Spark JobServer: from Spark Standalone to Mesos, Marathon and Docker

After several years of running Spark JobServer workloads, the need for better availability and multi-tenancy emerged across several projects author was involved in. This blog post covers design decisions made to provide higher availability and fault tolerance of JobServer installations, multi-tenancy for Spark workloads, scalability and failure recovery automation, and software choices made in order to reach these goals. Spark JobServer Spark JobServer is widely used across a variety of reporting and aggregating systems.