How to Fix Visual Studio Code Lag and High Memory Usage When Working With Large Projects — Real Fixes From Reddit Developers

Visual Studio Code (VS Code) is one of the most popular code editors among developers — and for good reason. It’s free, highly customizable, and boasts a powerful extension library. But when working with large codebases, many developers encounter two frustrating issues: lag and high memory usage. These problems can disrupt workflow, slow development, and lead to hours of unnecessary debugging just to get the editor itself working properly.

TL;DR

If you’re facing lag and memory issues in VS Code while working on large projects, you’re not alone. Real developers on Reddit have shared workable solutions that include adjusting settings like file watchers, disabling heavy extensions, and allocating system resources more efficiently. Key tweaks in settings.json, smarter file ignore rules, and lifecycle management of extensions can go a long way. Try these fixes before abandoning VS Code for “lighter” editors.

1. Disable Unnecessary Extensions

It’s tempting to install every productivity-boosting extension available in the VS Code marketplace, but overloading your editor comes at a cost. Many Reddit developers noted a dramatic speed-up after trimming their extension list. Think of extensions like browser add-ons — each one eats into your RAM and processing capacity.

Reddit solution: Perform an “extension audit.” Disable all extensions and re-enable only the ones you truly need.

  • Press Ctrl+Shift+P and search for “Extensions: Show Installed Extensions.”
  • Review each and identify which ones are essential for your current work.
  • Create workspaces with project-specific extension recommendations using .vscode/extensions.json.

Pro Tip: Extensions like Prettier, ESLint, and Python Language Server can significantly slow down performance when misconfigured. Adjust their scope or consider running them manually instead of automatically on every file save.

2. Configure File Watcher Limits

File watchers help VS Code respond to changes in the file system (like in VS Git integration), but they can overwhelm your system, especially when dealing with thousands of files across multiple directories.

Reddit solution: Set file watching exclusions in your settings to vastly improve performance.


"files.watcherExclude": {
  "/node_modules/": true,
  "/.git/": true,
  "/dist/": true,
  "/build/": true
}

Additionally, in Linux systems, users often hit the inotify limit, which restricts how many files the system can watch at once. You can increase this limit by running:


echo fs.inotify.max_user_watches=524288 | sudo tee -a /etc/sysctl.conf && sudo sysctl -p

This simple command can make a massive difference, especially for web developers with huge dependency trees.

3. Use Workspace Settings Effectively

If your project includes a lot of auto-generated files, test results, or log files, VS Code will still scan them unless told otherwise. This can bog down performance during search, indexing, and even source control commits.

Reddit solution: Create a .vscode/settings.json file at the root of your project and customize your file exclusion:


"files.exclude": {
  "/node_modules": true,
  "/dist": true,
  "/logs": true
},
"search.exclude": {
  "/node_modules": true,
  "/dist": true,
  "/logs": true
}

This tells VS Code to completely ignore unnecessary files in various processes like global search and indexing, saving you precious CPU cycles.

[ai-img]visual studio code, large project, slow editor[/ai-img]

4. Disable Unused Language Features

Language servers like TypeScript, Python, and Java IntelliSense can be memory hogs. A Reddit user working on a 500MB monorepo shared a tip that drastically cut their RAM usage: disable built-in language features when they’re not needed.

Example: If you’re working in a monorepo that includes JavaScript, Python, and Go, but you’re only actively developing in one language, consider disabling the others temporarily.


"typescript.disableAutomaticTypeAcquisition": true,
"python.analysis.autoSearchPaths": false,
"go.languageServerExperimentalFeatures": {
  "diagnostics": false
}

This prevents background processes that analyze and index sources unrelated to your work from consuming memory and CPU.

5. Optimize Git Integration

VS Code’s built-in Git integration is a feature-rich powerhouse, but with huge repositories, it’s known to cause lag — sometimes even freezing the editor. Reddit developers working on enterprise-level mono repositories shared one key fix:


"git.enabled": false

Alternatively, you can use command-line Git or another Git GUI like Fork, GitKraken, or GitHub Desktop for staging and committing. This offloads the Git processing that VS Code would otherwise attempt in the background.

6. Use the Insiders Build

If standard VS Code isn’t cutting it, Redditors recommend exploring VS Code Insiders, which sometimes includes performance improvements not yet available in the stable version. Developers claim Insiders builds often load large projects faster due to more aggressive optimization and memory management updates.

WARNING: As it’s a nightly build, it may be less stable, but for many users suffering severe lag, the tradeoff is worth it.

7. Profile Memory Usage

VS Code has a handy command called “Developer: Show Running Extensions,” which details each extension’s memory and CPU usage. You’d be surprised how often one rogue theme or linter extension is causing a memory leak.

Reddit solution: Use this command to identify culprits, then either uninstall or disable them per workspace.

[ai-img]developer tools, vs code, high memory, extension lag[/ai-img]

8. Split Your Workspace

If you’re working in a mega-codebase that spans multiple apps or modules, consider splitting the workspace into smaller, more manageable folders. Reddit contributors managing monorepos shared major performance wins by dividing work into separate VS Code projects using multi-root workspaces.

This helps keep memory and indexing under control while still giving access to shared tooling like linters and formatters.

Set it up like so:

  1. Use File > Add Folder to Workspace to add targeted folders only.
  2. Save the workspace as a .code-workspace file.
  3. Customize settings per folder as needed.

9. Run VS Code With Custom Memory Limits

Believe it or not, you can influence how much memory VS Code is allowed to use. For power users on systems with abundant RAM, launching VS Code with custom memory settings can prevent slowdowns and crashes.

On macOS and Linux, use:


code --max-old-space-size=4096

This allocates up to 4GB of memory to the Node.js processes behind many of VS Code’s features, including the language server protocol.

Note: Too low a value can cause crashes. Too high can strain your system. Tweak depending on your hardware capabilities.

10. Final Touches: Hardware and OS Tips

Sometimes, the solution lies outside of VS Code entirely. Reddit posts often mention that slow hard drives, limited RAM (under 8GB), and background programs can make a bad situation worse.

  • Upgrade to SSD: VS Code depends heavily on disk I/O for indexing files.
  • Close Chrome tabs: Browsers can hog memory and compete with VS Code.
  • Use lightweight distros: On Linux, switching from Ubuntu to something like Arch + XFCE can cut background CPU usage dramatically.

Conclusion

While VS Code is packed with features, it’s not always immediately optimized for large-scale projects out of the box. Fortunately, seasoned developers on Reddit have offered a treasure trove of effective and practical fixes. Whether you’re dealing with a sluggish interface, long search times, or memory crashes, the key is to be strategic: disable, exclude, and customize.

Adopting these changes can turn VS Code from a bloated editor into a highly responsive and powerful development tool — even in the most demanding environments. Happy coding!