The Clinic.js Workshop

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.

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Video Summary and Transcription
This video workshop dives into the tools and techniques for diagnosing performance issues in Node.js applications using Clinic.js. Participants are introduced to the essential tools within the suite, including Clinic Doctor, Clinic Flame, and Clinic BubbleProf, which are pivotal in identifying and addressing issues like CPU usage and event loop delays. The use of npm clinic is demonstrated to install the suite, making performance analysis more accessible. The workshop emphasizes the importance of establishing a baseline before optimization, using tools like AutoCano for benchmarking HTTP server performance. The session also touches on improving MongoDB query performance by adding indexes to avoid full table scans. Viewers are guided through using Clinic Flame to visualize CPU usage with flame graphs, which helps pinpoint bottlenecks in the code.

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

Available in Español: El Masterclass de Clinic.js

FAQ

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.

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

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.

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.

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

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++.

Video transcription and chapters available for users with access.
Rafael Gonzaga
Rafael Gonzaga
71 min
04 Jul, 2022

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