Book Image

Mastering Mesos

By : Dipa Dubhashi, Akhil Das
Book Image

Mastering Mesos

By: Dipa Dubhashi, Akhil Das

Overview of this book

Apache Mesos is open source cluster management software that provides efficient resource isolations and resource sharing distributed applications or frameworks. This book will take you on a journey to enhance your knowledge from amateur to master level, showing you how to improve the efficiency, management, and development of Mesos clusters. The architecture is quite complex and this book will explore the difficulties and complexities of working with Mesos. We begin by introducing Mesos, explaining its architecture and functionality. Next, we provide a comprehensive overview of Mesos features and advanced topics such as high availability, fault tolerance, scaling, and efficiency. Furthermore, you will learn to set up multi-node Mesos clusters on private and public clouds. We will also introduce several Mesos-based scheduling and management frameworks or applications to enable the easy deployment, discovery, load balancing, and failure handling of long-running services. Next, you will find out how a Mesos cluster can be easily set up and monitored using the standard deployment and configuration management tools. This advanced guide will show you how to deploy important big data processing frameworks such as Hadoop, Spark, and Storm on Mesos and big data storage frameworks such as Cassandra, Elasticsearch, and Kafka.
Table of Contents (16 chapters)
Mastering Mesos
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Introduction to Apache Aurora


Apache Aurora is a powerful Mesos framework for long-running services, cron jobs, and ad hoc jobs. It was originally designed at Twitter and was later open sourced under the Apache license. You can turn your Mesos cluster to a private cloud using Aurora. Unlike Marathon, Aurora is responsible for keeping jobs running across a shared pool of resources over a long duration. If any of the machines in the pool fails, then Aurora can intelligently reschedule those jobs on other healthy machines in the pool.

Aurora is not useful if you try to build an application with specific requirements for scheduling or if the job itself is a scheduler.

Managing long-running applications is one of the key features of Aurora. Apart from this, Aurora can be used to provide coarse-grained (that is, fixed) resources for your job so that at any point of time, the job always has a specified amount of resources. It also supports multiple users, and the configuration is templated with DSL...