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:

/catalyst-dev: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

/catalyst-dev: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: /catalyst-debugging:debug-production-error, /catalyst-debugging:error-impact-analysis