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Getting smart about cloud provisioning

collinchau ‎01-30-2013 11:52 PM - edited ‎10-26-2015 08:26 PM

As organizations and their cloud deployments mature and evolve, IT leaders are looking to “get smart” in the provisioning of resources. The move from a private cloud to a hybrid environment can be tricky.  Proper provisioning maximizes resource utilization and reduces costs; all while ensuring cloud services are uncompromised. IT leaders need intelligent policy-based cloud workload management systems to help them understand performance targets, to proactively (automatically) take actions to comply with service-level agreements (SLAs).



What defines a policy-based workload management system?



IT teams need automated provisioning based on user needs and quality-of-service goals for specific services. But, IT project planners need to know the cost and resource consumption of each request before they grant approval. Luckily these fine-grained policies are defined by HP Cloud Service Automation (CSA) within Moab® Cloud Optimizer from Adaptive Computing as part of a service design—where service request parameters are fulfilled through Moab. This policy-based workload management system of governing decides how resources are deployed via an automatic, complex set of decisions and processes.


These automated actions  allow you to :


  • Allocate optimal set of diverse resources for incoming service requests to avoid service failures
    • E.g. check whether a VM is heavily utilized before provisioning another workload on it
    • E.g. tag a workload as “high priority” and have it be provisioned to a dedicated VM that has the maximum amount of available unused CPU power
  • Optimize workload placement to maximize resource utilization by 20 to 40 percent
    • E.g. assign “non-critical” workloads and have them packed into a single VM
    • E.g. select specific datacenters when users subscribe to a specific workload/service
  • Dynamically adapt resources and infrastructure to respond to changing service needs and conditions
    • E.g. choose fine-grained attributes of a resource to map workload requirements exactly with the resource as and when it is needed to be delivered
  • Resource and workload reporting, capacity planning and policy management to optimize performance 


Besides the use of fine-grained policies as defined by CSA, the option exists for the use of pre-defined global placement policies by Moab for use. Powerful, pre-built content that allows IT to get up and running faster—and more efficiently.  


Learn more about dynamic workload management for the private cloud from the attached business white paper. Where CSA augmented with Moab® Cloud Optimizer from Adaptive Computing, delivers the management capability that IT needs to effectively implement and continue to grow and evolve the cloud. CSA provides the automation capabilities. Moab Cloud Optimizer helps address the more complex and advanced stages of a cloud implementation with policies and guidelines for allocating resources and adapting to changing data center environments. For more information, go to





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