Apache Mesos Essentials

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  • Get to grips with setting up a Mesos cluster in a data centre or in the Cloud
  • Perform data analysis on Mesos using frameworks such as Hadoop, Spark, and Storm
  • Familiarize yourself with managing services on Mesos using Marathon, Chronos, and Aurora
  • Gain insight into how to write a distributed application using the Mesos API
  • Discover how to automate and administer a Mesos Cluster and other operations such as logging and monitoring
  • Explore the fundamentals and internal working of Mesos

Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It allows developers to concurrently run the likes of Hadoop, Spark, Storm, and other applications on a dynamically shared pool of nodes. With Mesos, you have the power to manage a wide range of resources in a multi-tenant environment.

Starting with the basics, this book will give you an insight into all the features that Mesos has to offer. You will first learn how to set up Mesos in various environments from data centers to the cloud. You will then learn how to implement self-managed Platform as a Service environment with Mesos using various service schedulers, such as Chronos, Aurora, and Marathon. You will then delve into the depths of Mesos fundamentals and learn how to build distributed applications using Mesos primitives.

Finally, you will round things off by covering the operational aspects of Mesos including logging, monitoring, high availability, and recovery.

  • Deploy Apache Mesos to concurrently run cutting edge data processing frameworks like Spark, Hadoop and Storm in parallel
  • Share resources between various cluster computing applications and web applications
  • Detailed guidance on Mesos best practices in a stable production environment
Page Count 230
Course Length 6 hours 54 minutes
ISBN 9781783288762
Date Of Publication 28 Jun 2015


Dharmesh Kakadia

Dharmesh Kakadia is a research fellow at Microsoft Research, who develops the next-generation cluster management systems. Before coming to MSR, he completed his MS in research from the International Institute of Information Technology, Hyderabad, where he worked on improving scheduling in cloud and big data systems. He likes to work at the intersection of systems and data and has published research in resource management at various venues. He is passionate about open source technologies and plays an active role in various open source communities. You can learn more about him at @DharmeshKakadia on Twitter.