Book Image

IBM Cloud Pak for Data

By : Hemanth Manda, Sriram Srinivasan, Deepak Rangarao
3 (1)
Book Image

IBM Cloud Pak for Data

3 (1)
By: Hemanth Manda, Sriram Srinivasan, Deepak Rangarao

Overview of this book

Cloud Pak for Data is IBM's modern data and AI platform that includes strategic offerings from its data and AI portfolio delivered in a cloud-native fashion with the flexibility of deployment on any cloud. The platform offers a unique approach to addressing modern challenges with an integrated mix of proprietary, open-source, and third-party services. You'll begin by getting to grips with key concepts in modern data management and artificial intelligence (AI), reviewing real-life use cases, and developing an appreciation of the AI Ladder principle. Once you've gotten to grips with the basics, you will explore how Cloud Pak for Data helps in the elegant implementation of the AI Ladder practice to collect, organize, analyze, and infuse data and trustworthy AI across your business. As you advance, you'll discover the capabilities of the platform and extension services, including how they are packaged and priced. With the help of examples present throughout the book, you will gain a deep understanding of the platform, from its rich capabilities and technical architecture to its ecosystem and key go-to-market aspects. By the end of this IBM book, you'll be able to apply IBM Cloud Pak for Data's prescriptive practices and leverage its capabilities to build a trusted data foundation and accelerate AI adoption in your enterprise.
Table of Contents (17 chapters)
1
Section 1: The Basics
4
Section 2: Product Capabilities
11
Section 3: Technical Details

Chapter 11: Storage

Cloud Pak for Data leverages the Kubernetes concept of persistent volumes, which is supported in OpenShift, to enable its various services so that it can store data and metadata. Cloud Pak for Data services can also connect to remote databases, lakes, and object stores, as well as remotely exported filesystems as sources of data. We will look at the concepts and technologies that power both in-cluster PVs and off-cluster external storage. By the end of this chapter, you will have learned about what options are available in various public and private cloud infrastructures, as well as how to best optimize data storage for your use cases. You will also learn how storage should be operationalized, especially to support the continuous availability of your entire solution.

In this chapter, we're going to cover the following main topics:

  • Persistent volumes
  • Connectivity to external volumes
  • Operational considerations