4.0 KiB
4.0 KiB
description, category, tools, model, version
| description | category | tools | model | version |
|---|---|---|---|---|
| Analyze distributed traces and performance issues with Sentry | debugging | Task, TodoWrite | inherit | 1.0.0 |
Trace Analysis
Investigate distributed traces, transaction performance, and slow requests using Sentry.
Usage
/trace-analysis <trace-id-or-query>
Examples:
/trace-analysis "a4d1aae7216b47ff8117cf4e09ce9d0a"
/trace-analysis "slow API requests to /checkout"
/trace-analysis "traces with >5 second response time"
/trace-analysis "performance issues in payment service"
What This Analyzes
Trace Components
- Transaction spans (API calls, DB queries, external services)
- Timing breakdown per span
- Parent-child span relationships
- Span operations and descriptions
Performance Metrics
- Total transaction duration
- Time spent in each service
- Database query performance
- External API latency
- Network overhead
Bottleneck Identification
- Slowest spans in trace
- Sequential vs parallel operations
- N+1 query detection
- Inefficient operations
Example Analyses
Specific Trace Investigation
/trace-analysis "Analyze trace abc123def456: where's the bottleneck?"
Performance Pattern
/trace-analysis "Why are checkout API requests slow today?"
Service Comparison
/trace-analysis "Compare performance of payment service vs order service"
Database Performance
/trace-analysis "Find traces with slow database queries in user service"
Output Format
Analysis includes:
Trace Overview:
- Transaction name and operation
- Total duration
- Timestamp
- Environment and release
Span Breakdown:
Transaction: POST /api/checkout (2.4s)
├─ Authentication (45ms)
├─ Database Query: SELECT users (120ms)
├─ External API: Payment Gateway (1.8s) ⚠️ SLOW
├─ Database Query: INSERT orders (230ms)
└─ Email Service (180ms)
Performance Insights:
- Slowest operations
- Time distribution (pie chart/percentages)
- Parallel vs sequential execution
- Optimization opportunities
Recommendations:
- Cache frequently accessed data
- Optimize specific queries
- Implement async processing
- Add timeouts for external calls
Advanced Analysis
Multi-Trace Patterns
/trace-analysis "Find common bottlenecks across all slow checkout traces today"
Service Dependencies
/trace-analysis "Map service call chain for failed transactions"
Error Correlation
/trace-analysis "Traces that resulted in errors: what went wrong before?"
Integration Opportunities
With Error Debugging
# Enable debugging plugin (if not already)
/plugin enable catalyst-debugging
# Combine trace and error analysis
> "Show me the trace for the transaction that caused error ISSUE-456"
With Code Changes
After identifying bottleneck:
/create-plan "Optimize the slow payment gateway call identified in trace analysis"
Performance Optimization Workflow
1. Identify Slow Transactions
/trace-analysis "transactions with >2s response time in last hour"
2. Analyze Bottlenecks
> "Drill into the slowest trace: which span is the problem?"
3. Root Cause
> "Why is the database query taking 800ms?"
4. Implement Fix
/create-plan "Add database index for user lookups based on trace analysis"
5. Verify Improvement
> "After deploy, compare trace durations before and after"
Tips
- Start with aggregates - "slow checkouts" before diving into specific traces
- Look for patterns - One slow trace might be an outlier, many indicate systemic issue
- Check external dependencies - Third-party APIs often cause slowdowns
- Consider concurrency - Sequential operations that could be parallel
- Database queries - N+1 queries, missing indexes, inefficient queries
Context Cost
Plugin uses ~20k tokens. Disable after analysis:
/plugin disable catalyst-debugging
See also: /debug-production-error, /error-impact-analysis