Using Z Vm For Test And Development Environments A Roundup

This IBM Redbooks publication shows the strengths of z/VM and how you can use these strengths to create a highly flexible test and production environment. Some of the strengths of z/VM that are shown in this book are that you can run Linux on z/VM, you can run a sysplex under z/VM, and you can develop code under z/VM for z/TPF. You can also provision Linux guests under z/VM. A vswitch allows you to connect all of your guests (all operating systems that run under z/VM) easily to the network. You can simulate your production environment on a sysplex. The intention of this book is to show the strengths of z/VM and how you can use these strengths to simulate your production environment and expand your application development and testing environments.

This textbook provides students with the background knowledge and skills necessary to begin using the basic functions and features of z/VM Version 5, Release 3. It is part of a series of textbooks designed to introduce students to mainframe concepts and help prepare them for a career in large systems computing. For optimal learning, students are assumed to be literate in personal computing and have some computer science or information systems background. Others who will benefit from this textbook include z/OS professionals who would like to expand their knowledge of other aspects of the mainframe computing environment. This course can be used as a prerequisite to understanding Linux on System z. After reading this textbook and working through the exercises, the student will have received a basic understanding of the following topics: The Series z Hardware concept and the history of the mainframe Virtualization technology in general and how it is exploited by z/VM Operating systems that can run as guest systems under z/VM z/VM components The z/VM control program and commands The interactive environment under z/VM, CMS and its commands z/VM planning and administration Implementing the networking capabilities of z/VM Tools to monitor the performance of z/VM systems and guest operating systems The REXX programming language and CMS pipelines Security issues when running z/VM

This IBM® Redbooks® publication is volume one of five in a series of books entitled The Virtualization Cookbook for IBM Z. The series includes the following volumes: The Virtualization Cookbook for IBM z Systems® Volume 1: IBM z/VM® 7.2, SG24-8147 The Virtualization Cookbook for IBM Z Volume 2: Red Hat Enterprise Linux 8.2 Servers, SG24-8303 The Virtualization Cookbook for IBM z Systems Volume 3: SUSE Linux Enterprise Server 12, SG24-8890 The Virtualization Cookbook for IBM z Systems Volume 4: Ubuntu Server 16.04, SG24-8354 Virtualization Cookbook for IBM Z Volume 5: KVM, SG24-8463 It is recommended that you start with Volume 1 of this series because the IBM z/VM hypervisor is the foundation (or base "layer") for installing Linux on IBM Z®. This book series assumes that you are generally familiar with IBM Z technology and terminology. It does not assume an in-depth understanding of z/VM or Linux. It is written for individuals who want to start quickly with z/VM and Linux, and get virtual servers up and running in a short time (days, not weeks or months). Volume 1 starts with a solution orientation, discusses planning and security, and then, describes z/VM installation methods, configuration, hardening, automation, servicing, networking, optional features, and more. It adopts a "cookbook-style" format that provides a concise, repeatable set of procedures for installing, configuring, administering, and maintaining z/VM. This volume also includes a chapter on monitoring z/VM and the Linux virtual servers that are hosted. Volumes 2, 3, and 4 assume that you completed all of the steps that are described in Volume 1. From that common foundation, these volumes describe how to create your own Linux virtual servers on IBM Z hardware under IBM z/VM. The cookbook format continues with installing and customizing Linux. Volume 5 provides an explanation of the kernel-based virtual machine (KVM) on IBM Z and how it can use the z/Architecture®. It focuses on the planning of the environment and provides installation and configuration definitions that are necessary to build, manage, and monitor a KVM on Z environment. This publication applies to the supported Linux on Z distributions (Red Hat, SUSE, and Ubuntu).

This IBM® Redbooks® publication is Volume 4 of a series of books entitled The Virtualization Cookbook for IBM z Systems. The other volumes in the series are: The Virtualization Cookbook for IBM z Systems Volume 1: IBM z/VM 6.3, SG24-8147 The Virtualization Cookbook for IBM z Systems Volume 2: Red Hat Enterprise Linux 7.1 Servers, SG24-8303 The Virtualization Cookbook for IBM z Systems Volume 3: SUSE Linux Enterprise Server 12, SG24-8890 It is advised that you start with Volume 1 of this series, because the IBM z/VM® Hypervisor is the foundation for installing Linux on IBM zTM Systems.

This IBM® Redbooks® publication shows the power of IBM System z® virtualization and flexibility in sharing resources in a flexible production environment. In this book, we outline the planning and setup of Linux on System z to move from a development or test environment into production. As an example, we use one logical partition (LPAR) with shared CPUs with memory for a production environment and another LPAR that shares some CPUs, but also has a dedicated one for production. Running in IBM z/VM® mode allows for virtualization of servers and based on z/VM shares, can prioritize and control their resources. The size of the LPAR or z/VM resources depends on the workload and the applications that run that workload. We examine a typical web server environment, Java applications, and describe it by using a database management system, such as IBM DB2®. Network decisions are examined with regards to VSWITCH, shared Open Systems Adapter (OSA), IBM HiperSocketsTM and the HiperPAV, or FCP/SCSI attachment used with a storage area network (SAN) Volume Controller along with performance and throughput expectations. The intended audience for this IBM Redbooks publication is IT architects who are responsible for planning production environments and IT specialists who are responsible for implementation of production environments.

Big data is currently one of the most critical emerging technologies. Organizations around the world are looking to exploit the explosive growth of data to unlock previously hidden insights in the hope of creating new revenue streams, gaining operational efficiencies, and obtaining greater understanding of customer needs. It is important to think of big data and analytics together. Big data is the term used to describe the recent explosion of different types of data from disparate sources. Analytics is about examining data to derive interesting and relevant trends and patterns, which can be used to inform decisions, optimize processes, and even drive new business models. With today's deluge of data comes the problems of processing that data, obtaining the correct skills to manage and analyze that data, and establishing rules to govern the data's use and distribution. The big data technology stack is ever growing and sometimes confusing, even more so when we add the complexities of setting up big data environments with large up-front investments. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its own challenge of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big data systems (such as Hadoop) are built on the shared nothing principle, where each node is independent and self-sufficient. A solution architecture that can allow these mutually exclusive principles to coexist is required to truly exploit the elasticity and ease-of-use of cloud computing for big data environments. This IBM® RedpaperTM publication is aimed at chief architects, line-of-business executives, and CIOs to provide an understanding of the cloud-related challenges they face and give prescriptive guidance for how to realize the benefits of big data solutions quickly and cost-effectively.