Answering what-if deployment and configuration questions with wise

  • Authors:
  • Mukarram Tariq;Amgad Zeitoun;Vytautas Valancius;Nick Feamster;Mostafa Ammar

  • Affiliations:
  • Georgia Tech., Atlanta, GA, USA;Google Inc., Mountain View, CA, CA, USA;Georgia Tech., Atlanta, GA, USA;Georgia Tech., Atlanta, GA, USA;Georgia Tech., School of Computer Science, GA, USA

  • Venue:
  • Proceedings of the ACM SIGCOMM 2008 conference on Data communication
  • Year:
  • 2008

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Abstract

Designers of content distribution networks often need to determine how changes to infrastructure deployment and configuration affect service response times when they deploy a new data center, change ISP peering, or change the mapping of clients to servers. Today, the designers use coarse, back-of-the-envelope calculations, or costly field deployments; they need better ways to evaluate the effects of such hypothetical "what-if" questions before the actual deployments. This paper presents What-If Scenario Evaluator (WISE), a tool that predicts the effects of possible configuration and deployment changes in content distribution networks. WISE makes three contributions: (1) an algorithm that uses traces from existing deployments to learn causality among factors that affect service response-time distributions; (2) an algorithm that uses the learned causal structure to estimate a dataset that is representative of the hypothetical scenario that a designer may wish to evaluate, and uses these datasets to predict future response-time distributions; (3) a scenario specification language that allows a network designer to easily express hypothetical deployment scenarios without being cognizant of the dependencies between variables that affect service response times. Our evaluation, both in a controlled setting and in a real-world field deployment at a large, global CDN, shows that WISE can quickly and accurately predict service response-time distributions for many practical What-If scenarios.