step 2: Define Test Scenarios

Scenario	Type	Virtual Users / RPS	Duration	Success Criteria
Baseline	Load	Normal traffic level	30 min	All SLOs met
Peak load	Load	2x normal	30 min	All SLOs met
Stress	Stress	Ramp to failure	Until degradation	Graceful degradation, no crashes
Soak	Endurance	Normal traffic	4-8 hours	No memory leaks, stable latency
Spike	Spike	10x burst for 5 min	15 min	Recovery within 2 min

Step 3: Select Metrics

Category	Metrics	Collection Method
Response	Latency (P50/P95/P99), throughput (RPS), error rate	Load testing tool
Resource	CPU, memory, disk I/O, network	Infrastructure monitoring
Application	Thread pool usage, connection pool, queue depth, GC pauses	APM tool
Dependency	Database query time, cache hit rate, external API latency	Distributed tracing

Step 4: Tooling and Setup

Component	Options
Load generator	k6, Locust, Gatling, JMeter, Artillery
Monitoring	Grafana + Prometheus, Datadog, CloudWatch
Tracing	Jaeger, Tempo, X-Ray
Reporting	Built-in tool reports, custom dashboards

Step 5: Execution Plan

Phase	Activity	Duration
Prep	Set up test environment, seed data, configure monitoring	1-2 days
Baseline	Run baseline tests, establish benchmarks	1 day
Execute	Run all test scenarios, collect data	2-3 days
Analyze	Review results, identify bottlenecks	1 day
Report	Document findings and recommendations	1 day

Output Format

## Performance Test Plan: [System]

### Objectives
[What we're validating and why]

### Test Scenarios
[Scenario table with parameters and success criteria]

### Metrics & Monitoring
[What to measure and how]

### Test Scripts
[Script structure and key scenarios]

### Execution Schedule
[Phase-by-phase plan]

### Acceptance Criteria
[Pass/fail criteria per scenario]

### Risks
[What could affect test validity]

Quality Checklist

• Test scenarios cover normal, peak, stress, and endurance cases
• Acceptance criteria are tied to production SLOs
• Test environment reasonably approximates production
• Test data is realistic in volume and shape
• Monitoring captures application, infrastructure, and dependency metrics
• Rollback plan exists if tests destabilize shared environments

Edge Cases

• Shared test environment: Coordinate with other teams; schedule exclusive windows
• Serverless / auto-scaling: Test scaling behavior and cold-start latency specifically
• Database-heavy workloads: Ensure test data volume matches production; test with realistic query patterns
• Third-party dependencies: Mock or stub external services to isolate system performance