Why Data Scientists Love Kubernetes


Let’s start with an uncontroversial point: Software developers and system operators love Kubernetes as a way to deploy and manage applications in Linux containers. Linux containers provide the foundation for reproducible builds and deployments, but Kubernetes and its ecosystem provide essential features that make containers great for running real applications, like:

  • Continuous integration and deployment, so you can go from a Git commit to a passing test suite to new code running in production

  • Ubiquitous monitoring, which makes it easy to track the performance and other metrics about any component of a system and visualize them in meaningful ways

  • Declarative deployments, which allow you to rely on Kubernetes to recreate your production environment in a staging environment

  • Flexible service routing, which means you can scale services out or gradually roll updates out to production (and roll them back if necessary)

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