Book Image

Native Docker Clustering with Swarm

By : Fabrizio Soppelsa, Chanwit Kaewkasi
Book Image

Native Docker Clustering with Swarm

By: Fabrizio Soppelsa, Chanwit Kaewkasi

Overview of this book

Docker Swarm serves as one of the crucial components of the Docker ecosystem and offers a native solution for you to orchestrate containers. It’s turning out to be one of the preferred choices for Docker clustering thanks to its recent improvements. This book covers Swarm, Swarm Mode, and SwarmKit. It gives you a guided tour on how Swarm works and how to work with Swarm. It describes how to set up local test installations and then moves to huge distributed infrastructures. You will be shown how Swarm works internally, what’s new in Swarmkit, how to automate big Swarm deployments, and how to configure and operate a Swarm cluster on the public and private cloud. This book will teach you how to meet the challenge of deploying massive production-ready applications and a huge number of containers on Swarm. You'll also cover advanced topics that include volumes, scheduling, a Libnetwork deep dive, security, and platform scalability.
Table of Contents (18 chapters)
Native Docker Clustering with Swarm
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Dedication
Preface

Another app: Apache Spark


Now that we have acquired some practice using services, we step up to the next level. We'll deploy Apache Spark on Swarm. Spark is an open source cluster computing framework from the Apache foundation, which is mainly used for data processing.

Spark may be (but not limited to) used for things, such as:

  • Analysis of big data (Spark Core)

  • Fast and scalable data structured console (Spark SQL)

  • Streaming analytics (Spark Streaming)

  • Graph processing (Spark GraphX)

Here we will focus mainly on the infrastructural part of Swarm. If you want to learn how to program or use Spark in detail, read Packt's selection of books on Spark. We suggest starting with Fast Data Processing with Spark 2.0 - Third Edition.

Spark is a neat and clear alternative for Hadoop, it is a more agile and efficient substitute for the complexity and magnitude of Hadoop.

The theoretical topology of Spark is immediate and can reckon the Swarm mode on one or more managers leading the cluster operations and a certain...