The Firefox Profiler visualizes performance data recorded from web browsers. It is a tool designed to consume performance profiles from the Gecko Profiler but can visualize data from any profiler able to output in JSON. The interface is a web application built using React and Redux and runs entirely client-side.
Mozilla develops this tool to help make Firefox silky smooth and fast for millions of its users, and to help make sites and apps faster across the web.
This project was previously called perf.html and Cleopatra.
Visit profiler.firefox.com 🚀
This project is live on https://profiler.firefox.com/. The website includes instructions on how to get going to start recording and viewing performance profiles.
You will need a recent enough version of Yarn, version 1.0.1 is known to work correctly. You can install it into your home directory on Linux and probably OS X with:
cd /tmp
wget https://yarnpkg.com/install.sh
chmod a+x install.sh
./install.shTo download and build the Firefox Profiler web app run:
git clone [email protected]:firefox-devtools/profiler.git
cd firefox-profiler
yarn install
yarn startYou can also develop the Firefox Profiler online in a pre-configured development environment:
For more detailed information on getting started contributing. We have plenty of docs available to get you started.
| Contributing | Find out in detail how to get started and get your local development environment configured. |
| Code of Conduct | We want to create an open and inclusive community, we have a few guidelines to help us out. |
| Developer Documentation | Want to know how this whole thing works? Get started here. |
| Source Files | Dive into the inner workings of the code. Most folders have a README.md providing more information. |
| Gecko Profiler Addon | The Firefox Profiler can record profiles directly in the browser using an add-on, development takes place in another repo. |
Say hello on slack in the #perf channel.
Some permissive software licenses request but do not require an acknowledgement of the use of their software. We are very grateful to the following people and projects for their contributions to this product:
- The zlib compression library (Jean-loup Gailly, Mark Adler and team)