Architecting Modern Data Platforms: A Guide to Enterprise Hadoop at Scale

Book Description There’s a lot of information about big data technologies, but splicing these technologies into an end-to-end enterprise data platform is a daunting task not widely covered. With this practical book, you’ll learn how to build big data infrastructure both on-premises and in the cloud and successfully architect a modern data platform.
Ideal for enterprise architects, IT managers, application architects, and data engineers, this book shows you how to overcome the many challenges that emerge during Hadoop projects. You’ll explore the vast landscape of tools available in the Hadoop and big data realm in a thorough technical primer before diving into:

• Infrastructure: Look at all component layers in a modern data platform, from the server to the data center, to establish a solid foundation for data in your enterprise
• Platform: Understand aspects of deployment, operation, security, high availability, and disaster recovery, along with everything you need to know to integrate your platform with the rest of your enterprise IT
• Taking Hadoop to the cloud: Learn the important architectural aspects of running a big data platform in the cloud while maintaining enterprise security and high availability

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Content

Chapter 1. Big Data Technology Primer

Part I. Infrastructure
Chapter 2. Clusters
Chapter 3. Compute and Storage
Chapter 4. Networking
Chapter 5. Organizational Challenges
Chapter 6. Datacenter Considerations

Part II. Platform
Chapter 7. Provisioning Clusters
Chapter 8. Platform Validation
Chapter 9. Security
Chapter 10. Integration with Identity Management Providers
Chapter 11. Accessing and Interacting with Clusters
Chapter 12. High Availability
Chapter 13. Backup and Disaster Recovery

Part III. Taking Hadoop to the Cloud
Chapter 14. Basics of Virtualization for Hadoop
Chapter 15. Solutions for Private Clouds
Chapter 16. Solutions in the Public Cloud
Chapter 17. Automated Provisioning
Chapter 18. Security in the Cloud