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google
pprof
Go2018–2025
google / pprof

pprof

pprof is a tool for visualization and analysis of profiling data

9Distinct people
13Mentions
0Explicit recommenders
9.3KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

pprof is a tool for visualization and analysis of profiling data

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 10:56:20 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year13 dated mentions

Observed mentions: 2018-03-11 22:58:04 UTC to 2025-07-10 15:35:20 UTC.

012342018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC413
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC202
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC110
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC303
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC303

What Hacker News says

3 sources
Damn I hate it when you write a whole project and someone comes along and says "this already exists" and you realise how much time you wasted (yeah even if some of it counts towards learning I'd still rather not needlessly repeat other people's work). Anyway, pprof has a fantastic interactive Flamegraph viewer that lets you narrow down to specific functions. It's really very good, I would use that. https://github.com/google/pprof Run `pprof -http=:` on a profile and you get a web interface with the Flamegraph, call graph, line based profiling etc. It's demonstrated in this video. https://youtu.be/v6skRrlXsjY They only show a very simple example and no zooming, but it works very well with huge flamegraphs.
In Navtive FlameGraphViewer
How do flame graphs handle the case where most of the time is spent in some leaf function that is called from all over the program? In this case, each individual stack would not take much time but in aggregate, a lot of time is spent in the function at the top of all of the call stacks. This should not be that uncommon to have hotspots in things like copying routines, compression, encryption etc that are not associated with any particular stack. pprof from https://github.com/google/pprof can produce a DAG view of a profile where nodes are sized proportional to their cumulative time, e.g., https://slcjordan.github.io/images/pprof/graphviz.png and such a view would seem to cover the case above and subsume the usual use cases for a flame graph, would it not? Although I guess a flat text profile of functions sorted by time would also highligh
Read the rest
t these kinds of hot spots. Still, if we want a single graphical view as a go-to, it's not clear that flame graphs are all that much better than pprof DAGs.
In Flame Graphs: Making the opaque obvious (2017)
The pprof format is not tied to Go. From my understanding, it's used within Google across multiple languages. The format is defined in the pprof repository[0], and the visualization tool is source-language agnostic. I've seen libraries in numerous languages (e.g. Python, Java) to publish profiles in pprof format. This is an indicator the pprof format has become de-facto. Grafana Pyroscope[1] is a tool that's capable of parsing the pprof format, agnostic to the source programming language, and has instructions for Go, Java, Python, Ruby, node.js, Rust, and .NET. My understanding is that you're searching for a combination of the profiles, metrics, and tracing. Caddy supports all 3. [0] https://github.com/google/pprof/blob/main/doc/README.md [1] https://grafana.com/docs/pyroscope/latest/ metrics and tracing need to be manually enabled (for
Read the rest
now, perhaps)
In Profiling Caddy

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