Preface

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In 1999, Dr Willy Chiu, noticing the emergence of many large and complex customer Web sites, and observing how they often failed to deliver the expected robustness and customer satisfaction, set up a new team within IBM called the High-Volume Web Sites (HVWS) team. This team was chartered to work with customers and IBM internal teams involved in the creation and deployment of really large Web sites, and in particular those supporting e-business applications used by customers over the Internet -- typical business to customer (B2C) applications but large and complex ones. The team would learn from this experience and document proven best practices so that customers could learn how to make high-volume Web sites that worked well, and so that IBM developers could improve their products to better support high-volume sites.

On December 9, 2003 IBM announced that it has chosen Silicon Valley as the location for its first "e-business on demand Center of Competency" -- which will amass heavy technology resources and expertise to help companies advance their Internet initiatives. The Center of Competency in IBM's Silicon Valley Lab will be the first of several to open in the next year as part of IBM Chairman and Chief Executive Officer Samuel J. Palmisano's $10 billion commitment for research, acquisitions, marketing and training centers devoted to e-business on demand. This is IBM's one-year-old initiative to help companies improve efficiency, productivity, and their ability to respond to changing conditions such as peaks in customer demand.

IBM is beefing up capabilities in the Silicon Valley lab to help companies that operate some of the world's busiest Web sites and must reliably handle huge, often unpredictable amounts of traffic (with page views that can soar into the hundreds of millions each day).

The center will house experts from IBM Software, IBM Research, and other parts of the company who are some of the world's top experts in high-performance Internet computing, as well as hundreds of server computers and other equipment that will allow companies to design and test new technologies for on-demand computing.

The center is an extension of IBM's existing High-Volume Web Site Lab in the Silicon Valley Lab, which has worked with eBay, Charles Schwab, CIGNA, Federated Department Stores, VISA and many others to stretch the boundaries of business computing on the Internet.

For more than four years, IBM's High-Volume Web Sites (HVWS) team has been working with many of the world's largest Web sites. The team has accumulated a significant amount of knowledge and defined best practices for designing and deploying high-volume sites, earning a reputation as one of the world's leading centers of expertise on scalable e-business infrastructures. The team has locations in California, New York, Japan, Korea, China, Taiwan, and the United Kingdom.

The IT infrastructures that comprise most high-volume sites present unique challenges in design, implementation, and management. While actual implementations vary, Figure 0-1 shows a typical e-business infrastructure comprised of several tiers. Each tier handles a particular set of functions, such as serving content (Web servers, such as the IBM HTTP Server), providing integration business logic (Web application servers, such as the WebSphere Application Server), or processing database transactions (transaction and database servers). Site workloads are assumed to be high volume, serving dynamic, volatile data.

Figure 0-1: Multi-tier infrastructure for e-business

The HVWS team analyzes site traffic patterns to improve performance and availability. Figure 0-2 shows how IBM's HVWS team defines the life cycle of a Web site; it shows also the categories of best practices recommended for one or more phases of the cycle.

Figure 0-2: Life cycle of a Web site

As it accumulates experience and knowledge, the HVWS team publishes papers aimed at helping CIOs and others like you understand and meet the new challenges presented during one or more of the phases. This IBM Redbook is a compilation of the HVWS papers, which are available individually at the HVWS Web page.

In January 2004, IBM renamed the HVWS team to reflect its success and expanding mission. The new name is High Performance On Demand Solutions (HiPODS) in recognition of the evolution of its work with some of IBM's largest customers, including eBay and Charles Schwab, whose projects are evolving from high volume Web architectures toward high performance on demand operating environments, including all the software brands.

About this redbook

This redbook is a compilation of the HVWS white papers published in 2003:

Chapter 1, Prepare your WebSphere Web site for e-business on demand, introduces how some of IBM's largest customers are starting their transition to on demand computing. It also introduces a limited IBM offering, IBM Server Allocation for WebSphere Application Server, developed by the HVWS group. Finally, the chapter identifies what you can do now to improve resource use and ready your e-business to benefit from on demand computing.

Chapter 2, Architecture for virtualization with WebSphere Application Server, Version 5, explains how enterprises can use the new and enhanced features of WebSphere Application Server, Version 5 as the first steps in building and realizing the value of resource virtualization today. Enterprises who virtualize will be ready to implement emerging on-demand offerings such as IBM Server Allocation for WebSphere Application Server.

Chapter 3, Advanced clustering techniques for maximizing Web site availability with WebSphere Application Server, Version 5, discusses advanced techniques for Web and application server clustering using IBM WebSphere Application Server, Version 5. Server clustering is critical to the on-demand operating environment and, in particular, to the Web infrastructure. Server clustering can be used to help achieve continuous availability of Web sites in the always-on global marketplace.

Chapter 4, Resilience of Websphere Portal clusters under load, describes a HVWS project to test and validate the resilience of WebSphere Portal clusters under realistic load conditions against a variety of failure scenarios. It includes a description of the behavior of the clusters during recovery of application server clones and nodes, verifying the successful redistribution of workload to the recovered clones and/or nodes. This chapter includes lessons learned and a number of best practices settings and guidelines.

Chapter 5, How WebSphere caches dynamic content for high-volume Web sites, introduces a feature of WebSphere Application Server Version 5 that can improve Web Site performance. Optimizing for scalability and personalization remains a significant challenge for e-businesses as they balance the demands for instantaneous changes, high performance, availability, reliability, and security. Vendors are responding with infrastructure options and supporting hardware and software platforms that address these requirements.

Chapter 6, Impact of object serialization and local enterprise JavaBeans on application server performance, explains the Java serialization process, related research, and the cost of serialization and deserialization of Java objects within WebSphere Application Server, Version 5.0 environments. The objective of this chapter is to help software architects and designers make informed choices when implementing remote objects.

Chapter 7, Using IBM's Content Manager to manage Web content, describes a joint project between IBM and a customer to use IBM Content Manager to develop in a short time a customized application to manage Web content. Leveraging the capabilities of IBM Content Manager avoids issues common to the development of applications that manage Web content.

Chapter 8, Building a custom Web content management solution with IBM Content Manager for Multiplatforms, Version 8, describes a joint project between IBM and a customer to use IBM Content Manager to develop in a short time a customized application to manage Web content. Leveraging the capabilities of IBM Content Manager avoids issues common to the development of applications that manage Web content.

Chapter 9, High-volume Web site Performance Simulator for WebSphere, introduces the High-Volume Web Site Performance Simulator for WebSphere, an analytic queuing model that estimates the performance of a Web server based on workload patterns, performance objectives, and specified hardware and software. The results can be used as guidelines for configuration sizing.

Chapter 10, Sametime Links scalability report, reviews the results of a test of the scalability of Sametime Links. The objective of the test was to understand how Sametime Links could be scaled to support a very large number of users. Overall, the tests showed that Sametime could support 300,000 concurrent Sametime Links clients in the test environment.

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