VMware Cloud on AWS – Technical Deep dive

Raja Roychoudhury, Head, Infrastructure Software Services at MindCraft, explains how IBM Cloud Private can be used to leverage on-premises private cloud infrastructure to run your cloud-ready application.

Data is increasingly becoming a crucial asset for organizations to survive in todays fast moving business world. In addition, data becomes more valuable if enriched and/or fused with other data. Unfortunately, enterprise data is dispersed by most organizations over numerous systems all using different technologies. To bring all that data together is and has always been a major technological challenge.

Data science requires vast amounts of data. And that too from multiple sources. Data virtualization integrates the data across these disparate sources and provides a unified view of the data to data science algorithms. With it, data scientists can deliver important answers to business questions that enable the business users to perform their functions efficiently.

In spite of the clear success of the hyperscale public cloud providers, many organizations – due to cost, control, refactoring complexity and data sovereignty issues – are choosing to host many workloads with regional cloud service providers (CSP), in colocation/interconnection facilities or to simply keep workloads on-premise. These data center operators, whether xSP or enterprise, typically already manage multiple data centers today. With the growth of IoT and edge compute on the horizon, they need to prepare to deploy and manage 10’s if not 100’s of mini- and micro-data centers in the future.