Tiered storage: does all data have to fly first class? - Storage Networking

Computer Technology Review, Feb, 2004 by Tad Lebeck

The notion of tiered storage--of allocating applications' different types of storage based on performance, availability and recovery requirements--has been an oft-discussed, yet seldom implemented practice since the advent of SANs. The practical reality, however, is that managing multiple tiers of storage service and delivering these services to the applications that need them has proven to be a labor-intensive business. What's more, in the absence of tight process and policy control, the risk of under-provisioning critical data has far outweighed the savings attributed to tiering. As a result, in order to simplify operations and certify that service levels for mission-critical data are met, the default option for most IT departments has been to deliver a single class of high-performance, high-availability service to all data. But it begs the question: Does all data truly need to fly first class?

Tiered storage can involve one or more strategies:

* Provisioning cheap vs. expensive disk, based on availability or performance needs

* Allocating different levels of data protection, based on recovery requirements

* Migrating data to different classes of storage as requirements evolve, e.g., ILM.

Each of these strategies comes with its own implementation issues' and tradeoffs between savings, operational complexity, labor cost and risk.

Matching storage price performance to application need has a very straightforward value proposition. Placing low value data on inexpensive disk, such as ATA devices, can carry a hardware cost of less than $7 per gigabyte. This compares with high-speed, high-reliability arrays that can run more than fifteen times as much. In addition, allocating storage to applications from different device types is also a relatively straightforward management proposition from a policy compliance perspective. But cheap versus expensive is a strategy best suited for larger enterprises with enough data in different classes to justify the expense of acquiring different classes of storage devices, and training staff on the different tools required to manage them.

Provisioning different levels of data protection offers perhaps the most widely applicable and cost-effective tiering strategy. Not all data requires mirroring, local or remote replication to meet availability and recovery requirements. But arrays in most IT departments are configured to deliver at least mirrored, if not replicated, storage to all data. One storage administrator joked to me that this was his "make a copy of this before you throw it away" policy. Configuring LUNs with different levels of data protection and allocating these to applications based on business requirements can save as much as 30% over provisioned, high-performance storage capacity. But managing different levels of protection is a labor-intensive process, and tight policy control is required to certify that critical business data is never under-provisioned.

Finally, migrating data from high-performance, high-availability storage to lower cost media as the data becomes less critical can further optimize asset utilization. However, this strategy assumes that tiering policies and practices for initial provisioning are in place, and that companies have a firm grasp on the metrics that determine when data evolves to require a lesser tier of storage service. More importantly, if data is migrated, what circumstances will dictate its return to "critical" status, and can re-provisioning be accomplished in a compliant fashion?

Increasing pressure to improve IT cost structure, coupled with the emergence of process automation tools that simplify operations and enforce policy compliance for service delivery, now presents a more practical risk-reward equation for tiered storage. Software to automate and control the process of storage service delivery differs from traditional monitoring tools by allowing IT departments to package the systems operations, human work-flow and policies required to deliver a specific class of storage to a specific application--then deploy these "packaged services" as a repeatable, software-automated process. Process automation software can reduce the labor and complexity involved in supporting multiple tiers of storage service. More importantly, these tools effectively bind service tiers to applications enforcing compliant service delivery. As the gap in price between classes of storage technology continues to widen, the justification for implementing a tiered storage strategy is becoming more compelling. But most IT departments today don't have documented processes and policies for service delivery. Many that do, still struggle with enforcing and measuring operational compliance. And most automation has been implemented through scripting of practices and policies that have evolved in the context of a manual storage supply chain. From this starting point, how does one evolve to tiered storage services without placing the company's data at risk, or burying already shorthanded staff in a project heavy on documentation and light on implementation?