The Clinic.js Workshop

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The Clinic.js Workshop video covers essential tools for diagnosing and optimizing Node.js application performance. It introduces Clinic.js, a suite of tools including Clinic Doctor, Clinic Flame, and Clinic BubbleProf, which help identify issues such as CPU bottlenecks and event loop delays. The workshop emphasizes the importance of establishing a baseline using tools like AutoCannon, which simulates HTTP requests to measure server performance. MongoDB optimization is discussed, highlighting the need for indexing to improve query performance. The video also explores using Fastify for HTTP servers and the importance of running performance tests on dedicated machines. Additional tools and techniques such as flame graphs, promise.all for asynchronous operations, and handling concurrent client requests are also discussed.

From Author:

Learn the ways of the clinic suite of tools, which help you detect performance issues in your Node.js applications. This workshop walks you through a number of examples, and the knowledge required to do benchmarking and debug I/O and Event Loop issues.

This workshop has been presented at JSNation 2022, check out the latest edition of this JavaScript Conference.

FAQ

Rafael Gonzaga is a Node.js core member, Clinic.js core member, and a performance engineer at NearForm. He is based in Brazil and has a strong affinity for C++.

Rafael Gonzaga is a member of Node.js core, Clinic.js core, and NearForm.

The prerequisites for the workshop include Node.js version 16, Docker, and a clean installation of Clinic.js. Node.js version 18 might work but is not officially supported due to V8 changes.

Clinic.js is a suite of tools designed to help diagnose performance issues in Node.js applications. It includes tools like Clinic Doctor, Clinic Flame, Clinic BubbleProf, and Clinic Heap Profiler.

You can install Clinic.js by running the command 'npm install -g clinic'. After installation, you can use 'clinic --help' to see available commands.

Clinic Doctor is used as an entry point for diagnosing performance issues in Node.js applications. It helps identify symptoms such as low CPU usage, blocking garbage collection, and frequent event loop blocks.

A flame graph is a visualization tool used in Clinic Flame to identify which functions are consuming the most CPU time. The x-axis represents time spent, while the y-axis represents the call stack.

If Clinic Doctor detects an event loop issue, the recommendation is to use Clinic Flame to identify the specific functions causing the problem.

To improve MongoDB query performance, you can add indexes to your collections to avoid full table scans (co-scans). This significantly reduces query time.

Establishing a baseline is crucial because it provides a point of comparison to measure improvements. Without a baseline, it's difficult to quantify how much performance has been enhanced.

Rafael Gonzaga
Rafael Gonzaga
71 min
04 Jul, 2022

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Video Transcription

Available in Español: El Masterclass de Clinic.js
Video transcription and chapters available for users with access.

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