Recent advances in hardware development coupled
with the rapid adoption and broad applicability of cloud computing
have introduced widespread heterogeneity in data centers,
significantly complicating the management of cloud applications
and data center resources. This paper presents the CACTOS
approach to cloud infrastructure automation and optimization,
which addresses heterogeneity through a combination of in-depth
analysis of application behavior with insights from commercial
cloud providers. The aim of the approach is threefold: to model
applications and data center resources, to simulate applications
and resources for planning and operation, and to optimize application
deployment and resource use in an autonomic manner.
The approach is based on case studies from the areas of business
analytics, enterprise applications, and scientific computing.