Storage Management Strategies for the CIO
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You can conquer IT infrastructure challenges by rethinking ownership and functional processes.
However, a current of change is propelling us away from business-as-usual systems. Server virtualization and related technologies are causing organizations to reconsider not only IT infrastructure design and architecture, but the lines of demarcation between functional responsibilities and new/updated operational processes. For example, many of the benefits associated with server virtualization are dependent upon a storage infrastructure optimized to support it; without proper planning, however, an unintended consequence might be a substantial increase in storage consumption and a decrease in utilization.
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to just-in-time Surveys indicate that while most firms are adopting server virtualization for financial reasons such as infrastructure consolidation and improved TCO, there are also high expectations for improved service delivery capabilities. An often-cited benefit of virtualization is ease of management, particularly the ability to quickly create, relocate and tear down virtual servers. A prime example of the interdependence of servers and storage is the provisioning process. The ability to provision a server in a virtualized environment shrinks from weeks to days or even hours. However, if the requisite storage still takes weeks to provision, the net benefit to the organization may be lost. In the pre-virtualization days, server and storage provisioning times tended to be roughly equivalent and were therefore reasonably in sync. With the adoption of server virtualization, storage now becomes a major bottleneck. How do we address this? Anyone who has dealt with IT performance issues knows that one way to deal with bottlenecks is to create buffers. If we decide to overpurchase and overallocate storage to keep ahead of server provisioning demands, we can, in a sense, mitigate the problem, but at a substantial cost when it comes to efficiency. When we consider that storage is often overallocated because of limited forecasting ability, we run a significant risk of making a bad situation worse. How is this addressed in other supply-chain models? Consider a manufacturing facility with multiple assembly lines where various subsystems are built and must come together at precisely the right time. Many years ago, these firms adopted a just-in-time approach as the most efficient way to meet their needs. In contrast, IT has operated on a just-in-case basis, forfeiting efficiency for serviceability. Server virtualization disrupts that model and will drive related functions to modify their approaches.
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This was first published in May 2008
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