“CPU Partitioning”: When CPUs on a server are separated into individual sections where each section acts as a separate system. Sometimes this is called “segmenting.” There are several hardware and software partitioning technologies available that deliver partitioning capabilities, with varying degree of resource allocation flexibility.

VESL recommends only Oracle Certified CPU Partitioning to be implemented for Oracle Product Stacks.

Minimize CapEX

  • More applications(VM's)per server
  • Reduce server footprint, power and cooling
  • Consolidate current and aging Oracle app's into one single integrated platform

Minimize OpEX

  • Manage many applications/OS's as one
  • Standardized, automated procedured & services levelsvirtualization 1
  • Rapid provisioning and re-deployment of applications
  • Manage the Cloud stack out of OEM12c

Maximize Agility

  • Cloning for development/testing
  • Scalability, one compute node at a time
  • Trusted Partitioning for optimized license costs
  • Windows,Solaris,Linux workloads supported

Ease of Adoption

  • Applications run unchanged based on standards
  • Simplify IT on integrated stack

Why Virtualization?

Database Administrators (DBAs) often partition servers to achieve the following benefits:

  • Ability to run multiple operating systems, or multiple versions of an operating system, on the same server
  • Ability to improve workload balancing and distribution by managing processor, memory or even storage allocations across applications and users on the server
  • Ability to leverage hardware models such as “Capacity on Demand” and "Pay As You Grow.”
  • To run or create Test / Development environment without wastage / adding resources
  • Less maintenance and support charges
  • Easy to backup / restore / clone
  • Achieve high-availability without investing huge costs

Key Factors / Decision Criteria

  • Operating Cost
  • Technical Architecture
  • Hardware maintenance and expansion
  • Oracle Product Licensing
  • Applications Installed and Used
  • Business Process
  • Data management and growth