FlameGraph
speedscope
FlameGraph | speedscope | |
---|---|---|
53 | 5 | |
16,438 | 5,206 | |
- | - | |
4.5 | 7.0 | |
16 days ago | 17 days ago | |
Perl | TypeScript | |
- | MIT License |
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.
FlameGraph
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JVM Profiling in Action
We'll use async-profiler and flame graphs for profiling. To simplify the process, we'll run the code using JBang.
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Memray – A Memory Profiler for Python
And flame graphs excel and this kind of thing
https://www.brendangregg.com/flamegraphs.html
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All my favorite tracing tools: eBPF, QEMU, Perfetto, new ones I built and more
which can output in a format understood by Brendan Gregg's flame frames (https://www.brendangregg.com/flamegraphs.html)
But that's not quite the kind of tracing you're talking about. We also built a printf-style interface to our recording files, which seems closer:
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Recap of Werner Vogels' Keynote at re:Invent 2023
Strategies included discontinuing or resizing underutilized services, transitioning to more cost-effective solutions, reducing the current resources to the amount of resources that we need for our application, and conducting detailed analyses of computing resource utilization through tools like flamegraphs. This detailed scrutiny helped identify and rectify significant cost-driving areas, such as garbage collection and application configurations.
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Pinpoint performance regressions with CI-Integrated differential profiling
Flame Graphs by Brendan Gregg
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Flameshow: A Terminal Flamegraph Viewer
Historically brendangregg's since AIUI he basically invented flamegraphs
https://www.brendangregg.com/flamegraphs.html
So if you can make your tool eat whatever https://github.com/brendangregg/FlameGraph is fed with you're going to support a lot of existing tooling across OSes and languages.
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Introducing Flame graphs: It’s getting hot in here
“Flame graphs are a visualization of hierarchical data, created to visualize stack traces of profiled software so that the most frequent code-paths to be identified quickly and accurately.”
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Using SVG to create simple sparkline charts
SVGs are amazing for interactive visualisation too. Like Flamegraphs: https://www.brendangregg.com/flamegraphs.html
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Good example of using flame graphs to speed up java code (50x improvement)
This may be a good example of the application of a flame graph but it is not a good demonstration of flame graphs; the graph is nearly incidental. The source has an actual explanation.
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Intro to PostGraphile V5 (Part 1): Replacing the Foundations
A profiling flame graph from Graphile Crystal (a precursor to Grafast) using GraphQL.js' executor (each tick is 1ms, total: 29ms). As we removed more and more responsibilities from GraphQL.js, we ended up only using it for output. Replacing this final responsibility with a custom implementation in Graphile Crystal itself, we reduced execution time for this query down to 15.5ms (effectively removing the majority of the yellow portion of the flame graph).
speedscope
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Speeding up the JavaScript ecosystem – Polyfills gone rogue
Glad to hear you like it! Those flame graph screenshots are taken from https://www.speedscope.app/ .
- Speedscope (An Interactive Flamegraph Visualizer)
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Speeding up the JavaScript ecosystem - one library at a time
Looks like speedscope. https://www.speedscope.app/
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A Trick For Reading Flamegraphs
Flamegraphs simply visualize this process by placing each of these recorded stacks side by side. The resulting visualization looks like "flames", hence a "flame graph". If you do this visualization where the "parent" of all the stack frames is on the top, rather than the bottom, you get a "waterfall graph", because it looks like a waterfall. It's the same thing though. Speedscope and DevTools visualize using the waterfall format, but I still call them flamegraphs anyway.
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Performance Profiling a Mongoid Issue Using AppProfiler
While doing research on Ruby profiling I found Shopify's blog post on "How to Fix Slow Code in Ruby". Though the entire post was extremely insightful, it lead me to Shopify's app_profiler library, which can be used to automatically profile code and redirect the output to a local instance of speedscope. Having worked previously with Flame Graphs of CPU stack traces collected using perf.
What are some alternatives?
hotspot - The Linux perf GUI for performance analysis.
stackprof - a sampling call-stack profiler for ruby 2.2+
benchmark - A microbenchmark support library
Microsoft-Performance-Tools-Linux-Android - Linux, Android and Chromium Performance Tools built using the Microsoft Performance Toolkit. Cross-platform .NET Core + WPA GUI
tracing-bunyan-formatter - A Layer implementation for tokio-rs/tracing providing Bunyan formatting for events and spans.
app_profiler - Collect performance profiles for your Rails application.
HeatMap - Heat map generation tools
nolyfill - Speed up your package installation process, reduce your disk usage, and extend the lifespan of your precious SSD.
node-clinic - Clinic.js diagnoses your Node.js performance issues
eslint-plugin-import - ESLint plugin with rules that help validate proper imports.
pmu-tools - Intel PMU profiling tools
ljharb