datadog/go-profiler-notes

felixge's notes on the various go profiling methods that are available.

View on GitHub ↗Jump to charts ↓

Summary Information

Updated 16 minutes ago
Type:Documentation / SpecificationCategory(s):Debugging & ProfilingObservability & MonitoringDeveloper Tools
Added to GitGenius on September 19th, 2026
Created on January 7th, 2021
Open Issues & Pull Requests: 3 (+0)
GitHub issues: Enabled
Number of forks: 218
Total Stargazers: 3,664 (+0)
Total Subscribers: 86 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 6.9 days
Mean response time: 31.5 days
90th percentile: 56.2 days
Tracked items: 2

Most active contributors

Sign in to see contributor activity.

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Open issues: 0
New in 7 days: 0
Closed in 7 days: 0
Avg open age: N/A days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

No label distribution available yet.

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

go-profiler-notes is a collection of educational reference materials that explains how Go's profiling tools and methods work.

The repository addresses the gap between Go's rich profiling capabilities and the lack of accessible documentation about what profiling data actually means. Rather than building a tool, it provides detailed written explanations and guides covering the mechanics of Go's profilers, the pprof format and tooling, stack traces as a foundational system for profiling, goroutine profiling for inspecting active goroutines, and block profiling for measuring time spent waiting on channels and locks. The material is structured to help developers understand not just how to use these profilers but what the underlying data represents.

This resource suits developers who need to understand Go profiling deeply enough to interpret results, debug performance issues effectively, or work on profiling infrastructure. It is particularly valuable for those building observability systems or continuous profiling solutions who need to grasp the mechanics rather than just the surface-level usage. The repository complements the official Go diagnostics documentation by providing substantially more depth on individual profiling methods.

The project maintains a structured guide alongside focused deep-dives into specific profiling topics, with some areas marked as in progress. External references are actively curated to point readers toward complementary resources and official documentation. The work reflects ongoing research into Go's profiling landscape with a commitment to making that knowledge accessible to the broader community.