6.8 KiB
Memory Leak Investigation Report
Service: [Service Name] Date: [YYYY-MM-DD] Investigator: [Your Name] Severity: [Critical/High/Medium/Low]
Executive Summary
TL;DR: [One sentence summary of the leak, cause, and fix]
Impact:
- Memory growth: [X MB/hour or X% increase]
- OOM incidents: [Number of crashes]
- Affected users: [Number or percentage]
- Duration: [How long the leak existed]
Resolution:
- Root cause: [Leak pattern - e.g., "EventEmitter listeners not removed"]
- Fix deployed: [Date/time]
- Status: [Resolved/Monitoring/In Progress]
Incident Timeline
| Time | Event | Details |
|---|---|---|
| [HH:MM] | Detection | [How was leak detected? Alert, manual observation, etc.] |
| [HH:MM] | Investigation started | [Initial actions taken] |
| [HH:MM] | Root cause identified | [What was found] |
| [HH:MM] | Fix implemented | [Code changes made] |
| [HH:MM] | Fix deployed | [Deployment details] |
| [HH:MM] | Validation complete | [Confirmation that leak is fixed] |
Symptoms and Detection
Initial Symptoms
- Linear memory growth (X MB/hour)
- OOM crashes (frequency: ___)
- GC pressure (frequent/long pauses)
- Connection pool exhaustion
- Service degradation (slow responses)
- Other: ___
Detection Method
How Discovered: [Alert, monitoring dashboard, user report, etc.]
Monitoring Data:
Prometheus query: [Query used to detect the leak]
Alert rule: [Alert name/threshold]
Dashboard: [Link to Grafana dashboard]
Example Metrics:
Before:
- Heap usage baseline: X MB
- After 6 hours: Y MB
- Growth rate: Z MB/hour
Current:
- Heap usage: [Current value]
- Active connections: [Number]
- GC pause duration: [p95 value]
Investigation Steps
1. Initial Data Collection
Tools Used:
- Chrome DevTools heap snapshots
- Node.js
--trace-gclogs - Python Scalene profiling
- Prometheus metrics
- Application logs
- Other: ___
Heap Snapshots Collected:
Snapshot 1: [timestamp] - [size] MB - [location/filename]
Snapshot 2: [timestamp] - [size] MB - [location/filename]
Snapshot 3: [timestamp] - [size] MB - [location/filename]
2. Snapshot Comparison Analysis
Method: [Comparison view in Chrome DevTools, diff analysis, etc.]
Findings:
Objects growing between snapshots:
- [Object type 1]: +X instances (+Y MB)
- [Object type 2]: +X instances (+Y MB)
- [Object type 3]: +X instances (+Y MB)
Top 3 memory consumers:
1. [Object type] - X MB - [Retainer path]
2. [Object type] - X MB - [Retainer path]
3. [Object type] - X MB - [Retainer path]
3. Retainer Path Analysis
Leaked Object: [Type of object that's leaking]
Retainer Path:
Window / Global
→ [Variable name]
→ [Object/function]
→ [Property]
→ [Leaked object]
Why Not GC'd: [Explanation of what's keeping object alive]
Root Cause Analysis
Leak Pattern Identified
Pattern: [e.g., EventEmitter leak, closure trap, unclosed connection, etc.]
Vulnerable Code (before fix):
// File: [filepath]:[line]
// [Brief explanation of why this leaks]
[Paste vulnerable code here]
Why This Leaks:
- [Step 1 of how the leak occurs]
- [Step 2]
- [Result: memory accumulates]
Reproduction Steps
- [Step to reproduce leak in dev/staging]
- [Step 2]
- [Observed result: memory growth]
Reproduction Time: [How long to observe leak? Minutes/hours]
Fix Implementation
Code Changes
Pull Request: [Link to PR]
Files Modified:
- [file1.ts] - [Brief description of change]
- [file2.ts] - [Brief description of change]
Fixed Code:
// File: [filepath]:[line]
// [Brief explanation of fix]
[Paste fixed code here]
Fix Strategy:
- Remove event listeners (use
removeListener()oronce()) - Close connections (use context managers or
try/finally) - Clear timers (use
clearInterval()/clearTimeout()) - Use WeakMap/WeakSet (for cache)
- Implement generator/streaming (for large datasets)
- Other: ___
Testing and Validation
Tests Added:
// Test that verifies no leak
describe('Memory leak fix', () => {
it('should not leak listeners', () => {
const before = emitter.listenerCount('event');
// ... execute code
const after = emitter.listenerCount('event');
expect(after).toBe(before); // No leak
});
});
Load Test Results:
Before fix:
- Memory after 1000 requests: X MB
- Memory after 10000 requests: Y MB (growth)
After fix:
- Memory after 1000 requests: X MB
- Memory after 10000 requests: X MB (stable)
Deployment and Results
Deployment Details
Environment: [staging/production] Deployment Time: [YYYY-MM-DD HH:MM UTC] Rollout Strategy: [Canary, blue-green, rolling, etc.]
Post-Deployment Metrics
Before Fix:
Memory baseline: X MB
Memory after 6h: Y MB
Growth rate: Z MB/hour
OOM incidents: N/week
After Fix:
Memory baseline: X MB
Memory after 6h: X MB (stable!)
Growth rate: 0 MB/hour
OOM incidents: 0/month
Improvement:
- Memory reduction: [X% or Y MB]
- OOM elimination: [100%]
- GC pressure: [Reduced by X%]
Grafana Dashboard
Link: [Dashboard URL]
Key Panels:
- Heap usage trend: [Shows memory stable after fix]
- GC pause duration: [Shows improved GC behavior]
- Error rate: [Shows OOM errors eliminated]
Lessons Learned
What Went Well
- [Positive aspect 1]
- [Positive aspect 2]
What Could Be Improved
- [Improvement area 1]
- [Improvement area 2]
Preventive Measures
Monitoring Added:
- Alert: Memory growth >X MB/hour for >Y hours
- Alert: Heap usage >Z% of limit
- Dashboard: Memory trend visualization
- Alert: Connection pool saturation >X%
Code Review Checklist Updated:
- Event listeners properly cleaned up
- Database connections closed
- Timers/intervals cleared
- Large datasets processed with streaming/chunking
Testing Standards:
- Memory leak tests for event listeners
- Load tests with memory monitoring
- CI/CD checks for connection cleanup
Related Documentation
- Pattern Catalog: [Link to memory-optimization-patterns.md]
- Similar Incidents: [Links to previous memory leak reports]
- Runbook: [Link to memory leak runbook]
Appendix
Heap Snapshot Files
- [snapshot1.heapsnapshot] - [Location/S3 URL]
- [snapshot2.heapsnapshot] - [Location/S3 URL]
GC Logs
[Relevant GC log excerpts showing the leak]
Prometheus Queries
# Memory growth rate
rate(nodejs_heap_used_bytes[1h])
# GC pause duration
histogram_quantile(0.95, rate(nodejs_gc_duration_seconds_bucket[5m]))
Report Completed: [YYYY-MM-DD] Next Review: [Date for follow-up validation]