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If there’s one overarching learning COVID-19 has taught IT leaders, it’s that businesses need flexible IT infrastructure that is adaptable to constant or rapid change. Many find that synonymous with a cloud infrastructure. But there are a lot of components to think about when considering how – and on which platform – to move your data to the cloud. Increased complexity, a plethora of cloud services to choose from, and countless vendors claiming to be the best way to enable your cloud transformation make this a daunting task.

Where to start? Most organizations already have rich legacy infrastructure in place, so the story of ripping and replacing entire infrastructures in the cloud is tired and unrealistic. You could make a list of requirements and check off boxes as you sort through your options – but a features and functions comparison may be an overwhelming place to start.

There are a few higher-level questions and requirements to approach and ensure first.

Achievable

The notion of achievability relates to your organization’s path to the cloud. There must be a path other than rip-and-replace. 451 Research surveyed IT leaders on how they will modernize their most mission-critical, legacy applications, and a couple of popular paths emerged. While the “lift and shift” method has become less popular, there was an uptick in two strategies:

  1. the choice to modernize-in-place, with hybrid cloud environments likely playing a role in the overall strategy, and
  2. the choice to “refactor and shift” which “involves application refactoring using cloud-native frameworks prior to redeployment in off-premises cloud environments.”

Both in-place modernization and “refactor and shift” are incremental approaches that are more likely to succeed in the long run, especially with mission-critical systems that must remain available to the business during the transition. Key to the success of either strategy is a technology that allows you to wrap your existing on-premises systems with an API abstraction layer, and then seamlessly migrate to your cloud platform of choice – leaving you with the flexibility to decide which systems and APIs to move, and when to move them.

Flexible

A cloud-based infrastructure provides enterprises with agility – a main driver of digital transformation. While you’re on this train of thought, decide the level of flexibility you need when it comes to managing your data. The ability to handle multiple use cases in the same system will call for a multi-model platform, rather than multiple specialized engines. This means document, semantic graph, geospatial, and relational modeling capabilities in a single platform. Gartner states:

Developers are increasingly challenged to choose between specialty engines and existing multimodel DBMSs to match their target use cases — especially for use as services for cloud deployment.

A multi-model solution allows organizations to choose the right mix of data models for a given use case without sacrificing data consistency. This may be more cost-effective as it’s suitable for a large percentage of use cases, and the ability to store and query multiple data models in one platform results in unprecedented flexibility.

Unified

Organizations need to be able to track data and metadata together, and have the capability to govern and secure their data all in one place. There may be a separate tool for everything these days, whether it’s data integration, storage, search, or mastering, but that doesn’t mean you should necessarily piece together your cloud architecture that way. Bringing all of this together in one platform will allow for a consistent, real-time view of all data, rather than a bunch of data silos. The level of security and synergy that comes from a unified architecture will result in a durable data asset, and moreover, operational simplicity.

Migrating to a modern, cloud-based data infrastructure is an important step in the quest for digital transformation. It’s appealing to think about simply building a new infrastructure in the cloud and then shifting your whole business there. But this is the high-risk approach. A more incremental approach with a flexible technology infrastructure – that can wrap and abstract your legacy systems – will let you prioritize projects with the highest risk-adjusted return, and learn as you go without risking business continuity.


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