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Virtualization: Article

Virtualizing onto Mainframes

How to analyze workloads to determine fit

The flexibility, efficiency, and reduced cost of ownership virtualization provides makes it extremely compelling to large and small organizations alike. Increasingly IT organizations are contemplating virtualization across all platforms.

As this trend makes its way deeper and deeper into the data center, organizations are starting to leverage the fact that virtualization also lifts many of the constraints that govern which platform an application needs to run on. Different types of applications possess different workload “personalities” and these heavily influence how well an application will perform on a given virtualization model.

Some workloads possess certain characteristics that make them ideal for consolidation onto mainframes. In this article I’ll discuss these characteristics as well as the overall process for analyzing existing IT environments to determine the optimal approach to consolidating workloads onto the mainframe platform.

Analyzing Workloads onto Mainframes
Partitioning, hypervisors, containers, and other approaches can all be used to allow workloads to co-reside on a common platform. Given the relative strengths and weaknesses among platform classes, a considerable amount of diligence is required when consolidating workloads between them. This involves understanding which applications will run on the mainframe, which applications will experience the most benefit by moving, and what they will look like after the transition. In practice, it’s even more important to understand the subtlety of such a transformation, particularly when the overall goals are to optimize the benefits while at the same time minimizing the risks.

By modeling transformations in terms of the constraints that govern them, it’s possible to chart a course that reaches the end goal while not going off side in the process. These constraints can be classified into three categories:

  1. Technical Constraints: What can go together
  2. Business and Process Constraints: What should go together
  3. Workload Analysis: What fits together

More Stories By Andrew Hillier

Andrew Hillier is CTO and co-founder of CiRBA, Inc., a data center intelligence analytics software provider that determines optimal workload placements and resource allocations required to safely maximize the efficiency of Cloud, virtual and physical infrastructure. Reach Andrew at ahillier@cirba.com.

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