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  • Book Overview & Buying IBM Cloud Pak for Data
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IBM Cloud Pak for Data

IBM Cloud Pak for Data

By : Manda, Srinivasan, Rangarao
5 (7)
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IBM Cloud Pak for Data

IBM Cloud Pak for Data

5 (7)
By: Manda, Srinivasan, 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)
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1
Section 1: The Basics
4
Section 2: Product Capabilities
11
Section 3: Technical Details

Understanding the concept of persistent volumes

We will start by providing a quick introduction to the foundational storage concepts in Kubernetes and how Cloud Pak for Data leverages storage. Typical containers are stateless, which means that any files they create or any changes they make will be ephemeral; upon restarting the container, these changes would not be restored. Also, in-container files would be created in a temporary location on the host, which can cause contention with other, similar consumers of that location. In Kubernetes, the concept of volumes [1] enables the persistence of directory files that are needed for stateful containers. Such volumes are mounted in a Kubernetes Pod and, depending on the access mode associated with that volume, the same directory contents can be shared with other Pods running concurrently within that Kubernetes namespace.

In this section, you will learn what it means to provision entities known as persistent volumes, which provide storage...

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IBM Cloud Pak for Data
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