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IBM Redbooks: Top 5 Publications you Should Read

Joseph Gulla reviews a list of five “rock star” Redbooks publications, which he got from Chris Rayns, manager for technical content services for IBM Redbooks.

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In this post, I am finishing up this series on IBM Redbooks, which contain content developed and published by the IBM Systems Worldwide Client Experience Center. I began this series a month ago and I’m a bit sad to finish it because I have learned so much. Many years ago, when I was a system programmer, I used the Redbooks publications to get things done. This is pretty much what everyone did—we took those books, studied them and implemented the solution that they explained in their straightforward manner.
 
I have been away from technical projects, so rediscovering IBM Redbooks has really been rewarding and I can now see how they can help me fill gaps that I have in my current knowledge. This probably applies to you, too. This week, I’ll focus on the idea of reviewing five “rock star” Redbooks publications. I got the list from a friend, Chris Rayns, who is a manager for technical content services for IBM Redbooks. I am betting that he has an informed opinion.

The Best of the Best

Chris wrote to me that it’s “so difficult to choose ‘rock stars’ “ for so many for different reasons. Customers just love the Redbooks. Here is the list he sent and what I found:
 
1. “Getting Started with z/OS Data Set Encryption”

Summary: A 200-page publication written by a worldwide team of 10 practitioners with diverse experience and skills that provides a broad explanation of data protection through encryption and explains how the various hardware and software components interact in a z/OS data set encryption environment. It’s organized to help understand security challenges and then to plan, prepare, deploy, audit and maintain encryption and the supporting environment.
 
Best Quote: “At the core of every enterprise is data, which if lost or exposed might cause irreparable damage to the business or organization. In many instances, regulatory requirements are designed to safeguard data with high penalties if the requirements are not met or if sensitive data is exposed.”
 
Most Useful Chapter: Chapter 3: “Planning for z/OS Data Set Encryption”
This chapter covers planning considerations for implementing z/OS data set encryption from several perspectives, and includes the following topics:
3.1 Creating an implementation plan  
3.2 Data set administration considerations  
3.3 Resource authorization considerations  
3.4 ICSF administration considerations 
3.5 Key management considerations    
3.6 General considerations  
 
I also found the troubleshooting appendix very useful. “This appendix describes some of the common error situations you might encounter when working with data set encryption. Errors and their symptoms (error messages, unexpected result or behavior) also are described, including how to remedy or bypass the problem.” The appendix includes the problem description and remedy, including JCL and commands to fix the problem.
 
Note: I read the ePub version of this book (and all the others) using Apple iBooks. It’s easy to handle the book in this format—to browse and read and jump around—and the figures are very clearly rendered. The ePub version of the book is 475 pages long versus 200 as a PDF.
 
2. “AI and Big Data on IBM Power Systems Servers”
 
Summary: This publication was written by a team of seven people from around the world working at the IBM Redbooks Austin center. In this IBM Redbooks publication, which is 162 pages, the team covers the best practices for deploying and integrating some of the best artificial intelligence (AI) solutions on the market, including IBM Watson Machine Learning Accelerator, IBM Watson Studio Local, IBM Power Systems, IBM Spectrum Scale, IBM Data Science Experience, IBM Elastic Storage Server, Hortonworks Data Platform, Hortonworks DataFlow and H2O Driverless AI.
 
Best Quote: “As big data becomes more ubiquitous, businesses are wondering how they can best leverage it to gain insight into their most important business questions. Using machine learning and deep learning in big data environments can identify historical patterns and build AI models that can help businesses to improve customer experience, add services and offerings, identify new revenue streams or lines of business, and optimize business or manufacturing operations. The power of AI for predictive analytics is being harnessed across all industries, so it is important that businesses familiarize themselves with all of the tools and techniques that are available for integration with their data lake environments.”
 
Most Useful Chapter: I found the overview chapter most useful as I have a weak foundation in AI and big data. The solution overview chapter provides an introduction to the technologies that play a key part in the integration of big data and AI. The following topics are covered in this chapter:
• Introduction
• AI solutions
• Data platforms
• When to use a GPU
• Hortonworks Data Platform GPU support
• Linux on Power
• Client use cases
 
Note: Additionally, the overview chapter surveys all of the AI solutions in the market and includes five separate use cases. This is a great overview chapter that could be read stand-alone.
 
3. “Scale up for Linux on LinuxONE” 
 
Summary: This publication provides the reader with the information needed in making a decision on scaling architecture when implementing Linux on LinuxONE. This book has several goals, including to inform the reader about x86 sprawl problems, including how x86 vertical scale-out architectures are problematic going forward and to provide solutions to x86 server sprawl problems. It also seeks to inform the reader about the LinuxONE solution for each x86 server sprawl problem and to provide virtualization and security options for LinuxONE. This 68-page Redpaper publication was written by three specialists in the center in Poughkeepsie, New York.
 
Best Quote:  “In the digital era, businesses are demanding optimization of IT resources, focusing on workloads. It is a challenge to scale the environment when the workload increases. Server sprawl is a growing concern in data centers today.”
 
Most Useful Chapter: “Introducing the LinuxONE platform” is a compelling, stand-alone chapter that discusses scale-up and scale-out definitions, LinuxONE versus distributed x86 (workload utilization, x86 sprawl problems, reducing costs, total cost of ownership, data center floor space, etc.) and LinuxONE platform considerations.
 
Note:  I have explored consolidation as a topic for some time now. In “The Changing Face of IT Consolidation,” I explored the world of server consolidation and more.
 
4. “IBM FlashSystem 9100 Architecture, Performance, and Implementation” 
 
Summary: In this IBM Redbooks publication, the authors discuss the product’s features and clearly explain the planning steps, architecture, installation and configuration. They also include many hints and tips. IBM FlashSystem 9100 combines the performance of flash and Non-Volatile Memory Express with the reliability and innovation of IBM FlashCore technology and the rich features of IBM Spectrum Virtualize. This is a 368-page publication written by a team of 10 practitioners.
 
Best Quote: “The success or failure of businesses often depends on how well organizations use their data assets for competitive advantage. Deeper insights from data require better information technology. As organizations modernize their IT infrastructure to boost innovation, they need a data storage system that can keep pace with highly virtualized environments, cloud computing, mobile and social systems of engagement, and in-depth, real-time analytics.”
 
Most Useful Chapter:  After reading Chapters 1 and 2, I found the data reduction and tools chapter (Chapter 3) most compelling as it goes over the random access compression engine, location-based compression and the predecide mechanism among other key topics. This chapter covers the following main ideas:
• Compression and deduplication techniques
• Data Reduction Pools inside the FS9100
• RACE compared to Data Reduction Pools
• Data Reduction Pools and Unmap
• Data Reduction Pools with Easy Tier
• Garbage collection
• Data Reduction Pools with deduplication
• Estimating data reduction using various tools
• When to use Flash Core Modules or Data Reduction Pools
 
Note: I also found Chapter 4, “Planning,” very useful as well. My general interest in project planning and management is reflected in my choice of “favorite” topics.
 
5. “IBM Cloud Object Storage Concepts and Architecture: System Edition”
 
Summary: This IBM Redpaper publication is focused on object storage, which is the primary storage solution that’s used in the cloud and on-premises solutions as a central storage platform for unstructured data. At 30 page, it was written by a team of specialists from around the world working at the IBM Cloud Object Storage Office in Chicago.
 
Best Quote: “Object Storage is the primary storage solution that is used in the cloud and on-premises solutions as a central storage platform for unstructured data. Object storage is growing more popular for the following reasons:
•It’s designed for exabyte scale
•It’s easy to manage and yet meets the growing demands of enterprises for a broad set of applications and workloads
•It allows users to balance storage cost, location and compliance control requirements across data sets and essential applications.”
 
Most Useful Chapter: The publication is brief, so the organization is by topics, not chapters. I found the security topic most compelling. IBM Cloud Object Storage security provides the following key characteristics:
• All crucial configuration information is digitally signed to avoid being compromised
• Certificate-based authentication of every node (manager, accesser node, and slicestor node) is provided
• Transmission and storage of data is inherently private and secure
• No single disk or slicestor node contains a full object
• Transport Layer Security is supported for data-in-motion protection
• All data is encrypted at rest by default
• Supports retention enabled vaults
 
IBM Cloud Object Storage security is separated into appliance, user authentication, network, data, retention enabled vaults, client and object security. The sections that follow this general security discussion focus on appliance, user authentication, etc.
 
Note: This is a brief and effective introduction to IBM Cloud Object Storage, a system that provides industry-leading flexibility that enables using organizations the tools to handle unpredictable but always changing needs of business and evolving workloads.
 
Thanks to Chris Rayns for sending me his “rock star” Redbooks list. He was right about the publications. 

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