# rakyll/gom

A visual interface to work with runtime profiling data for Go

Repository: https://github.com/rakyll/gom
Canonical: https://ross.abutalabs.com/products/rakyll-gom
Language: Go
License: Apache-2.0
License Family: permissive
Archived: true
Last push: 2022-02-24T15:58:30+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4328, "days_push": 1651, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1276, forks 42 (observed 2026-08-28T04:04:13.032005+00:00)

## What it is
gom is a lightweight terminal-based visual interface for exploring runtime profiling data from Go programs. It connects to an HTTP endpoint exposed by your application and lets you browse, filter, and sort CPU and heap profiles interactively.

## Use cases
- view go heap profile in a terminal ui
- browse cpu profiling data from a running go service
- filter pprof profiles by symbol name regex
- quickly inspect runtime profiles without go tool pprof
- sort profile samples by cumulative time
- explore profiling data of a live go application

## When to choose
- you want a simpler, interactive alternative to go tool pprof for runtime profiles
- you need to filter and sort profile entries by symbol names quickly
- you prefer a lightweight terminal ui over command-line pprof flags

## When to avoid
- you need advanced pprof features like flame graphs or graphical output
- your go program cannot expose an http endpoint for profiling handlers
- you need actively maintained tooling with recent updates

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: monitoring, tracing, developer-tools, terminal-ui
- domain: developer-tools, performance
- platform: windows, go, cli
- tags: profiling, go-runtime, pprof, cpu-profile, heap-profile, tui, command-line, linux, macos

## Member repositories
- rakyll/gom (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:13.032005+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 2026-08-30T05:02:58.242666+00:00, confidence not recorded.
  - readme: https://github.com/rakyll/gom (fetched 2026-08-28T04:04:13.032005+00:00, sha 72e9168ac64f)
- Data as of 2026-08-30T08:39:29.467469+00:00.