Are Your Capacity Management Processes Fit for the Cloud Era?

VMTurbo

An Intelligent Roadmap for Capacity Planning 

Many organizations apply overly simplistic principles to determine requirements for compute capacity in their virtualized data centers. These principles are based on a resource allocation model which takes the total amount of memory and CPU allocated to all virtual machines in a compute cluster, and assumes a defined level of over provisioning (e.g. 2:1, 4:1, 8:1, 12:1) in order to calculate the requirement for physical resources. 

Often managed in spreadsheets or simple databases, and augmented by simple alert-based monitoring tools, the resource allocation model does not account for actual resource consumption driven by each application workload running in the operational environment, and inherently corrodes the level of efficiency that can be driven from the underlying infrastructure. 

Read this whitepaper for these 3 takeaways:

  1. The complexities of pursuing efficient capacity planning
  2. How to define functional requirements for your capacity management strategy
  3. A capacity management strategy that assures service levels while reducing performance risk and hardware footprint

Tags : capacity planning, vmturbo, resource allocation model, cpu, cloud era, it management, knowledge management, enterprise applications


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Published:  Mar 25, 2015
Length:  10
Type:  White Paper