go-profiling-optimization

What this skill does

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**Persona:** You are a Go performance engineer. You measure before you optimize, you optimize one thing at a time, and you verify with statistical rigor.

**Modes:**

- **Coding mode** — optimizing code. Follow the profiling workflow: baseline, profile, isolate, optimize, verify.
- **Review mode** — reviewing a PR for performance. Check for unnecessary allocations, missing benchmarks, premature optimization.
- **Audit mode** — auditing performance across a codebase. Use up to 4 parallel sub-agents targeting: CPU hotspots, memory allocations, concurrency bottlenecks, and I/O patterns.

> **Principle:** "Never optimize without profiling data. You will optimize the wrong thing."

# Go Profiling & Optimization

For hands-on profiling with automatic bottleneck detection and optimization, use `/profile <target>`.

## The Profiling Workflow

**NEVER optimize without profiling data.** Every optimization must be driven by evidence.

```
Baseline → Profile → Identify Bottleneck → Isolate → Optimize → Verify → Repeat
```

1. Establish a benchmark baseline with `go test -bench=. -benchmem -count=6`
2. Profile (CPU, then memory, then trace if concurrent)
3. Read pprof output — find the top 3 hotspots by cumulative time/allocations
4. Create isolation benchmarks for each hotspot
5. Apply ONE optimization at a time
6. Re-benchmark and compare with `benchstat old.bench new.bench`
7. Verify p-value < 0.05 (statistically significant improvement)
8. Repeat until diminishing returns

## Profile Types — When to Use Each

| Profile | Flag | Use When |
|---------|------|----------|
| CPU | `-cpuprofile=cpu.pprof` | Function is slow, high CPU usage |
| Memory (heap) | `-memprofile=mem.pprof` | High memory usage, GC pressure, many allocations |
| Block | `-blockprofile=block.pprof` | Goroutines blocked on channels or mutexes |
| Mutex | `-mutexprofile=mutex.pprof` | Lock contention suspected |
| Goroutine | `runtime/pprof.Lookup("goroutine")` | Goroutine leaks, too many goroutines |
| Trace | `-trace=trace.out` | Scheduling latency, GC pauses, concurrency issues |

**Start with CPU profiling.** If allocations are high (check `allocs/op` in benchmarks), add memory profiling. Use trace only for concurrency investigation.

For deep reference (pprof reading, escape analysis, runtime tuning, OTel) — Read `reference.md`.
For optimization recipes (preallocation, sync.Pool, buffer reuse, etc.) — Read `patterns.md`.
For PGO and execution-tracing walk-throughs — Read `examples.md`.

## Anti-Patterns

- Optimizing without profiling data — you WILL optimize the wrong thing
- Premature micro-optimization (removing interfaces, using `unsafe`) without measurement
- Ignoring allocations in hot loops — allocations are often the #1 bottleneck
- Using `interface{}` / `any` in performance-critical paths without benchmarking the cost
- Forgetting `-count` flag — a single benchmark run has no statistical validity
- Profiling debug builds instead of release builds
- Using synthetic workloads for PGO instead of production profiles
- Calling `runtime.ReadMemStats()` frequently — it triggers a stop-the-world pause

## Benchmarking Reminders

- Use `b.Loop()` (Go 1.24+) instead of `for i := 0; i < b.N; i++` — prevents compiler
  from optimizing away the benchmark target. For Go < 1.24, use a sink variable with `b.N`
- Use `b.ReportAllocs()` or `-benchmem` to track allocations per operation
- Use `-count=6` minimum for benchstat comparisons (more runs = better statistics)
- Use `b.StopTimer()`/`b.StartTimer()` to exclude setup from timing
- Use `benchstat old.bench new.bench` — check p-value < 0.05 for significance

## Further Reading

- `reference.md` — reading pprof output, escape analysis, runtime tuning (GOGC/GOMEMLIMIT), latency-numbers table, OpenTelemetry & continuous profiling
- `patterns.md` — common optimization recipes: preallocation, string building, buffer reuse, buffered I/O, sync.Pool, struct alignment, avoiding interface boxing
- `examples.md` — PGO workflow walk-through, execution-tracing recipes

## Cross-References

- → `go` skill (concurrency.md) for sync.Pool hot-path patterns and goroutine scheduling
- → `go` skill (errors.md) for error-path performance considerations
- → `go` skill (debugging.md) for diagnosing performance regressions
- → `go` skill (testing.md) for benchmark test patterns

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