This is an article from DZone’s 2022 Kubernetes in the Enterprise Trend Report.
Kubernetes and machine learning (ML) are a perfect match. As the leading container orchestrator, Kubernetes’ scalability and flexibility make it the perfect platform for managing extract-transform-load (ETL) pipelines and training ML models. That’s why there’s a thriving ecosystem for running ML tasks on Kubernetes. Let’s look at how Kubernetes is uniquely suited for supporting machine learning, how you can use it to make your ML pipelines run faster and better, and some of the most popular Kubernetes tools for ETL and ML.