IBM E server pSeries Sizing and Capacity Planning A Practical Guide

Short Description
This IBM® Redbook offers a comprehensive guide to the concepts, concerns, and approaches to properly size and plan the capacity of IBM Eserver pSeries® systems. It discusses the major hardware, software, benchmarks, and various tools used in the sizing and capacity planning process. This redbook is suitable for professionals who want to acquire a better understanding of sizing pSeries products. It targets clients, sales and marketing professionals, technical support professionals, and IBM Business Partners. The introduction of this redbook provides an excellent look into how sizing and capacity planning are accomplished for pSeries servers. Client dialogs are used throughout this book for illustration purposes.

Website: www.redbooks.ibm.com | Filesize: 6489kb
No of Page(s): 570

Content
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Introduction to sizing and capacity planning
This part introduces and describes the concepts, concerns, general guidelines, and approaches to the sizing and capacity planning of pSeries servers.
Overview, concepts, and approach
This chapter provides the basics behind practical sizing and capacity planning. It also examines the underlying concepts and approach.
Properly sizing pSeries servers can be difficult since every client environment is unique. Usually there is not enough information to make the best decision. Therefore, you must take a realistic approach. And if you make proper assumptions, you can reach an adequate solution.
Capacity planning is a predictive process to determine future computing hardware resources required to support estimated changes in workload. The increased workload on computing resources can be a result of growth in business volumes or the introduction of new applications and functions to enhance the current suite of applications.
The objective of the capacity planning process is to develop an estimate of the system resource required to deliver performance objectives that meet a forecast level of business activity at some specified date in the future. As a result of its predictive nature, capacity planning can only be an approximation at best.
The implementation of the same application in different environments can result in significantly different system requirements. There are many factors that can influence the degree of success in achieving the predicted results. These include changes in application design, the way users interact with the application, and the number of users who may use the applications. The key to successful capacity planning is a thorough understanding of the application implementation and use of performance data collected.
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