What to Discover Before Migrating to the Cloud

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IFIP/IEEE Integrated Network Management Symposium (IM)
Ghent, Belgium,
Abstract. The adoption of the cloud computing model continues to be dominated by startups seeking to build new applications that can take advantage of the cloud’s pay-as-you-go pricing and resource elasticity. In contrast, large enterprises have been slow to adopt the cloud model, partly because migrating legacy applications to the cloud is technically non-trivial and economically prohibitive. Both challenges arise, in part, from the difficulty in discovering the complex dependencies that these legacy applications have on the underlying IT environment. In this paper, we introduce a novel Kullback-Leibler (KL) divergence based method that can systematically discover the complex server-toserver and application-to-server relationships. We evaluate our method using five real datasets from large enterprise migration efforts. Our results demonstrate that our new method is capable of finding critical application correlations; it performs better than traditional approaches, such as Bayesian or mutual information models. Additionally, by cleverly subdividing the sample space, we are able to uncover intriguing phenomena in different subspaces. These analyses aid migration engineers in a variety of tasks ranging from migration planning to failure mitigation, and can potentially lead to significant cost reduction in migration to cloud.
author = {Kun and Bai and Niyu and Ge and Hani and Jamjoom and Xiaolan and Zhang and Ee Ee and Jan and Lakshminarayanan and Renganarayana},
title = {{What to Discover Before Migrating to the Cloud}},
booktitle = {IFIP/IEEE Integrated Network Management Symposium (IM)},
address = {Ghent, Belgium},
month = {May},
year = {2013}