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

Infrastructure requirements, storage, and networking

The IaaS layer could be on-premises or on the public cloud hyper-scalers. Compute could be virtualized, such as with VMware/vSphere or via Amazon AWS EC2 machines, Azure VMs, and so on, or physical bare-metal machines. These hosts form the Kubernetes master and worker nodes. Storage solutions could be native to the cloud (such as AWS EBS or IBM File Gold) or, in the case of on-premises deployments, leverage existing investments in storage solutions (such as IBM Spectrum Scale or Dell/EMC Isilon).

With OpenShift Container Platform v4, these hosts typically run Red Hat Enterprise Linux CoreOS (RHCOS), a secure, operating system purpose-built for containerized workloads. It leverages the same Linux kernel, the same packages as the traditional RHEL installation, besides being designed for remote management. In addition, for improved security, it enables SELINUX out of the box and is deployed as an immutable operating system (except...