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)
Section 1: The Basics
Section 2: Product Capabilities
Section 3: Technical Details

Tenancy considerations

We will start by looking closely at what multi-tenancy implies, why tenancy is important, and, in general, what architectural choices, trade-offs, and compromises regarding expenses need to be made when planning for such shared deployments.

Designating tenants

Each enterprise usually has a very different interpretation when it comes to identifying their tenants, but by and large, a tenant is defined as a select group of users granted specific privileges to access a shared software installation. When tenants represent different companies altogether, users belonging to one tenant are generally unaware of the existence of other tenant users. However, even such isolation can be relaxed when it comes to users within the same enterprise, and employees in the same company may be members of multiple tenant "accounts."

Here are some example situations where a Cluster Operations team may want to designate "tenants" that share the same OpenShift...