CI/CD for AI model deployments

CI/CD for AI models is an industry standard that involves creating a pipeline with multiple steps: a safe environment to deploy model updates without affecting production, testing newly deployed models before promoting to production, seamlessly transitioning traffic from an old production deployment to a new one, and reverting to a previous production deployment if there are any issues. An automated pipeline can validate the model's speed and correctness using endpoints such as the development deployment inference endpoint and monitor the deployment status for the production deployment. The pipeline can also promote a new deployment to production and fall back to a previous production deployment in case of errors, minimizing interruption to the production service. To build an effective CI/CD pipeline for AI models, it's essential to separate model evaluation from model deployment and gain confidence in output quality through manual testing and comprehensive benchmarks before initiating a production deployment process.

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