Kubernetes Container Orchestration Infrastructure Management

While establishing a local data science setup for individual use for simple ML tasks may seem straightforward, creating a robust and scalable data science environment for multiple users (catering to diverse ML tasks and effectively tracking ML experiments) poses significant challenges. To overcome the scalability and control challenges of having a large number of users, companies normally implement ML platforms. There are different approaches to building ML platforms including build-your-own using open-source technologies or fully managed cloud ML platforms.

In this chapter, we will explore the open-source option, and specifically, Kubernetes, an indispensable open-source container orchestration platform that serves as a critical foundation for constructing open-source ML platforms. Kubernetes offers a wealth of capabilities, enabling the seamless management and orchestration of containers at scale. By leveraging Kubernetes...