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

Architecting for multi-tenancy

In this section, we will explore what it means to implement multi-tenancy with Cloud Pak for Data, starting with how to plan out the topology on an OpenShift cluster and how to separate the tenants within the same cluster.

Achieving tenancy with namespace scoping

As we established earlier, assigning a unique OpenShift project (a Kubernetes namespace) to each unique tenant is the recommended approach for Cloud Pak for Data multi-tenant deployments.

The following diagram shows how multiple tenants can be sandboxed into individual OpenShift projects and the logical separation between the Operations zone (which would be managed by the cluster administrators) and the Tenants zone (somewhere the tenant users are potentially given access to):

Figure 12.1 – Individual tenant namespaces in a shared Kubernetes cluster

The Cluster Operations zone includes all the management functions provided by OpenShift and Kubernetes...