Hey everyone!
I've landed a proof of concept (POC) at work focused on integrating AI into our DevOps processes, specifically within our Continuous Integration/Continuous Deployment (CI/CD) pipelines. My background in AI is quite limited, so I'd really appreciate hearing about any experiences you have with similar projects. How did you approach it?
My task is pretty flexible, and I'm eager to highlight the benefits of using AI in CI/CD.
Just to give you more context, we primarily work with build and release pipelines, alongside some infrastructure setups, and our code base is mainly in C#.
Additionally, I'm wondering if we could use AI to automate tasks, like linking a check-in to known bug occurrences or generating commit descriptions and release notes based on changes. Any insights would be awesome!
Thanks!
1 Answer
You could start with simple AI models like a Naive Bayes classifier to flag pull requests that might have issues. It could act as a kind of 'is it bad?' filter for your code.
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