GitHub Integration Now In GA - Build Images from GitHub Repos Even Faster

RunPod is pleased to announce that our GitHub integration is officially out of beta and ready for production use! This feature enables you to iterate your work more quickly by building packages to deploy on RunPod serverless directly from a GitHub repo, removing all of the friction involved in creating and updating Docker images locally.

Enabling the Integration

You can enable the integration by attempting to deploy a repo under GitHub Repo. where it will ask you to sign in to your GitHub account if you have not already connected it. This connection can be broken under your Settings page if you need to do so later.

Using the Integration

You can then select a repo from your GitHub account. For this example, I’ll select a repo in my account where I’ve created a basic serverless function that returns a Hello World.

Select your branch, and enter the path for your Dockerfile. Note that it’s generally recommended to have your requirements.txt, Dockerfile, and hander.py in the root if at all possible.

Configure your endpoint as usual, and then click Create Endpoint. You will see it build the image on its own and deploy it to the endpoint. Note that whenever any commits are made to the branch, it will automatically build and push a corresponding image down to the endpoint, saving you the hassle of having to do all of the builds on your own.

Improved Speed

We’ve made some heavy duty optimizations while in the beta phase over the past few weeks so if you’ve used it before, you may want to revisit it again to take a look at the improved speeds. Check out how our benchmarks have since we’ve made our improvements now that we are in GA:

Practical applications

Machine Learning Model Updates 

When fine-tuning or updating your AI models, you can commit the new model weights or architecture changes to your repo, and the endpoint will automatically rebuild with the latest version. This is perfect for teams running continuous model improvement cycles.

API Evolution 

As your AI service grows, you might need to add new endpoints, modify response formats, or optimize performance. With GitHub integration, these changes can be tested in a development branch and seamlessly promoted to production once approved.

Version Control and Rollbacks 

If an update causes issues, you can quickly roll back to a previous version by reverting to an earlier commit. This provides a safety net for your production AI services and makes it easy to maintain multiple versions of your endpoint.

Conclusion

The GitHub integration is just the beginning of our efforts to streamline the AI deployment workflow. We're excited to see how our users leverage this feature to build and scale their AI applications more efficiently.

Have you integrated your GitHub repositories with RunPod? We'd love to hear about your experience and use cases in the comments below!