Derivation of Response Time Service Level Objectives for Business Services

Design of Service Level Agreements (SLAs) emerges as an increasingly important discipline in business-oriented IT management. In this work, we study utility maximization of contractual obligations of a business service provider for a typical SLA. We demonstrate that using service usage and performance data as well as IT performance data, routinely collected by enterprises, efficient automated derivation of optimal response time Service Level Objectives (SLOs) of an SLA is possible. This paper addresses a specific facet of the SLA design problem not sufficiently addressed in previous studies. One common approach is to calculate SLOs attainable for the given IT infrastructure by means of simple percentile analysis. However, this methodology is business agnostic and may result in sub-optimal SLOs. Another widespread approach addresses IT infrastructure (re)design, where the goal is to enable the IT to meet specified target SLOs. In contrast to these approaches, our work proposes finding optimal response lime SLOs attainable for the given IT infrastructure in a business aware manner. We define the response time SLO optimization problem, propose an algorithm that efficiently solves it using linear optimization and percentile analysis, and evaluate our solution both analytically and experimentally.

[1]  A. N. PETTrrr A Non-parametric Approach to the Change-point Problem , 1979 .

[2]  A. Pettitt A Non‐Parametric Approach to the Change‐Point Problem , 1979 .

[3]  P. Bickel,et al.  Confidence Bands for a Distribution Function Using the Bootstrap , 1989 .

[4]  Pradeep Ray,et al.  Service level management definition, architecture, and research challenges , 1999, Seamless Interconnection for Universal Services. Global Telecommunications Conference. GLOBECOM'99. (Cat. No.99CH37042).

[5]  D. Verma,et al.  Supporting Service Level Agreements on IP Networks , 1999 .

[6]  Jong-Wook Baek,et al.  Management of service level agreements for multimedia Internet service using a utility model , 2001, IEEE Commun. Mag..

[7]  Fan Zhang,et al.  A statistical approach to predictive detection , 2001, Comput. Networks.

[8]  Eric Bouillet,et al.  The structure and management of service level agreements in networks , 2002, IEEE J. Sel. Areas Commun..

[9]  Claudio Bartolini,et al.  Management by contract , 2004, 2004 IEEE/IFIP Network Operations and Management Symposium (IEEE Cat. No.04CH37507).

[10]  Ted Ralphs,et al.  COmputational INfrastructure for Operations Research (COIN-OR) , 2004 .

[11]  Philip S. Yu,et al.  Utility computing SLA management based upon business objectives , 2004, IBM Syst. J..

[12]  Onn Shehory,et al.  Automated and Adaptive Threshold Setting: Enabling Technology for Autonomy and Self-Management , 2005 .

[13]  Filipe Marques,et al.  SLA Design from a Business Perspective , 2005, DSOM.

[14]  Filipe Marques,et al.  Optimal Design of E-Commerce Site Infrastructure from a Business Perspective , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[15]  D. Trastour,et al.  IT service management driven by business objectives An application to incident management , 2006, 2006 IEEE/IFIP Network Operations and Management Symposium NOMS 2006.