This tutorial opens the door for the ICAC audience to apply some of the autonomic computing ideas to the optimized deployment of workloads in the cloud. We have designed the tutorial to have two parts: (I) Overview of cloud management, OpenStack, Heat, and HOT technologies; and (II) Optimization algorithms for solving the large-scale placement problem of workloads in the cloud, in a scaleable manner. Part I acts as an introduction to the area for those who may be experts in autonomic computing, but are not quite familiar with the state-of-the-art of cloud management. And, part II should appeal to the theoreticians and application-oriented in the audience alike.
Overview of cloud management (1.5 hrs):
Overview of OpenStack open source cloud software
Heat template-driven orchestration engine
HOT: The Heat orchestration template
Cloud workload definition
Architecture of a workload placement engine
End-to-end flow
Workload Optimization (1.5 hrs)
Definition of workload placement optimization problem
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