Preface
The term and technology of autonomic computing is unfamiliar to most IT people. However, it will become familiar and understood after reading this book. Today, IT organizations are faced with the growing challenge of supporting the needs of the corporate enterprise with a reduced budgets and persistent or growing computing demands. For many enterprises, the challenge is compounded by complex architectures and distributed computing infrastructures that were developed over the last 20 years. This situation has caused system management costs to escalate while budgets and corporate spending are shrinking.
CIOs and CTOs everywhere are now tasked with reducing the costs of the IT organization while continuing to support the ongoing and growing computing needs of the enterprise. To succeed, the CIO must find new ways to operate the computing infrastructure of the company more efficiently. Solving this problem requires a new computing model—one that allows for efficiencies in IT infrastructure and resources. Indeed one such model is now emerging. IBM calls it autonomic computing. This is a new methodology for managing enterprise computing environments. Autonomic computing is a new approach that enables software to operate intelligently and dynamically, basing decisions on IT policies and service requirements. Top hardware vendors, such as IBM, Microsoft, Hewlett Packard and others are looking at how to develop servers, operating systems and system management tools and services that encompass the fundamental requirements of autonomic computing.
What Is Autonomic Computing?
The word “autonomic” means acting or occurring involuntarily. Autonomics is used to describe an action or response that occurs without conscious control. In physiology, it relates to the activities controlled by the autonomic nervous system (ANS).
Autonomic computing is the ability to manage your computing enterprise through hardware and software that automatically and dynamically responds to the requirements of your business. This means self-healing, self-configuring, self-optimizing, and self-protecting hardware and software that behaves in accordance to defined service levels and policies. Just like the autonomic nervous system responds to the needs of the body, the autonomic computing system responds to the needs of the business.
Goals of Autonomic Computing
Autonomic computing is a new approach to computer and systems management. The purpose is to reduce the cost of managing the IT infrastructure, and at the same time, increase service.
The goals autonomic computing is to reduce the cost of service through far more automated and efficient use of available resources and capacity. This includes dynamic resource allocation, self-healing hardware and software, and setting service-level agreements according to business needs. Autonomic computing have four basic value propositions that can be stated as business goals:
Reduced costs— achieved by better and more efficient resource usage, and by reduced system-management (labor) costs.
Improved service levels— achieved by dynamic adjustments or tuning of IT services.
Increased agility—achieved by rapid provisioning of new services or resources and scaling of established services.
Less complexity— by self-managing and intelligent decision making in IT operations much of the complexity is managed without human intervention.
There are eight key elements of an autonomic-computing system:
Knowledge of itself, in terms of resources and capabilities
An autonomic system has knowledge of its components, status, capacity and connections with other systems to govern itself.
The ability to configure and reconfigure itself
The autonomic system is capable of configuring itself and making dynamic adjustments to that configuration as its environment changes.
The ability to continuously self-optimize itself
The autonomic system monitors its constituent parts and fine-tunes workflow to achieve established system goals.
Self-healing capabilities
The autonomic system must be able to discover problems or potential problems and find alternate ways of using resources or reconfigure the system to keep functioning smoothly.
Self-protection capabilities
The autonomic system must be able to protect itself from various types of internal/external attacks and failures to maintain overall system security and integrity.
The ability to discover knowledge of its environment and context—and to adapt accordingly
The autonomic system must be able to understand how to best interact with neighboring systems, using available resources and adapting to its environment.
The ability to function in a heterogeneous computing environment
The autonomic system must be able to function in a heterogeneous world—in other words, it cannot be a proprietary solution.
The ability to anticipate and adapt to user needs
The autonomic system must be able to meet the goals of the business without involving the user for data collection, analysis, and decision-making.
The fundamental process is to have autonomic systems that can enforce your computing policies and service-level agreements through the use of intelligent hardware and software. Maintenance and processing tasks are automated and computing resources are dynamically allocated for maximum efficiencies.
Summary
With the continuos and unrelenting demands for cost reduction and economies of scale that are placed on IT organizations today, new methods for managing the computing enterprise are essential. IT organizations must operate as efficient service centers or contend with the choice of being outsourced. Service centers must operate efficiently and keep costs low to sustain their business. This requires IT organizations to operate differently—using new methods. Automating work, using intelligent software, and managing the enterprise with a holistic view are essential today. Autonomic solutions are required for cost-efficient operations—and must be based on the policies and service-level agreements of the enterprise. The major hardware vendors have initiatives underway to deliver servers, operating systems, and utilities that are self-configuring, self-optimizing, and self-healing. The ISVs must deliver software that not only meets those requirements but add additional value. This leads the major hardware vendors to strive for automatically adjusting servers and dynamically managing workload. It also forces independent software vendors (ISVs) of enterprise management tools to develop autonomic solutions that not only meet the same requirements, but also take advantage of this important technology.
The intent of this book is to provide all readers with and understanding of the scope, issues, elements and examples of autonomic computing and prepare IT for the benefits that can be achieved.
—Richard Murch
Columbus, OH