The Availability Index in .NET

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The Availability Index
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Another way of making the point about balancing downtime with cost is to look at availability as a curve. The more you spend, the higher you move up the curve. Be sure to note, however, that the incremental costs to move from one level to the next increase as you move up the curve. As you go through the technology chapters, which make up the heart of the book, you ll find that each chapter begins with a picture of the Availability Index. A detailed explanation can be found in 3, The Value of Availability, but fundamentally, it shows the relationship between availability and cost. The line is curved because the relationship is not linear; the higher the level of availability you require, the more it costs to move to the next level. Costs accelerate as you move up the Index. Another way to look at it is that the curve reflects the law of diminishing returns. After you protect against the
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cheaper and easier-to-fix problems, the cost (and complexity) of the next level of protection increases, flattening out the curve. You may also notice that the curve never quite makes it to 100 percent; that s because we believe that 100 percent availability cannot be attained over the medium and long term. More on that later.
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Summary
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Computer systems are very complex. The solutions that make them work best are complex too. They require planning, work, testing, and a general ongoing effort by knowledgeable people at every level of implementation. Applications must be tolerant of failures and inappropriate inputs. Hardware must be able to automatically recover from failures. And since systems change, if you want this functionality to always be present, you must regularly test your recovery procedures. Do they still work Do they still work as quickly as they should If they do not work as expected, the time to find out is not when something has gone wrong and the pressure is on. Our goals are to help you design your systems for maximum availability and predictable downtime and recovery times. We will look at these systems from end to end, and from network, system, and application perspectives.
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Organization of the Book
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We take a very layered approach to systems, and that layered approach follows in the organization of this book. We look at each type of component separately, starting with disks and moving up through systems into software and finally disaster recovery. In many of the chapters, you will find sidebars that we call Tales from the Field. They are generally true-to-life experiences that we have lived through ourselves or have seen real users of computer systems go through. Some of them are funny; all of them help make a point clearer. We hope that you learn from the mistakes and examples that we have seen and sometimes suffered through. 2, What to Measure, takes a look at the numbers and statistics that go into measuring availability, as well as what can go wrong with the various components of your system. This chapter also looks at measurement trends, such as six sigma and nines, that are becoming more common metrics for system quality. 3 introduces the Availability Index in some detail and looks at the business case for availability. 4, The Politics of Availability, is a primer on how to introduce the concept of availability into your organization and how to deal with some of the politics and other potential organizational roadblocks.
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Introduction
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5, 20 Key High Availability Design Principles, is a cornerstone for the whole book and contains our 20 key design principles for attaining resilience and high availability. We refer back to these principles throughout the book. 6, Backups and Restores, focuses on the last line of defense between you and irrevocably lost data. How do you take backups, why do you take them, and how do you handle the tapes and the hardware 7, Highly Available Data Management, looks at data storage. We discuss disks and disk arrays, and the ways to logically arrange them to maximize your protection against hardware failures, including the use of RAID (redundant array of independent disks) hardware and software. 8, SANs, NAS, and Virtualization, introduces some newer technology: Storage Area Networks (SANs), Network-Attached Storage (NAS), and virtualization. 9, Networking, reviews networking concepts and discusses the various elements of making your networks survive failures at the physical or logical layers, including router redundancy and load balancing 10, Data Centers and the Local Environment, looks at the environment around your computers, including your data center, power issues, cabling, maintenance plans, cooling, system naming conventions, and physical space. 11, People and Processes, looks at some people and process issues related to system resiliency, such as system administrators, maintenance plans, patches, documentation, vendor management, and security. 12, Clients and Consumers, examines clients as consumers of high-availability services and as resources to be managed. 13, Application Design, focuses on application reliability. What are the issues involved in making your applications recover properly after a server has failed and recovered What should you do to make your applications more resilient to external system faults and internal (logical) problems 14, Data and Web Services, details high-availability models for web and network services such as web, application, and directory servers, along with some thoughts on making XML-based web services more reliable. 15, Local Clustering and Failover, introduces the concept of clustering, the technology that is often viewed as the core of high availability. In 16, Failover Management and Issues, we look at failovers and the software that manages them. We look at the implications of building your own failover software, and at some of the inherent complexities that accompany the use of this software. 17, Failover Configurations, examines the myriad of different failover configurations the good, the bad, and the ugly. 18, Data Replication, reviews techniques for replicating critical data to remote systems across a network.
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