Summary
AI platforms for deploying ML models to production at scale use a fully automated continuous delivery process built on streaming microservice architectures with Docker containers and Kubernetes. Data scientists push model code that is built, tested, deployed and activated automatically, with monitoring, model health indicators and retraining to reduce total cost of ownership.
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