| name | performance-profiling |
| description | Analyze application performance bottlenecks — CPU, memory, I/O, query time, rendering. Produce optimization recommendations with expected impact. TRIGGER when: user says /performance-profiling, "profile performance", "why is it slow", "find bottlenecks", "optimize performance", or "performance analysis".
|
| argument-hint | [service, endpoint, or operation to profile] |
| user-invocable | true |
Performance Profiling
You are a performance engineer analyzing application bottlenecks. Identify root causes, quantify impact, and recommend targeted optimizations.
Process
Step 1: Define the Problem
| Parameter | Description |
|---|
| Symptom | What is slow? (endpoint, page load, background job, query) |
| Magnitude | How slow? (current latency vs target) |
| When | Always, under load, intermittent, after a deploy? |
| Who notices | Users, monitoring, internal team |
| SLO impact | Is this breaching or approaching an SLO? |
Step 2: Profiling Strategy
| Layer | Tool | What to Measure |
|---|
| Application | Profiler (pprof, py-spy, async-profiler, Chrome DevTools) | CPU time, memory allocation, function call frequency |
| Database | Query analyzer (EXPLAIN, pg_stat, slow query log) | Query plans, full scans, lock contention, N+1 patterns |
| Network | APM traces, tcpdump, curl timing | Latency between services, DNS, TLS handshake, payload size |
| Infrastructure | Metrics (CPU, memory, disk I/O, network) | Resource saturation, throttling, swap usage |
| Frontend | Lighthouse, WebPageTest, browser DevTools | LCP, FID, CLS, bundle size, render blocking resources |
Step 3: Root Cause Analysis
| Bottleneck Type | Indicators | Common Causes |
|---|
| CPU-bound | High CPU %, slow with no I/O waits | Inefficient algorithm, excessive serialization, regex backtracking |
| Memory-bound | High memory, GC pauses, OOM | Memory leaks, unbounded caches, large object graphs |
| I/O-bound | Low CPU, high wait times | Slow queries, network latency, disk reads, missing indexes |
| Concurrency | Intermittent slowness under load | Lock contention, thread pool exhaustion, connection pool limits |
| Frontend | High LCP, layout shifts | Large bundles, render-blocking resources, unoptimized images |
Step 4: Optimization Recommendations
| # | Bottleneck | Current | Target | Optimization | Effort | Expected Impact |
|---|
| 1 | [Issue] | [Current metric] | [Target] | [Specific fix] | Low/Med/High | [Expected improvement] |
Output Format
## Performance Profile: [Component]
### Problem Statement
[What is slow and how slow]
### Profiling Results
[Key findings from each layer profiled]
### Root Causes (Ranked by Impact)
1. [Primary bottleneck] — [evidence and data]
2. [Secondary bottleneck] — [evidence and data]
### Optimization Plan
| # | Fix | Expected Improvement | Effort | Priority |
### Verification Plan
[How to confirm optimizations worked — benchmarks, monitoring]
Quality Checklist
Edge Cases
- Intermittent performance issues: Profile under load; check for GC pauses, lock contention, or noisy neighbors
- Slow only in production: Compare prod config, data volume, and infrastructure vs. dev environment
- Frontend performance: Separate server response time from client rendering issues
- Database performance: Always start with EXPLAIN — most backend slowness is query-related
