Agent skill

go-performance

Go performance optimization - profiling, benchmarks, memory management

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/productivity/go-performance

SKILL.md

Go Performance Skill

Optimize Go application performance with profiling and best practices.

Overview

Comprehensive performance optimization including CPU/memory profiling, benchmarking, and common optimization patterns.

Parameters

Parameter Type Required Default Description
profile_type string yes - Type: "cpu", "memory", "goroutine", "block"
duration string no "30s" Profile duration

Core Topics

pprof Setup

go
import (
    "net/http"
    _ "net/http/pprof"
)

func main() {
    // Start pprof server
    go func() {
        http.ListenAndServe("localhost:6060", nil)
    }()

    // Your application
    runApp()
}

CPU Profiling

bash
# Collect 30s CPU profile
go tool pprof http://localhost:6060/debug/pprof/profile?seconds=30

# Interactive commands
(pprof) top 10          # Top 10 CPU consumers
(pprof) list funcName   # Source view
(pprof) web             # Open in browser
(pprof) svg > cpu.svg   # Export SVG

Memory Profiling

bash
# Heap profile
go tool pprof http://localhost:6060/debug/pprof/heap

# Allocs since start
go tool pprof http://localhost:6060/debug/pprof/allocs

(pprof) top --cum       # By cumulative allocations
(pprof) list funcName   # Where allocations happen

Benchmarking

go
func BenchmarkProcess(b *testing.B) {
    data := setupData()

    b.ResetTimer()
    b.ReportAllocs()

    for i := 0; i < b.N; i++ {
        Process(data)
    }
}

func BenchmarkProcess_Parallel(b *testing.B) {
    data := setupData()

    b.RunParallel(func(pb *testing.PB) {
        for pb.Next() {
            Process(data)
        }
    })
}
bash
# Run benchmarks
go test -bench=. -benchmem ./...

# Compare benchmarks
go test -bench=. -count=5 > old.txt
# make changes
go test -bench=. -count=5 > new.txt
benchstat old.txt new.txt

Memory Optimization

go
// Preallocate slices
func ProcessItems(items []Item) []Result {
    results := make([]Result, 0, len(items)) // Preallocate
    for _, item := range items {
        results = append(results, process(item))
    }
    return results
}

// Use sync.Pool for frequent allocations
var bufferPool = sync.Pool{
    New: func() interface{} {
        return new(bytes.Buffer)
    },
}

func GetBuffer() *bytes.Buffer {
    buf := bufferPool.Get().(*bytes.Buffer)
    buf.Reset()
    return buf
}

func PutBuffer(buf *bytes.Buffer) {
    bufferPool.Put(buf)
}

Escape Analysis

bash
# Check what escapes to heap
go build -gcflags="-m -m" ./...

# Common escapes
# - Returning pointers to local variables
# - Storing in interface{}
# - Closures capturing variables

Optimization Patterns

go
// String building - use strings.Builder
var b strings.Builder
for _, s := range parts {
    b.WriteString(s)
}
result := b.String()

// Avoid interface{} in hot paths
// Use generics or concrete types

// Reduce allocations in loops
buffer := make([]byte, 1024)
for {
    n, err := reader.Read(buffer)
    // reuse buffer
}

Profiling Commands

bash
# Goroutine profile (leak detection)
go tool pprof http://localhost:6060/debug/pprof/goroutine

# Block profile (contention)
go tool pprof http://localhost:6060/debug/pprof/block

# Mutex profile
go tool pprof http://localhost:6060/debug/pprof/mutex

# Trace (detailed execution)
curl -o trace.out http://localhost:6060/debug/pprof/trace?seconds=5
go tool trace trace.out

Troubleshooting

Failure Modes

Symptom Cause Fix
High CPU Hot loop, GC Profile, reduce allocs
High memory Leak, no pooling Heap profile, sync.Pool
Slow start Large init Lazy initialization
GC pauses Many allocations Reduce allocations

Usage

Skill("go-performance")

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