golang-performance

Go Performance Optimization

Overview

This skill provides comprehensive guidance for profiling, benchmarking, and optimizing Go applications. Use this skill when working on performance-critical code, investigating bottlenecks, or optimizing production systems.

When to Use This Skill:

• Profiling application performance
• Benchmarking code changes
• Investigating memory leaks or high allocations
• Optimizing hot paths
• Tuning garbage collection
• Reducing latency in production

Core Tools:

• pprof - CPU, memory, and goroutine profiling
• go test -bench - Benchmarking framework
• go build -gcflags - Escape analysis
• GOGC and GOMEMLIMIT - GC tuning

---

1. Profiling with pprof

1.1 CPU Profiling

Enable CPU Profiling in Code:

import (
    "os"
    "runtime/pprof"
)

func main() {
    f, err := os.Create("cpu.prof")
    if err != nil {
        log.Fatal("could not create CPU profile: ", err)
    }
    defer f.Close()

    if err := pprof.StartCPUProfile(f); err != nil {
        log.Fatal("could not start CPU profile: ", err)
    }
    defer pprof.StopCPUProfile()

    // Your application code here
    runApplication()
}

CLI Profiling:

# Profile a test
go test -cpuprofile=cpu.prof -bench=.

# Profile a binary
go test -c
./myapp.test -test.cpuprofile=cpu.prof -test.bench=.

Analysis Commands:

# Interactive web UI (recommended)
go tool pprof -http=:8080 cpu.prof

# Text output - top functions by CPU time
go tool pprof -top cpu.prof

# Top 20 with cumulative time
go tool pprof -top -cum cpu.prof | head -20

# Call graph visualization
go tool pprof -svg cpu.prof > cpu.svg

# Focus on specific function
go tool pprof -focus=processData cpu.prof

# Exclude standard library
go tool pprof -ignore=runtime cpu.prof

Interpreting CPU Profiles:

• flat: Time spent in function itself (excludes callees)
• flat%: Percentage of total runtime
• sum%: Cumulative percentage
• cum: Time spent in function and callees
• cum%: Cumulative time percentage