CI/CD for ML

In traditional software, CI/CD is straightforward: test the code, build an artifact, deploy it. ML systems break this model because code is only one of three things that can change.

A data shift, a retrained model, or a feature pipeline update can each break production, and none of them show up in a code diff. CI/CD for ML extends the traditional pipeline to test and deploy data and models alongside code.