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Future Trends in Data Lifecycle Management

By Geoff Hough, 3PAR Director of Product Marketing

It has been reported that ILM is so complex, its almost impossible. Even leading storage vendorswho advocate ILM as a means of cost optimisation have been known to characterise it as ajourney. This begs the question: is cost-effective data lifecycle management just a dream? Thisreview will attempt to answer this question by exploring proposed alternatives for achieving acost-optimised tiered storage environment.

ILM: The Endorsed ChampionInformation Lifecycle Management (ILM) pertains to classifying information at the informationlevel (e.g. records, messages, files, etc.) and then processing that information according tometadata policies established around those information structures. ILM was originally developedto meet document control and compliance requirements. However, over the past few yearstraditional storage vendors have co-opted ILM as a strategy for cost optimising storageenvironments. In these new ILM strategies, original functionality is extended to data movementbetween tiers of storage devices (each with different price/performance characteristics) in

accordance with established metadata policies. Provided all information is properly classified -- byno means a foregone conclusion -- the promise of ILM is a precise and accurate method of cost-optimising data over the entire data lifecycle.

However ILM was never intended as a means for cost optimising storage environments. As aresult, organisations must embrace a high degree of cost and complexity when implementing ILMfor storage cost optimisation. ILM requires multiple storage platforms, new processes, andapplication-specific software for classifying, moving and storing data throughout its lifecycle. Ofcourse, there is no shortage of professional services available to help users implement ILM. Aftersumming these costs and incremental management layers required for precise data classificationand movement, some will find that true net cost savings from ILM are small, distant or altogetherelusive.

Integrated Data Lifecycle Management: An Efficient Alternative?For organisations aiming to reduce their cost of storage, ILM may not be the best or only answer.In fact, an alternative approach called integratedData Lifecycle Management (DLM) promises togreatly reduce the expense and complexity of achieving dynamic, cost-optimised tiered storage.Integrated DLM can be deployed today and, unlike ILM, was designed specifically for the purposeof cost optimising storage environments. Integrated DLM enables organisations to achievestorage cost-optimisation by consolidating the disk-based data lifecycle onto a single, massivelyscalable and fully tiered array.

The storage infrastructure capable of supporting integrated DLM can also support ILM when andif necessary. For those organisations with strict compliance or regulatory requirements, storagearrays supporting integrated DLM can be deployed in conjunction with ILM for improved storageROI. The appeal of an integrated DLM strategy relative to traditional ILM-only approaches is the

avoidance of multiple devices and device management, large-scale information classificationprocesses and procedures, and application-specific software that add cost and complexity.Because integrated DLM is based on a consolidated storage infrastructure, it enablesorganisations to utilise common data management and administration tools across and betweenall service level tiers of storage. Storage arrays capable of supporting integrated DLM also offernon-disruptive volume conversion between data service tiers and the ability to move blocks ofdata (portions of volumes) to the appropriate service level automatically, based on policies set inand usage patterns observed by the array, for increased flexibility.

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What Is Right fo r Your Organisation?So, how do you determine what is right for your organisation? Consideration must be given to theamount of data, its growth, and the projected data lifecycle as it pertains to each application andthe required storage quality of service levels that must be delivered. Therefore, before choosing astorage cost optimisation solution, there are several questions you should ask:

What document control and compliance requirements must be considered?As already mentioned, ILM is a logical response for applications where document control andcompliance are required. However, if your organisation also requires a cost-optimised storagesolution, you will need to decide what tiered storage infrastructure is appropriate.

Traditional ILM solutions suggest several independent devices to cover the entire disk-basedlifecycle, as well as specialised compliance hardware such as WORM devices if needed. Anotherchoice for the underlying disk-based lifecycle could be storage platforms that support integratedDLM, as a compliment to any compliance hardware or software. Integrated DLM platforms offerconsolidated array management and data replication services while reducing fixed costs andenhancing data lifecycle ROI.

What additional investment is required?When considering a cost optimisation strategy, it is crucial to add up not just the incremental

hardware, software and licensing investment that must be made, but also the cost ofimplementation and ongoing management. Traditional ILM solutions anticipate a variety ofstorage devices to meet different levels of performance, availability, capacity and cost. However,with disparate devices and heterogeneity also come greater fixed costs, administrativecomplexity, and interoperability management. Additionally, there is the need to provisionmaximum capacity by tier and by application. In other words, to avoid constant manualprovisioning and adjusting of capacity, you will need to provision sufficient capacity by tier for thepeak amount of data that an application-specific ILM platform may transition through a given tierover a given period of time. Provisioning is not automated through the integration of ILM platformsand proprietary array device managers.

In the case of an integrated DLM-capable storage platform, you have the opportunity toconsolidate multiple levels of performance, availability, capacity and cost into a single, massively

scalable device. This diminishes fixed costs, administrative complexity, and interoperabilityissues. A storage array that supports integrated DLM can also provide a means of poolingcapacity across tiers and applications. Peaks and valleys of capacity demand for variousapplication/tier combinations can be dynamically balanced against one another, saving cost andincreasing ROI.

How will data movement be handled?Central to any data lifecycle management approach is the way in which data is understood andmoved through its lifecycle. These functions are essential to being able to place data onto theright storage tier at the right time in order to achieve optimal cost efficiency. ILM-basedapproaches examine data at the information level and move related data between storage tiers.

As we have seen, much of the savings resulting from this precision (to the extent it can beachieved) can be lost in the cost and complexity of implementing it, and in the blind peak

provisioning that must occur.

An integrated DLM storage platform offers two forms of data movement between tiers of storage:at the volume level and at sub-volume level. In each case, what may be lost in precision, relativeto ILM approaches that manage to deliver effective data classification, is made up for through thesimplicity and cost-effectiveness of implementing a single (not multiple) movement scheme, andthe substantial reduction in capacity from pooling capacity across applications and tiers. In thecase of volume level movement, highly virtualised integrated DLM platforms provide a simple andnon-disruptive method for converting the underlying service level of a given volume (e.g., disktype, RAID level, stripe width, etc.) This translates into a dynamic and flexible solution with no

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heavy up-front planning and provisioning and no incremental host, fabric or array-based migrationfacilities.In the case of sub-volume level movement, a storage array for integrated DLM takesadvantage of knowing when specific blocks of data were originally written and observing usagepatterns thereafter. This adaptive provisioning functionality automaticallymoves blocks of datato the appropriate service levels (up or down) within the same volume at the appropriate timeaccording to policy. Such an approach provides exceptional capacity utilisation, very granulardata lifecycle management, and low administrative overhead.

ConclusionOf course, users must assess their own requirements carefully and select appropriate solutions.This review has provided some core considerations for those looking forward to implementingdata lifecycle management. The good news for some is that an integrated DLM strategy may notbe such a remote or costly proposition after all.

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