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Automated planners for storage provisioning and disaster recovery

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11 Author(s)
Gopisetty, S. ; IBM Almaden Research Center, 650 Harry Road, San Jose, California 95120, USA ; Butler, E. ; Jaquet, S. ; Korupolu, M.
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Introducing an application into a data center involves complex interrelated decision-making for the placement of data (where to store it) and resiliency in the event of a disaster (how to protect it). Automated planners can assist administrators in making intelligent placement and resiliency decisions when provisioning for both new and existing applications. Such planners take advantage of recent improvements in storage resource management and provide guided recommendations based on monitored performance data and storage models. For example, the IBM Provisioning Planner provides intelligent decision-making for the steps involved in allocating and assigning storage for workloads. It involves planning for the number, size, and location of volumes on the basis of workload performance requirements and hierarchical constraints, planning for the appropriate number of paths, and enabling access to volumes using zoning, masking, and mapping. The IBM Disaster Recovery (DR) Planner enables administrators to choose and deploy appropriate replication technologies spanning servers, the network, and storage volumes to provide resiliency to the provisioned application. The DR Planner begins with a list of high-level application DR requirements and creates an integrated plan that is optimized on criteria such as cost and solution homogeneity. The Planner deploys the selected plan using orchestrators that are responsible for failover and failback.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Journal of Research and Development  (Volume:52 ,  Issue: 4.5 )