Kubernetes for Data Science and Machine Learning - Kublr

This article was originally published May 11, 2018 on JAXenter. At Kublr we've been talking with customers and the community about the workloads they plan to run using containers and Kubernetes. Frameworks from MapReduce to Hadoop to Spark have created parallel processing capabilities that leverage clusters to speed processing tasks. These clusters have been frequently managed with their own cluster management solution (eg. Recent developments in Kubernetes for data science and machine learning include the 2.3 release of Apache Spark with "native" Kubernetes support.