Why data scientists shouldn’t need to know Kubernetes
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Re: Why data scientists shouldn’t need to know Kubernetes
#2This article has enough interesting past the headline that it is worth a scan.
Table of Contents …. The full-stack expectations …. Separation of development and production environments …. Bridging the gap Part I: containerization …. Bridging the gap Part II: infrastructure abstraction …. Workflow orchestration vs. infrastructure abstraction …. Workflow orchestration: Airflow vs. Prefect vs. Argo …. Infrastructure abstraction: Kubeflow vs. Metaflow