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Mastering Mesos

You're reading from   Mastering Mesos The ultimate guide to managing, building, and deploying large-scale clusters with Apache Mesos

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Product type Paperback
Published in May 2016
Publisher Packt
ISBN-13 9781785886249
Length 352 pages
Edition 1st Edition
Tools
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Authors (2):
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Akhil Das Akhil Das
Author Profile Icon Akhil Das
Akhil Das
Dipa Dubhashi Dipa Dubhashi
Author Profile Icon Dipa Dubhashi
Dipa Dubhashi
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introducing Mesos FREE CHAPTER 2. Mesos Internals 3. Getting Started with Mesos 4. Service Scheduling and Management Frameworks 5. Mesos Cluster Deployment 6. Mesos Frameworks 7. Mesos Containerizers 8. Mesos Big Data Frameworks 9. Mesos Big Data Frameworks 2 Index

What this book covers

Chapter 1, Introducing Mesos, introduces Mesos, dives deep into its architecture, and introduces some important topics, such as frameworks, resource allocation, and resource isolation. It also discusses the two-level scheduling approach that Mesos employs, provides a detailed overview of its API, and provides a few examples of how Mesos is used in production.

Chapter 2, Mesos Internals, provides a comprehensive overview of Mesos' features and walks the reader through several important topics regarding high availability, fault tolerance, scaling, and efficiency, such as resource allocation, resource reservation, and recovery, among others.

Chapter 3, Getting Started with Mesos, covers how to manually set up and run a Mesos cluster on the public cloud (AWS, GCE, and Azure) as well as on a private datacentre (on premise). It also discuss the various debugging methods and explores how to troubleshoot the Mesos setup in detail.

Chapter 4, Service Scheduling and Management Frameworks, introduces several Mesos-based scheduling and management frameworks or applications that are required for the easy deployment, discovery, load balancing, and failure handling of long-running services.

Chapter 5, Mesos Cluster Deployment, explains how a Mesos cluster can be easily set up and monitored using the standard deployment and configuration management tools used by system administrators and DevOps engineers. It also discusses some of the common problems faced while deploying a Mesos cluster along with their corresponding resolutions.

Chapter 6, Mesos Frameworks, walks the reader through the concept and features of Mesos frameworks in detail. It also provides a detailed overview of the Mesos API, including the new HTTP Scheduler API, and provides a recipe to build custom frameworks on Mesos.

Chapter 7, Mesos Containerizers, introduces the concepts of containers and talks a bit about Docker, probably the most popular container technology available today. It also provides a detailed overview of the different "containerizer" options in Mesos, besides introducing some other topics such as networking for Mesos-managed containers and the fetcher cache. Finally, an example of deploying containerized apps in Mesos is provided for better understanding.

Chapter 8, Mesos Big Data Frameworks, acts as a guide to deploying important big data processing frameworks such as Hadoop, Spark, Storm, and Samza on top of Mesos.

Chapter 9, Mesos Big Data Frameworks 2, guides the reader through deploying important big data storage frameworks such as Cassandra, the Elasticsearch-Logstash-Kibana (ELK) stack, and Kafka on top of Mesos.

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