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Gartner research director Richard Watson once observed, “When the CIO issues the straightforward directive: ‘Move some applications to the cloud,’ architects face bewildering choices about tips on how to try this, and their decision must consider an organization’s requirements, evaluation criteria and architecture principles.”

Unfortunately, many architects assume that migrating your legacy systems means migrating your applications to the cloud. However, the truth is that this sort of migration involves both data migration and alertness migration. Each of those need to be assessed, planned, designed and executed separately after which integrated. They’re two parts of the identical migration of a legacy system, but each requires different analysis steps and different skill sets.

By concentrating on your data migration separately out of your application migration, you may guantee that both will scale properly.

It’s worth noting that government agencies are taking the lead during this area. For instance, the dep. of Defense Cloud Computing Strategy requires both metadata tagging and an information cloud which will implement “data-as-a-service” (DaaS). The creation of that requires separating the appliance from its data throughout the migration phase. Here’s the identical strategy that the Intelligence Community is pursuing with its community cloud.

[ Would like to learn more about DOD cloud plans? Read Defense Dept. Seeks $450 Million Cloud Builder. ]

The goal of both data and alertness migration to the cloud is to realize scalability and elasticity. Your general migration model for analysis is to begin with a transparent understanding of the sources of the applications and information to be migrated, examine your options in attaining scalability, after which select the objective implementation that achieves those objectives.

That specialize in the source to your data migration, that you must observe how your application currently stores its data. Typically it really is in a single of 3 ways: in a relational database management system (accessed via SQL), in a no-SQL data store, or in files at the file system. Your first assessment is whether or not your data has to be scalable in relation to processing and cupboard space . On your target options the most important cloud providers all offer SQL stores, no-SQL stores and BLOB (binary large objects) storage.

Data migration comprises three parts: the migration lifecycle for your data subsystem, the transfer of legacy data, and, finally, the mixing with the remainder of the migrated application. Let’s have a look at each in additional detail:

1. Data Migration Lifecycle

Very similar to your systems development lifecycle (SDLC), the migration lifecycle begins with an assessment phase rather than a requirements phase. Additionally, the advance phase is replaced by the migration phase. I explain this in greater detail in my new book, The Great Cloud Migration; for now, suffice it to claim that data migration is classed by cloud platform type, scalability requirements, data type or by data volume. On the end of the assessment you will want selected a target implementation that achieves your scalability and elasticity goals.

2. Transfer Of Legacy Data

Moving your data out of your legacy data stores to the cloud is a novel opportunity for quality controls, metadata tagging, data dictionary, data lineage and other data management best practices. Whilst you could assume your data is okay and choose to move it without change, leveraging the cloud migration to wash and harmonize your data across your corporation is a golden opportunity. Some organizations may fit even further and look to cloud migration as a chance to centralize their data and abstract it via an enterprise data layer.

3. Integration With The Migrated Application

Once your connectivity to the objective platform is done, you should integrate your data storage subsystem with the remainder of your migrated cloud application. This integration is dependent upon how loosely coupled the info storage subsystem is with the remainder of the appliance.

By concentrating on your data migration separately out of your application migration, you may ensure that both achieve your goals for scalability, elasticity and metered billing.

Forgetting the stairs had to migrate your data would be costly from both a migration perspective and an enterprise perspective. Instead, seizing upon your cloud migration as a chance to implement enterprise-wide information management practices may help the organization become more efficient and better even as. Yes, you may have killed the proverbial two birds with one stone!

Bold visions are competing with practical budget realities for federal IT leaders. Our latest annual survey looks on the top IT priorities. Also within the new, all-digital Tech Priorities issue of InformationWeek Government: IT leaders are making progress improving the efficiencies of their IT operations, but many lack the tools to prove it. (Free registration required.)