When should I use benchstat?

Use benchstat after making performance-related code changes. It compares the results of 'old' and 'new' benchmark runs to determine if your optimizations resulted in a statistically significant improvement.

How do I profile CPU usage in Go with this skill?

You can use the runtime/pprof package to start a CPU profile, then analyze the output file using 'go tool pprof' to identify the functions consuming the most execution time.

What is the benefit of using sync.Pool in Go applications?

sync.Pool allows you to reuse temporary objects like byte buffers or string builders, which significantly reduces the frequency of heap allocations and lessens the load on the Garbage Collector.

What does GOMEMLIMIT do in Go?

GOMEMLIMIT (introduced in Go 1.19) sets a soft memory limit for the runtime, helping prevent Out-Of-Memory (OOM) errors by making the Garbage Collector more aggressive as the limit is approached.

Go Performance Optimization

Name: Go Performance Optimization
Author: geoffjay

bygeoffjay

•

Analytics & Monitoring

Optimizes Go application performance through profiling, efficient memory management, and runtime tuning.

About

This skill provides expert-level guidance for improving the performance and efficiency of Go applications. It empowers developers to identify bottlenecks using CPU and memory profiling, implement memory-saving techniques like pre-allocation and sync.Pool, and fine-tune garbage collection and concurrency patterns. Whether you are dealing with high-latency hot paths or excessive memory usage, this skill provides the implementation patterns and benchmarking strategies needed to build high-performance, production-ready Go services.

Key Features

Memory optimization through escape analysis and zero-copy techniques
Comprehensive Benchmarking and performance comparison with benchstat
2 GitHub stars
Advanced Concurrency tuning with sharded locks and atomic operations
Runtime and Garbage Collection (GC) configuration and monitoring
CPU and Memory Profiling using pprof and execution tracing

Use Cases

Identifying and resolving CPU bottlenecks in data processing pipelines
Reducing memory allocations in high-throughput microservices
Optimizing concurrent access to shared resources to reduce lock contention

About

Key Features

Memory optimization through escape analysis and zero-copy techniques
Comprehensive Benchmarking and performance comparison with benchstat
2 GitHub stars
Advanced Concurrency tuning with sharded locks and atomic operations
Runtime and Garbage Collection (GC) configuration and monitoring
CPU and Memory Profiling using pprof and execution tracing

Use Cases

Identifying and resolving CPU bottlenecks in data processing pipelines
Reducing memory allocations in high-throughput microservices
Optimizing concurrent access to shared resources to reduce lock contention