I’ll be speaking about Spark on Kubernetes at Spark Summit EU this week. The main thesis of my talk is that the old way of running Spark in a dedicated cluster that is shared between applications makes sense when analytics is a separate workload. However, analytics is no longer a separate workload — instead, analytics is now an essential part of long-running data-driven applications. This realization motivated my team to switch from a shared Spark cluster to multiple logical clusters that are co-scheduled with the applications that depend on them.

I’m glad for the opportunity to get together with the Spark community and present on some of the cool work my team has done lately. Here are some links you can visit to learn more about our work and other topics related to running Spark on Kubernetes and OpenShift:

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