Product Description Learn everything you need to know to reliably automate, deploy, and maintain Apache Spark on AWS, Google Cloud, On-Premises, and Openstack. Unlike other books that focus on the internals of how Apache Spark works, and which mostly interest data-scientists, this book covers the operational aspects of Apache Spark. This book will benefit anyone in a DevOps role, and help you understand how Spark was designed to handle scale and failures, and the operational considerations and tools useful in operating Apache Spark. About the Author Timothy Chen is a Distributed Systems Engineer at Mesosphere, where he helps customers build up their Mesos infrastructures. He has extensive experience with Spark, Mesos, Kafka, and many other Big Data Solutions. He is a committer and PMC for Apache Drill and Apache Mesos projects and regularly contributes code to Apache Spark.Parviz Deyhim is an Architect at Databricks, working with customers and the community on leading-edge Spark deployments. He has been involved in the Spark community since early 2012 and the early days of Apache Spark. In addition, he spent three years working at Amazon Web Services. During his time at AWS he championed adopting Spark on AWS and was responsible for Spark as an offering on AWS EMR.Denny Lee is a Senior Director of Data Sciences Engineering at Concur. He regularly (co)presents various Spark and Big Data sessions and webinars -- most recently at Tableau Data14 and Cloudera Apache Spark webinar. He writes regular blog posts on Spark and big data topics on his blog (dennyglee.com) and Concur's blog (concur.com/blog). He is the lead organizer of the Seattle Spark Meetup group and Seattle Mesos User Group, and had been involved with Spark since 2012. In his previous work at Microsoft, he helped build Project Isotope (Hadoop on Windows and Azure), co-authored various Wrox books on Analysis Services and PowerPivot, and wrote extensive blog posts on sqlcat.com.Benjamin Stickel