Cloud Computing – Measurement and Governance in the Cloud

.5 day to 2 day formats (customized based on your interests, tools and models/ frameworks)

 Purpose:  This workshop will benefit those who are interested in measurement for cloud computing environments.  This includes metering, migration, development and support. These are often part of cloud Service Level Agreements support overall governance of the cloud.
Metering and measurement is a critical core characteristic of cloud computing, therefore we need to understand the typical measures, metrics and analytics that are applicable for the cloud. This workshop will help identify strategies and approaches to prioritize and define
your own governance approaches  for cloud computing.

 Topic Areas:

  • Measurement integration into the cloud
  • Metering in the cloud (pricing models)
  • Resource measurement
  • Estimation migration to the cloud
  • Estimation development and using services in the cloud (IaaS, PaaS, SaaS, XaaS)
  • Estimation maintenance in the cloud
  • Testing and quality in the cloud
  • Cloud goals and objectives
  • Cloud roles and activities with goals/ objectives
  • Costing and return-on-investment
  • Risk measurement
  • Business value measurement
  • ITIL in the cloud
  • Auditing in the cloud
  • SLAs in the cloud

  Upon completion of this workshop the student will be able to:

  • Understand the multitude of metering and measurement types that should be considered to help maximize your cloud return-on-investment and manage risks
  • Understand how the NIST roles, with specific goals and objectives drive measurement
  • Use measurement well within the cloud, not rigidly

 Exercises: Several case studies will be discussed and reviewed, involving your own scenarios and situations to help drive your cloud measurement initiative.

 Of Interest to:  Functional Analysts, Function Point Specialists, Estimators, Software Architects, Developers, TM Forum Members and others who want to gain an understanding of cloud computing measurement and analytics.

Prerequisites:  “Cloud Computing an Introduction to the Reference Architectures and Models” or a good understanding of generic cloud computing models/ terminology