This IBM® RedbooksTM publication applies to Version 6 Release 1 of AIX® on POWER® systems. This book is provided as an additional resource as you investigate or consider implementing and deploying a cloud in a POWER® environment in the context of infrastructure as a service. is provided as an additional resource as you investigate or consider implementing and deploying a cloud in a POWER environment in the context of infrastructure as a service.
This book is intended for anyone who wants to learn more about Cloud Computing on Power systems.
The IBM® PureFlex® System combines no-compromise system designs along with built-in expertise and integrates them into complete, optimized solutions. At the heart of PureFlex System is the IBM Flex System® Enterprise Chassis. This fully integrated infrastructure platform supports a mix of compute, storage, and networking resources to meet the demands of your applications.
The solution is easily scalable with the addition of another chassis with the required nodes. With the IBM Flex System Manager®, multiple chassis can be monitored from a single panel. The 14 node, 10U chassis delivers high-speed performance complete with integrated servers, storage, and networking. This flexible chassis is simple to deploy now, and to scale to meet your needs in the future.
This IBM Redbooks® publication describes IBM PureFlex System and IBM Flex System available from IBM. It highlights the technology and features of the chassis, compute nodes, management features, and connectivity options. Guidance is provided about every major component, and about networking and storage connectivity.
This book is intended for customers, IBM Business Partners, and IBM employees who want to know the details about the new family of products. It assumes that you have a basic understanding of blade server concepts and general IT knowledge.
The book then looks more closely at the underlying technology and hones in on the security aspects for the following subsystems:
You’ll learn how to use Amazon Web Services (AWS) to build a private Windows domain, complete with Active Directory, enterprise email, instant messaging, IP telephony, automated management, and other services. By the end of the book, you’ll have a fully functioning IT infrastructure you can operate for less than $300 per month.Learn about Virtual Private Cloud (VPC) and other AWS tools you’ll useCreate a Windows domain and set up a DNS management systemInstall Active Directory and a Windows Primary Domain ControllerUse Microsoft Exchange to set up an enterprise email serviceImport existing Windows Server-based virtual machines into your VPCSet up an enterprise-class chat/IM service, using the XMPP protocolInstall and configure a VoIP PBX telephony system with Asterisk and FreePBXKeep your network running smoothly with automated backup and restore, intrusion detection, and fault alerting
Authors Kelsey Hightower, Brendan Burns, and Joe Beda—who’ve worked on Kubernetes at Google and other organizatons—explain how this system fits into the lifecycle of a distributed application. You will learn how to use tools and APIs to automate scalable distributed systems, whether it is for online services, machine-learning applications, or a cluster of Raspberry Pi computers.Explore the distributed system challenges that Kubernetes addressesDive into containerized application development, using containers such as DockerCreate and run containers on Kubernetes, using the docker image format and container runtimeExplore specialized objects essential for running applications in productionReliably roll out new software versions without downtime or errorsGet examples of how to develop and deploy real-world applications in Kubernetes
Microsoft Excel is a powerful tool that can transform the way you use data. This book explains in comprehensive and user-friendly detail how to manage, make sense of, explore and share data, giving scientists at all levels the skills they need to maximize the usefulness of their data.
Readers will learn how to use Excel to:
* Build a dataset – how to handle variables and notes, rearrangements and edits to data.
* Check datasets – dealing with typographic errors, data validation and numerical errors.
* Make sense of data – including datasets for regression and correlation; summarizing data with averages and variability; and visualizing data with graphs, pivot charts and sparklines.
* Explore regression data – finding, highlighting and visualizing correlations.
* Explore time-related data – using pivot tables, sparklines and line plots.
* Explore association data – creating and visualizing contingency tables.
* Explore differences – pivot tables and data visualizations including box-whisker plots.
* Share data – methods for exporting and sharing your datasets, summaries and graphs.
Alongside the text, Have a Go exercises, Tips and Notes give readers practical
experience and highlight important points, and helpful self-assessment exercises and summary tables can be found at the end of each chapter. Supplementary material can also be downloaded on the companion website.
Managing Data Using Excel is an essential book for all scientists and students who use data and are seeking to manage data more effectively. It is aimed at scientists at all levels but it is especially useful for university-level research, from undergraduates to postdoctoral researchers.
Gruntwork co-founder Yevgeniy (Jim) Brikman walks you through dozens of code examples that demonstrate how to use Terraform’s simple, declarative programming language to deploy and manage infrastructure with just a few commands. Whether you’re a novice developer, aspiring DevOps engineer, or veteran sysadmin, this book will take you from Terraform basics to running a full tech stack capable of supporting a massive amount of traffic and a large team of developers.Compare Terraform to other IAC tools, such as Chef, Puppet, Ansible, and Salt StackUse Terraform to deploy server clusters, load balancers, and databasesLearn how Terraform manages the state of your infrastructure and how it impacts file layout, isolation, and lockingCreate reusable infrastructure with Terraform modulesTry out advanced Terraform syntax to implement loops, if-statements, and zero-downtime deploymentUse Terraform as a team, including best practices for writing, testing, and versioning Terraform code
In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient—lessons directly applicable to your organization.
This book is divided into four sections:Introduction—Learn what site reliability engineering is and why it differs from conventional IT industry practicesPrinciples—Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE)Practices—Understand the theory and practice of an SRE’s day-to-day work: building and operating large distributed computing systemsManagement—Explore Google's best practices for training, communication, and meetings that your organization can use
Microservice technologies are moving quickly. Author Sam Newman provides you with a firm grounding in the concepts while diving into current solutions for modeling, integrating, testing, deploying, and monitoring your own autonomous services. You’ll follow a fictional company throughout the book to learn how building a microservice architecture affects a single domain.Discover how microservices allow you to align your system design with your organization’s goalsLearn options for integrating a service with the rest of your systemTake an incremental approach when splitting monolithic codebasesDeploy individual microservices through continuous integrationExamine the complexities of testing and monitoring distributed servicesManage security with user-to-service and service-to-service modelsUnderstand the challenges of scaling microservice architectures