Over 50 recipes on the core features of Apache Mesos and running big data frameworks in Mesos
About This Book- Learn to install and configure Mesos to suit the needs of your organization
- Follow step-by-step instructions to deploy application frameworks on top of Mesos, saving you many hours of research and trial and error
- Use this practical guide packed with powerful recipes to implement Mesos and easily integrate it with other application frameworks
This book is for system administrators, engineers, and big data programmers. Basic experience with big data technologies such as Hadoop or Spark would be useful but is not essential. A working knowledge of Apache Mesos is expected.
What You Will Learn- Set up Mesos on different operating systems
- Use the Marathon and Chronos frameworks to manage multiple applications
- Work with Mesos and Docker
- Integrate Mesos with Spark and other big data frameworks
- Use networking features in Mesos for effective communication between containers
- Configure Mesos for high availability using Zookeeper
- Secure your Mesos clusters with SASL and Authorization ACLs
- Solve everyday problems and discover the best practices
Apache Mesos is open source cluster sharing and management software. Deploying and managing scalable applications in large-scale clustered environments can be difficult, but Apache Mesos makes it easier with efficient resource isolation and sharing across application frameworks.
The goal of this book is to guide you through the practical implementation of the Mesos core along with a number of Mesos supported frameworks. You will begin by installing Mesos and then learn how to configure clusters and maintain them. You will also see how to deploy a cluster in a production environment with high availability using Zookeeper.
Next, you will get to grips with using Mesos, Marathon, and Docker to build and deploy a PaaS. You will see how to schedule jobs with Chronos. We'll demonstrate how to integrate Mesos with big data frameworks such as Spark, Hadoop, and Storm. Practical solutions backed with clear examples will also show you how to deploy elastic big data jobs.
You will find out how to deploy a scalable continuous integration and delivery system on Mesos with Jenkins. Finally, you will configure and deploy a highly scalable distributed search engine with ElasticSearch.
Throughout the course of this book, you will get to know tips and tricks along with best practices to follow when working with Mesos.
Style and approachThis step-by-step guide is packed with powerful recipes on using Apache Mesos and shows its integration with containers and big data frameworks.
Over 50 recipes on the core features of Apache Mesos and running big data frameworks in Mesos
About This Book- Learn to install and configure Mesos to suit the needs of your organization
- Follow step-by-step instructions to deploy application frameworks on top of Mesos, saving you many hours of research and trial and error
- Use this practical guide packed with powerful recipes to implement Mesos and easily integrate it with other application frameworks
This book is for system administrators, engineers, and big data programmers. Basic experience with big data technologies such as Hadoop or Spark would be useful but is not essential. A working knowledge of Apache Mesos is expected.
What You Will Learn- Set up Mesos on different operating systems
- Use the Marathon and Chronos frameworks to manage multiple applications
- Work with Mesos and Docker
- Integrate Mesos with Spark and other big data frameworks
- Use networking features in Mesos for effective communication between containers
- Configure Mesos for high availability using Zookeeper
- Secure your Mesos clusters with SASL and Authorization ACLs
- Solve everyday problems and discover the best practices
Apache Mesos is open source cluster sharing and management software. Deploying and managing scalable applications in large-scale clustered environments can be difficult, but Apache Mesos makes it easier with efficient resource isolation and sharing across application frameworks.
The goal of this book is to guide you through the practical implementation of the Mesos core along with a number of Mesos supported frameworks. You will begin by installing Mesos and then learn how to configure clusters and maintain them. You will also see how to deploy a cluster in a production environment with high availability using Zookeeper.
Next, you will get to grips with using Mesos, Marathon, and Docker to build and deploy a PaaS. You will see how to schedule jobs with Chronos. We'll demonstrate how to integrate Mesos with big data frameworks such as Spark, Hadoop, and Storm. Practical solutions backed with clear examples will also show you how to deploy elastic big data jobs.
You will find out how to deploy a scalable continuous integration and delivery system on Mesos with Jenkins. Finally, you will configure and deploy a highly scalable distributed search engine with ElasticSearch.
Throughout the course of this book, you will get to know tips and tricks along with best practices to follow when working with Mesos.
Style and approachThis step-by-step guide is packed with powerful recipes on using Apache Mesos and shows its integration with containers and big data frameworks.
![Apache Mesos Cookbook: Over 50 recipes on the core features of Apache Mesos and running big data frameworks in Mesos](http://img.images-bn.com/static/redesign/srcs/images/grey-box.png?v11.12.6)
Apache Mesos Cookbook: Over 50 recipes on the core features of Apache Mesos and running big data frameworks in Mesos
146![Apache Mesos Cookbook: Over 50 recipes on the core features of Apache Mesos and running big data frameworks in Mesos](http://img.images-bn.com/static/redesign/srcs/images/grey-box.png?v11.12.6)
Apache Mesos Cookbook: Over 50 recipes on the core features of Apache Mesos and running big data frameworks in Mesos
146Product Details
ISBN-13: | 9781785880933 |
---|---|
Publisher: | Packt Publishing |
Publication date: | 08/02/2017 |
Sold by: | Barnes & Noble |
Format: | eBook |
Pages: | 146 |
File size: | 2 MB |