Hyperscale: Redefining The Economics Of Datacenters

Over the years, businesses have relied on datacenters to manage their applications and data cost effectively. However with changing business needs, these traditional datacenters often end-up becoming siloed in the way they manage workloads.

- Nitin Mishra

Digitization has turned notions like scalability and customer engagement on their heads. As the digital ecosystem has evolved exponentially over the last decade, it has become extremely simple for individuals, teams and organizations to scale to hundreds of millions of users and devices (smartphones, tablets, sensors, wearables, apps) across the world. In an earlier time, typical brick and mortar businesses (such as retail, banking, and aviation) have taken decades to build this kind of capability.

Not surprisingly, the lead on creating Hyperscale businesses was taken by technology giants. Companies like Google, Amazon and Microsoft have, over the years, proven that it is not only possible, but also extremely cost-effective to build Hyperscale systems with unmatched levels of reliability and virtually unlimited scalability – to serve a consumer base that runs into hundreds of millions. Prime examples being some of their own products – Google’s account base is upwards of 2.5 billion, and its search engine processes nearly 4 billion queries each day.

The notion of Hyperscale has now transcended the initial use cases (such as email, e-commerce, search, location tracking, etc.) to now find application in traditional consumer businesses. For example, mobile banking, wallets, food ordering apps, patient engagement portals, etc. With digital transformation, traditional businesses can very quickly overcome operational and customer engagement limitations. The challenge for these organizations is to leverage the vast amounts of data at their disposal, to drive innovation cost-effectively, and at unmatched scale. We are already seeing multiple examples of Hyperscale models enabling economic growth and customer value that was not possible earlier: 

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