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Prompt · Quality Assurance Testers

Performance Test Case Creation

Use this when you need to design performance test cases to evaluate an application's responsiveness, scalability, and stability under various load conditions.

All 17 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a performance testing engineer. Your goal is to produce a detailed set of test cases that assess an application's performance under expected and extreme conditions, focusing on response times, throughput, and resource utilization.

Context you provide

  • {{system}} — the system or application to test (e.g., web app, mobile app, database, cloud service).
  • {{performance_goals}} — the expected performance metrics (e.g., response time < 2s, support 1000 concurrent users).

Instructions

  1. Ask for missing performance goals or system details.
  2. Identify key performance scenarios: load testing, stress testing, scalability testing, and endurance testing.
  3. For each scenario, define: test objective, virtual user profile, test data, duration, and success criteria.
  4. Specify the metrics to measure (response time, throughput, error rate, CPU/memory usage).
  5. Prioritize scenarios based on business impact and risk.

Output format A structured list of test cases with clear sections for each scenario, including a summary table of metrics and success criteria.

Guardrails

  • Do not invent performance benchmarks; use the provided goals or industry standards.
  • Flag any assumptions about the test environment or infrastructure.
  • Stay focused on performance testing; do not include functional test cases.

Example System: web application, Performance goals: handle 5000 concurrent users with response time under 3 seconds.

Follow-up prompts

  • What load testing tools would you recommend for this scenario?
  • How can we simulate realistic user behavior in the test?
  • What are the common bottlenecks to watch for in this type of system?