Performance engineering for EA systems in next generation data centresPerformance engineering for EA systems in next generation data centres

  • Authors:
  • Jerome Rolia;Ludmila Cherkasova;Richard Friedrich

  • Affiliations:
  • Hewlett-Packard Labs, Palo Alto, CA;Hewlett-Packard Labs, Palo Alto, CA;Hewlett-Packard Labs, Palo Alto, CA

  • Venue:
  • WOSP '07 Proceedings of the 6th international workshop on Software and performance
  • Year:
  • 2007

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Abstract

Software Performance Engineering (SPE) methods have been in use for over two decades as an approach to manage the risks of developing systems that fail to satisfy their performance requirements. In general, SPE advocates the use of performance oriented design principles to guide design decisions and predictive performance models to assess the performance impact of design alternatives. SPE methods have been used successfully to identify and overcome system design blunders early in the Information Technology (IT) project lifecycle before the blunders are built into a system and become expensive and time consuming to correct. While the methods have been used successfully in some IT project domains, they are not widely applied in the important domain of Enterprise Application (EA) systems. This experience paper considers the reasons for this and explores the role of SPE as new EA platform and data centre technologies become available.We find that many risks traditionally addressed by SPE have been mitigated by the nature of existing EA platforms, the nature of today's IT projects for EA, and an attention to business process modeling. Furthermore, the design and implementation of future EA systems will see some performance risks reduced even further by new EA and IT system management platforms for Next Generation Data Centres. However, we expect that the nature of EA systems to be built is becoming more complex. As a result some familiar performance risks will re-emerge along with new runtime risks. We believe that SPE methods can help to mitigate such risks and describe research challenges that must be addressed to make this a reality.