# astavonin/go-optimization-guide

Go Optimization Guide: Patterns and Techniques for Writing High-Performance Applications with Go

Repository: https://github.com/astavonin/go-optimization-guide
Canonical: https://ross.abutalabs.com/products/go-optimization-guide
Homepage: http://goperf.dev
Language: Markdown
License: CC-BY-4.0
License Family: other
Topics: go, golang, network-programming, networking, optimization, performance, performance-optimization, performance-tuning
Last push: 2026-03-11T10:56:45+00:00

## Health v2 (maintenance only)
Score: 52/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 71, release rhythm 35, longevity 37
- inputs: {"age_days": 531, "days_push": 175, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1134, forks 53 (observed 2026-08-28T04:03:43.242560+00:00)

## What it is
A long-form technical guide (published at goperf.dev, built with MkDocs Material) covering patterns and techniques for writing high-performance Go applications. It focuses on practical, measured optimizations for real production systems such as high-throughput APIs, microservices, and distributed services.

## Use cases
- optimize Go API performance under sustained traffic
- reduce allocation pressure on hot paths in Go
- learn when sync.Pool actually helps
- improve tail latency in distributed Go services
- understand Go runtime scheduling and I/O costs
- tune network programming performance in Go
- reduce garbage collection overhead in Go microservices

## When to choose
- you run Go services under real production load and want measured, practical optimization patterns
- you need concrete examples with numbers rather than folklore best practices
- you work on high-throughput APIs, pipelines, or latency-sensitive distributed systems in Go

## When to avoid
- your Go code lives only in benchmarks or toy projects
- you need a beginner tutorial on writing Go rather than performance tuning
- you want a tool or library rather than reading material

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools, documentation, benchmarking
- domain: developer-tools, performance, backend, tutorials
- platform: go, cli
- tags: go-performance, optimization-guide, mkdocs, network-programming, tail-latency, memory-allocations, profiling, web-server

## Member repositories
- astavonin/go-optimization-guide (main) score 52

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:43.242560+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:36:54.502889+00:00, confidence not recorded.
  - readme: https://github.com/astavonin/go-optimization-guide (fetched 2026-08-28T04:03:43.242560+00:00, sha f8718d982a59)
  - homepage: http://goperf.dev (fetched 2026-08-29T12:41:50.370375+00:00, sha e7f2fd277583)
- Data as of 2026-08-30T08:39:29.467469+00:00.