The last 5 years of IT evolution has forced enterprises to re-think their corporate strategy to stay relevant and competitive. These enterprises are looking to become lean so they can focus on their core business while outsourcing the rest. Applications and the associated data, the crown jewels of an enterprise are meanwhile anchored in legacy data-center environments.
The revolution around data-center infrastructure modernization has already happened with the increasing adoption of public and private clouds. Software defined networking and portability of application binaries have further helped this transition. Virtual machines and application binaries can be deployed on new cloud frameworks with a push of a button. However, application binary without data is like body without a soul. Unshackling data from its infrastructure and making it portable is essential for enterprises to fully embrace this evolution.
Enterprises as we all know run a wide variety of applications and require a solution that can handle all of the associated data. To deliver Enterprise Data-as-Service (EDaaS) effectively, the solution has to understand the DNA of a wide variety of applications (SQL, Oracle etc) and must be able to virtualize all of their associated data and metadata in an application consistent fashion. Application binaries will be unable to use this data when presented without application consistency. Enterprises also will not adopt a solution that only works with a small subset of their applications. EDaaS solution has to thus scale to handle a wide variety of enterprise applications.
Organizations are opposed to solutions that require an overhaul of their tool set, thus requiring re-training their vast IT staff. Ideally the EDaaS solution will virtualize application data while seamlessly integrating with the organization’s tool set that manipulate this data. Like a wide variety of applications, enterprises also have a wide variety of tool sets. The EDaaS solution should have comprehensive API support so it can be integrated into these developer tool sets ( jenkins, Ant, maven to name a few).
After they have tackled their application and tool-set domain enterprises look for data portability. Organization’s application infrastructure has evolved over time and thus the associated data is store on varied infrastructures – some in the cloud (could be one more clouds), some in a local SAN and some in disks attached to a physical server. The EDaaS solution must be capable of virtualizing data from all of these disparate sources and should present unified interface to access this data anywhere the organizations desire. For instance a large bank trying to migrate applications from their data center to AWS must be able capture application environment in their data center and present it on AWS infrastructure. The organization’s tool sets should then integrate and work seamlessly with data in its new location. This has to be done across the enterprise’s application suite and across the infrastructure that houses the data today.
The final frontier is to ability to scale out the deployment as data grows and efficiently manage the EDaaS solution. Enterprise data as we know is constantly growing and also have varied recovery requirements. Mission critical applications must have little to no down time while less important applications can have a more relaxed Recovery Time Objective. To tackle aggressive enterprise data growth the EDaaS solution must support a scale out architecture with centralized management. Organizations must be able to deploy this solution on demand and should have the capability to elastically scale this up and down per their needs. A central management console is crucial to monitor, troubleshoot and fix problems. The organization backing the EDaaS solution must have enterprise grade services and support for installation and break-fix. The services and support organization must have process and bandwidth to scale up as deployments get larger and more complex. You can read more in-depth by downloading this whitepaper.
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