pprof
tracy
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pprof | tracy | |
---|---|---|
12 | 57 | |
7,450 | 7,814 | |
2.5% | - | |
7.6 | 9.6 | |
1 day ago | 8 days ago | |
Go | C++ | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pprof
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Profiling Caddy
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 now, perhaps)
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Why So Slow? Using Profilers to Pinpoint the Reasons of Performance Degradation
Because we couldn't identify the issue using the results we got from Callgrind, we reached for another profiler, gperftools. It's a sampling profiler and therefor it has a smaller impact on the application's performance in exchange for less accurate call statistics. After filtering out the unimportant parts and visualizing the rest with pprof, it was evident that something strange was happening with the send function. It took only 71 milliseconds with the previous implementation and more than 900 milliseconds with the new implementation of our Bolt server. It was very suspicious, but based on Callgrind, its cost was almost the same as before. We were confused as the two results seemed to conflict with each other.
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Improving the performance of your code starting with Go
github.com - google/pprof
- Proposal to Support Timestamps and Labels in Pprof Events
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A Generic Approach to Troubleshooting
The application performances in a specific code path (e.g. gdb, pprof, …).
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Does rust have a visual analysis tool for memory and performance like pprof of golang?
pprof is https://github.com/google/pprof, it's a very useful tool in golang , and really really really convenient
- pprof - tool for visualization and analysis of profiling data
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Tokio Console
Go also has pretty good out of the box profiling (pprof[0]) and third-party runtime debugging (delv[1]) that can be used both remotely and local.
These tools also have decent editor integration and can be use hand in hand:
https://blog.jetbrains.com/go/2019/04/03/profiling-go-applic...
https://blog.jetbrains.com/go/2020/03/03/how-to-find-gorouti...
[0] https://github.com/google/pprof
[1] https://github.com/go-delve/delve
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Cats and Clouds – There Are No Pillars in Observability with Yoshi Yamaguchi
And what we do in Google Cloud is that we still use the pprof. But it's a kind of forked version of the pprof because the visualization part is totally different. So we give that tool as the Cloud Profiler. So that is the product name. And then, the difference between the pprof and a Cloud Profiler is that Cloud Profiler provides the agent library for each famous programming language such as Java, Python, Node.js, and Go. And then what you need to do is to just write 5 to 10 lines of code in a new application. That launches the profile agent in your application as a subsidiary thread of the main thread. And then, that thread periodically collects the profile data of the application and then sends that data back to Google Cloud and the Cloud Profiler.
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Is there a way I can visualize all the function calls made while running the project(C++) in a graphical way?
gprftools (https://github.com/gperftools/gperftools) can be easily plugged in using LD_PRELOAD and signal, and has nice go implemented visualization tool https://github.com/google/pprof.
tracy
- Tracy: Real-time nanosecond resolution frame profiler
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Google/orbit – C/C++ Performance Profiler
i don't really think there is _anything_ that comes even close to tracy https://github.com/wolfpld/tracy.
on top of this, given google's penchant for dumping projects aka abandonware, this would be an easy pass.
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Immediate Mode GUI Programming
The RemedyBG debugger (https://remedybg.handmade.network/) and the Tracy profiler (https://github.com/wolfpld/tracy) both use Dear ImGui and so far I've only read high praise from people who used those tools compared to the 'established' alternatives.
For tools like this, programmers are also just "normal users", and from the developer side, I'm sure they evaluated various alternatives with all their pros and cons before settling for Dear ImGui.
- Tracy Profiler
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Tuning Linux for Performance
Not the person you asked, but generally you might want to look at "frame-based" profilers. These are typically used in video games, but the concept is general, and can apply to other applications. The "frame" could also be something like a request or transaction being processed. I like Tracy[1], myself.
Another latency metric that you'll see, often w/respect to web apps and microservices is "P99" and similar. This is the amount of time in which 99% of requests get their response. For a higher percentile, you get a better idea of worst-case performance.
[1] https://github.com/wolfpld/tracy
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What is your favourite profiling tool for C++?
I've not actually used Superluminal, but I use Tracy for similar reasons. It's free though (and, importantly, open source).
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My first game engine
For profiling, you can check tracy.
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I got my procedural city engine / game (built from scratch in c++) running on the steam deck - does it look too garish?
You could try Tracy
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Sharing Saturday #462
There is no such thing as overengineering in fun projects, so I've also adopted Tracy as profiling solution. Works quite nice and gonna save me plenty of times in the future debugging performance spikes on badly optimized math heavy operations.
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Debugging and profiling embedded applications.
I know about tools such as tracing, jaeger or tracy. While having a complete tracing could be a potential solution, these tools don't work with no_std.
What are some alternatives?
gperftools - Main gperftools repository
optick - C++ Profiler For Games
prometheus - The Prometheus monitoring system and time series database.
orbit - C/C++ Performance Profiler
jaeger - CNCF Jaeger, a Distributed Tracing Platform
palanteer - Visual Python and C++ nanosecond profiler, logger, tests enabler
parca - Continuous profiling for analysis of CPU and memory usage, down to the line number and throughout time. Saving infrastructure cost, improving performance, and increasing reliability.
parallel-hashmap - A family of header-only, very fast and memory-friendly hashmap and btree containers.
massif-visualizer - Visualizer for Valgrind Massif data files
STL - MSVC's implementation of the C++ Standard Library.
heaptrack - A heap memory profiler for Linux