Summary
In this chapter, we covered Kubernetes, a robust container management platform that forms the infrastructure foundation for constructing open-source ML platforms. Throughout this chapter, you gained an understanding of containers and insights into the functioning of Kubernetes. Moreover, you acquired hands-on experience in establishing a Kubernetes cluster on AWS by leveraging AWS EKS. Additionally, we explored the process of deploying a containerized Jupyter Notebook application onto the cluster, thereby creating a fundamental data science environment. In the next chapter, we will shift our focus toward exploring a selection of open-source ML platforms that seamlessly integrate with the Kubernetes infrastructure.
Join our community on Discord
Join our community’s Discord space for discussions with the author and other readers:
