Storage Soup

May 14 2014   9:32AM GMT

Storage lifespans: don’t confuse technology with data

Randy Kerns Randy Kerns Profile: Randy Kerns

Clarification is needed about what lifespan means regarding storage because confusion is created by the way product messaging refers to both in the same context.

Lifespans of storage systems refer to many things: wear-out mechanisms for devices, technology obsolescence in the face of new developments, inadequacies of dealing with changing demands for performance and capacity, and physical issues such as space and power.

The wear-out mechanisms are tied to support costs, which typically increase dramatically after the warranty period that could run three years to five years in enterprise storage systems. These issues all lead to a cycle of planned replacement of storage systems, often triggered by the depreciation schedule for the asset.

For the information or data stored on a storage system, the lifespan depends on the characteristics and policies of that data. Information subject to regulatory compliance usually has a defined lifespan or period of time it must be retained. Other data may have business governance about retention. Most of the data is not so clearly defined, and is left to the owners of the data (business owners in many discussions) deciding about the disposition. Typically, data is retained for a long time – perhaps decades or even forever.

There is confusion about how to update the storage technology without regard to what is the content stored. This requires changing technology without disrupting access to the data, without requiring migration that entails additional administrative effort and operational expense, and without creating risk of impacts or data loss. These concerns are addressed with the many implementations of scale-out technology delivered with NAS or object storage systems.

Clustering, grids, ring, or other interconnect and data distribution technologies are key to scale out. Nodes can be added to a configuration (cluster, grid, ring, etc.) and data is automatically and transparently redistributed. Nodes can be retired – automatically where data is evacuated and redistributed and once empty, the node can be removed – all with transparent operation.

These scale-out characteristics allow storage technology to progress: new technology replaces old. This usually happens within the constraints of a particular vendor software or hardware implementation. The important development is that data is independent of the storage technology change.

For data, the format and the application are the big issues. Data may need to be converted to another form whenever the application that can access the data changes (meaning there is no longer support for that format, etc.). Being able to access data from an application is more important than merely storing information. The ability to understand the data is independent of the storage. Updating technology and progressing data along the storage technology improvements is possible and is being addressed with new scale-out systems. Dealing with formats that persist over time is another issue that can be independent of the storage technology.

(Randy Kerns is Senior Strategist at Evaluator Group, an IT analyst firm).

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