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

Operational considerations

In the previous sections, we discussed what it means to provide or consume storage either in-cluster or off-cluster for the containerized services in Cloud Pak for Data. However, it is also critical to make sure that the storage infrastructure itself is resilient and that operational practices exist to ensure that there is no data loss. Storage failover must also be taken into account from a disaster recovery (DR) standpoint.

In this section, we will take a quick look at some typical practices and tools we can use to ensure that the Cloud Pak for Data services operate with resilience, and that data protection is assured.

Continuous availability with in-cluster storage

A core tenet in Kubernetes is to ensure the continuous availability of applications. This includes load balancing and replicas for compute that can span multiple zones. Such zones could be failure (or availability) zones in public clouds or perhaps independently powered racks of hardware...