Moore’s Law, Latent Demand, and the Slowing of Cloud Computing

Cloud computing helps cope with variable workloads. The inherent inefficiencies in using cloud are outweighed by the savings in not having to configure an on-premise data center with sufficient capacity to handle peaks in demand. Cloud is, of course, never as efficient as on-prem simply because of the cost, complexity, and overhead of running your work on someone else’s machine; tuned, configured, and instrumented by strangers to meet their business goals, and located at the other end of a network connection.

For organizations that have relatively stable workloads, local, on-premise computing makes more economic sense. In the early days of cloud computing, the simplicity of running variable workloads on the spare capacity in another, much larger, firm’s data center made sense tactically. Strategically, Moore’s law guaranteed that eventually the cost of computing would come down, undercutting the cloud vendors’ margins, turning the cloud market into a classic red ocean with vendors competing on price alone. But that collapse took much longer than expected, due to latent demand. Organizations reaped the financial benefits of cloud migration for a decade or more before running into price problems.

Latent demand refers to work that was not done because the data center didn’t have enough capacity. For those parts of the organization which had work to do but couldn’t build a business case to justify the on-premise capacity for it, cloud was a wonderful option. These pockets of demand followed the mantra of “OpEx not CapEx” that led some organizations

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