- OpenStack Sahara Essentials
- Omar Khedher
- 321字
- 2021-07-16 11:22:51
Preface
OpenStack, the ultimate cloud computing operating system, keeps growing and gaining more popularity around the globe. One of the main reasons of OpenStack's success is the collaboration of several big enterprises and companies worldwide. Within every new release, the OpenStack community brings a new incubated project to the cloud computing open source world. Lately, big data has also taken a very important role in the OpenStack journey. Within its broad definition of the complexity of data management and its value extraction, the big-data business faces several challenges that need to be tackled. With the growth of the concept of cloud paradigm in the last decade, the big-data world can also be offered as a service. Specifically, the OpenStack community has taken on such a challenge to turn it into a very unique opportunity: Big Data as a Service. The Sahara project makes provisioning a complete elastic Hadoop cluster a very seamless operation with no need for touching the underlying infrastructure. Running on OpenStack, Sahara becomes a very mature project that supports Hadoop and Spark, the open source in-memory computing framework. That becomes a very good deal to find a parallel world about Big Data and Data Processing in Sahara named Elastic Data Processing. Sahara, formerly known as Savanna, has become a very attractive project, mature and supporting several big data providers.
In this book, we will explore the main motivation of using Sahara and how it interacts with other services of OpenStack. The main motivation of using Sahara is the facilities exposed from a central dashboard to manage big-data infrastructure and simplify data-processing tasks. We will walk through the installation and integration of Sahara OpenStack, launch clusters, execute sample jobs, explore more functions, and troubleshoot some common errors. By the end of this book, you should not only understand how Sahara operates and functions within the OpenStack ecosystem but also realize its major use cases of cluster and workload management.
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