Retrofitting Autonomic Capabilities onto Legacy Systems

  • Authors:
  • Janak Parekh;Gail Kaiser;Philip Gross;Giuseppe Valetto

  • Affiliations:
  • Department of Computer Science, Columbia University, z New York, United States 10027;Department of Computer Science, Columbia University, z New York, United States 10027;Department of Computer Science, Columbia University, z New York, United States 10027;Aff1 Aff2

  • Venue:
  • Cluster Computing
  • Year:
  • 2006

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Abstract

sec:abstractnak Autonomic computing--self-configuring, self-healing, self-managing applications, systems and networks--is a promising solution to ever-increasing system complexity and the spiraling costs of human management as systems scale to global proportions. Most results to date, however, suggest ways to architect new software designed from the ground up as autonomic systems, whereas in the real world organizations continue to use stovepipe legacy systems and/or build "systems of systems" that draw from a gamut of disparate technologies from numerous vendors. Our goal is to retrofit autonomic computing onto such systems, externally, without any need to understand, modify or even recompile the target system's code. We present an autonomic infrastructure that operates similarly to active middleware, to explicitly add autonomic services to pre-existing systems via continual monitoring and a feedback loop that performs reconfiguration and/or repair as needed. Our lightweight design and separation of concerns enables easy adoption of individual components for use with a variety of target systems, independent of the rest of the full infrastructure. This work has been validated by several case studies spanning multiple real-world application domains.