The cloud is not a single location. It is a combination of private, public and hybrid cloud locations and an organization may have several of each. The cloud aspect means that data and workloads should move seamlessly between these locations. The problem is that each location is not the same and the data may need some kind of transformation so it can operate in a different location. In addition there will be times where there should be a prohibition for certain data sets to move to a particular location. Data sovereignty is a good example. Organizations need an intelligent virtual repository that will enable data to not only move to different cloud locations but also transform data so that it will work in the location it needs to move to.
Centralized But Not Primary
The virtualized storage repository can not be primary storage. Primary storage needs to be static and close to the running workload or user. It should also not have the responsibility managing the distribution of that data to other points within the cloud infrastructure. The virtual repository should be a combination of secondary storage and software so it can store data cost effectively, versioned, indexed and managed.
A challenge, then, is moving data from production storage into the virtual repository. Obviously this can’t be a manual process and the organization will resist, with good reason, the addition of yet another product that moves or copies data. A modernized data protection application could be the ideal answer. It has to frequently protect, production data anyway. Extending that software to create a virtual storage repository is an ideal solution to the problem.
More Than Just a Storage Tank
The virtualized repository also has to be more than a gigantic storage landfill. It has to be able to protect, secure, organize and manage data while it is in the repository and during its removal. These requirements mean that the solution needs to understand what it is storing through both the use of metadata tags as well as a contextual investigation. The repository can leverage this information to make sure that data is distributed correctly based on need and data sovereignty.
The Virtual Data Repository could also use the contextual information to understand how a workload needs to transform. For example if it understands a VMware image that it stores will go to Amazon ECS, the software managing the repository should transform the image to make sure it works in its new location.
A CloudFirst strategy is a new objective for organizations. More than likely the organizations will have legacy physical and virtual environments they will need to maintain and ultimately transform into a more cloud ready environment. If fact many of these organizations may have even had a VirtualizeFirst strategy before adopting a CloudFirst strategy. But as we discussed in other entries, a CloudFirst strategy differs from a VirtualizeFirst strategy both in terms of location and the level of automation.
To help make the transition to a CloudFirst strategy organizations need to transform existing workloads into cloud-ready workloads. They need a virtual data repository that is more than just a storage dumping ground. That repository needs to be intelligent so it can understand the data it stores. Armed with that information it can, when the use case arises, automatically manage and transform data.
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