node-clinic
FlameGraph
node-clinic | FlameGraph | |
---|---|---|
14 | 53 | |
5,566 | 16,438 | |
0.4% | - | |
3.0 | 4.5 | |
10 months ago | 16 days ago | |
JavaScript | Perl | |
MIT License | - |
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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.
node-clinic
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Why you should start profiling your application on the production
It's basic, but it works. You can see what function or 3rd library is after your resources and debug them locally (For example, by using ClinicJS - https://clinicjs.org/)
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From Good to Great: Scaling Applications with TypeORM Optimization
Clinic.js
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Measuring the performance of JSS apps
Clinic.js - performance analysis tooling.
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Node 18.x async code performance problem?
I’ve also seen some pretty bad event loop saturation causing significant delays. Run this https://clinicjs.org
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7 Best Tools for Monitoring Node.js Servers
Clinic.js includes three tools to help diagnose and pinpoint performance issues in Node.js applications. It’s surprisingly easy to use. All you need to do is install the module from npm and run it. This will generate reports for you that make troubleshooting much easier.
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GraphQL Fastify vs Apollo Server — Learnings from the real world
To compare the two servers, we used two packages. The first one was ClinicJS, an open-source set of tools used to diagnose NodeJS performance issues, which also gives you suggestions and points you in a direction to fix the diagnosed problems. The second one was hey, a CLI tool to send some load to the server. Below we show how we use them and the results of these comparisons.
- Clinic.js
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Assessing memory needs for a running NestJS application
WTF? 1.15 GB of RAM while idle, have you tried to profile the app? maybe you have some memory leaks, use node clinic to diagnose performance issues.
- Clinic.js diagnoses your Node.js performance issues
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Code Optimisation Doubt, Current code fails to handle concurrent requsts.
You can use https://clinicjs.org along with autocannon to identify bottleneck
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).
What are some alternatives?
PM2 - Node.js Production Process Manager with a built-in Load Balancer.
hotspot - The Linux perf GUI for performance analysis.
typescript-eslint - :sparkles: Monorepo for all the tooling which enables ESLint to support TypeScript
benchmark - A microbenchmark support library
autocannon - fast HTTP/1.1 benchmarking tool written in Node.js
tracing-bunyan-formatter - A Layer implementation for tokio-rs/tracing providing Bunyan formatting for events and spans.
express-status-monitor - 🚀 Realtime Monitoring solution for Node.js/Express.js apps, inspired by status.github.com, sponsored by https://dynobase.dev
HeatMap - Heat map generation tools
appmetrics - Node Application Metrics provides a foundational infrastructure for collecting resource and performance monitoring data for Node.js-based applications.
pmu-tools - Intel PMU profiling tools
Transcrypt - Python 3.9 to JavaScript compiler - Lean, fast, open! -
etcd - Distributed reliable key-value store for the most critical data of a distributed system