Book Image

Securing Hadoop

By : Sudheesh Narayan
Book Image

Securing Hadoop

By: Sudheesh Narayan

Overview of this book

Security of Big Data is one of the biggest concerns for enterprises today. How do we protect the sensitive information in a Hadoop ecosystem? How can we integrate Hadoop security with existing enterprise security systems? What are the challenges in securing Hadoop and its ecosystem? These are the questions which need to be answered in order to ensure effective management of Big Data. Hadoop, along with Kerberos, provides security features which enable Big Data management and which keep data secure. This book is a practitioner's guide for securing a Hadoop-based Big Data platform. This book provides you with a step-by-step approach to implementing end-to-end security along with a solid foundation of knowledge of the Hadoop and Kerberos security models. This practical, hands-on guide looks at the security challenges involved in securing sensitive data in a Hadoop-based Big Data platform and also covers the Security Reference Architecture for securing Big Data. It will take you through the internals of the Hadoop and Kerberos security models and will provide detailed implementation steps for securing Hadoop. You will also learn how the internals of the Hadoop security model are implemented, how to integrate Enterprise Security Systems with Hadoop security, and how you can manage and control user access to a Hadoop ecosystem seamlessly. You will also get acquainted with implementing audit logging and security incident monitoring within a Big Data platform.
Table of Contents (15 chapters)
Securing Hadoop
About the Author
About the Reviewers

Automation of a secured Hadoop deployment

In a production environment, there are hundreds (sometimes even thousands) of nodes in a Hadoop cluster. Managing and configuring such a large cluster is not done manually as it is laborious and error prone. Traditionally, enterprises used Chef/Puppet or a similar solution for cluster configuration management and deployment, In this approach, organizations had to continuously update their chef recipes based on the changes in Apache Hadoop releases. Instead, organizations typically deploy Hadoop cluster deployment automation based on the Hadoop distribution they work with. For example, in a Cloudera-based Hadoop distribution, organizations leverages Cloudera Manager to provide cluster deployment. automation, and management capability. For Hortonworks-based distributions, organizations prefer Ambari. Similarly, Intel distribution has Intel Manager for Apache Hadoop. Each of these deployment managers support secured Hadoop deployment. The approach...