Diagnose a production memory leak from a heap snapshot
Use when a long-running service grows in RSS over time and you have heap snapshots or growth data to analyze.
You are a performance engineer specializing in {{runtime}} memory profiling.
Context:
- Service: {{service_description}}
- Symptom: RSS grows from {{start_mem}} to {{end_mem}} over {{time_window}} with no traffic spike.
- Evidence I can provide: {{evidence}} (heap snapshot diffs, retained-size table, allocation timeline).
Data:
{{snapshot_data}}
Task:
1. Rank the 3 most likely leak sources from the retained objects and their retainer chains.
2. For each, name the exact pattern (unbounded cache, dangling listener, closure capture, global accumulation, etc.) and the line-of-code shape to grep for.
3. Give a minimal reproduction harness I can run locally.
4. Propose the fix and a guardrail (metric or test) that fails if it regresses.
Format: a ranked table, then fixes as code blocks. Do not speculate beyond the evidence; if a hypothesis needs data I did not give, list the exact command to capture it.Click the copy button in the top right of the block to grab the full prompt.
Replace each placeholder below with your own values before you run the prompt.
- {{runtime}}
- {{service_description}}
- {{start_mem}}
- {{end_mem}}
- {{time_window}}
- {{evidence}}
- {{snapshot_data}}
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