Performance Issues

Summary

This page documents how you can help us to track down performance issues. It contains:

• Questions about your setup
• Experiments you can make to reproduce and narrow down
• Measurements you can provide us for further analysis.

Questions

To help us narrow down the issue please include answers for the following questions:

• What is the size of your workspace/project (how many files)?
• What languages are used in this project?
• Do you run Code on a single-CPU environment (e.g. VM)? We know that processes can go crazy and startup times can be super slow.
• Which Code process consumes consumes the most resources? VS Code is a multi process architecture and we need to know which process is causing the issue. You can identify the process based on the command line arguments that were used to start the process. On Mac, the Activity Monitor allows to find the PID of the process and from a terminal you can run ps aux | grep <pid> reveals its arguments. On Windows open the Task Manager, switch to the Details tab and make the "Command Line" column visible as shown below. Please attach the command line to this issue.

Experiments

Please try to reproduce the performance problems in different setups:

• Can you reproduce the issue when you start VS Code with extensions disabled? You can start VS Code with extension disabled using the --disable-extensions command line argument, e.g., code --disable-extensions.

• If you cannot reproduce the issue when the extensions are disabled, then can you narrow down the extension by selectively disabling extensions? You can disable extensions in the Extensions Viewlet and restart/reload. Once you found the extension please file an issue against the extension. To file an issue against an extension: find the issue in the market place, select the Issues link thin the Resources section.

• Try to reproduce the problem on different folders; a folder with less files, a folder that is not under source control, or open a single file?

• Try to reproduce the issue in the VS Code Insider version. This will run our latest code and use a different setup (settings, extensions). You can install the insider version here https://code.visualstudio.com/insiders.

• Run VS Code when your settings are reset/empty. Open your settings, copy your customizations and then emtpy the JSON contents so that only {} is left.

• Run VS Code in verbose mode and check whether there is any suspicious output in the console or the developer tools. You start VS Code in verbose mode with code --verbose. Also open the DevTools ("Help>Toggle Developer Tools") and open the console there.

Measurements

When you cannot share the workspace exposing the problem with us, then you can help us by providing performance profiles that we can analyze:

• If VS Code feels not responsive then please create a CPU profile of the VS Code core (renderer process) and attach it to the issue. To create a profile:

  • Execute "F1 > Toggle Developer Tools." In the overflow menu of the developer tools
  • Select 'More Tools > JavaScript Profiler'. In there select start.
  • Let it profile for 30 to 60 seconds, stop it.
  • When the performance issue happens on startup, start the profiler and then reload the window using "F1>Reload Window."
  • Save the profile to a file and attach the file to your issue.

• If VS Code feels not responsive and the CPU profile doesn't provide insights then please a create a CPU profile of the extension host process. The extension host process is the process that executes your installed extensions. To create a profile:

  • Start VS Code from the command line the with --inspect-extensions=<port>-flag, for example code --inspect-extensions=9333.
  • In VS Code, from the 'Command Palette (F1)', select 'Developer: Toggle Developer Tools', hit Enter.
  • Select the Console tab and find a message that starts with "Debugger listening on port 9333" and that ends with a chrome-devtools-link.
  • Open that link in Chrome for dedicated DevTools for the extension host.
  • Use the Memory and CPU profiler to understand how memory and compute resource are being used.
  • Save the profile to a file and attach the file to your issue.