| Guided reading | Years ago, the concept of hybrid cloud bursting was quite compelling, with workloads on both private and public clouds, and the ability to run those workloads on the private cloud during normal operation and burst when resources on the private cloud were low. Sending to the public cloud, how cool is that? But in 2018, there were not many bursts of hybrid cloud. |
Years ago, the concept of hybrid cloud bursting was quite compelling, with workloads on both private and public clouds, and the ability to run those workloads on the private cloud during normal operation and burst when resources on the private cloud were low. Sending to the public cloud, how cool is that? But in 2018, there were not many bursts of hybrid cloud.
There are several reasons for their absence, including:
Private cloud is no longer a thing. While some enterprises do use them, and private cloud companies still exist, for the most part, public cloud growth is happening. Enterprises need a private cloud to break out, and there are not many such private clouds.
Enterprises need to maintain workloads on private and public clouds for hybrid cloud bursting to work. Often, public and private clouds offer different sets of functionality and native APIs, and localizing software to the two clouds requires time and cost, and increases risk.
The obvious one: the explosive hybrid cloud concept adds too much complexity and cost to the technology stack (the cloud), mostly to get the most out of the enterprise. That's not to say hybrid cloud bursting doesn't work, but it's impractical or undesirable for most organizations.
Nonetheless, the cloud burst concept will have some practical uses, for example Microsoft has built a private cloud platform to emulate its public cloud (Stack), and those that have found the best burst approach is to use middleware that will loosely couple traditional internal Deploy the system to the public cloud.
The loosely coupled approach is attractive because businesses don't need to replace their on-premises systems with private clouds, just combine their on-premises workloads with a public cloud that can handle some of the processing. Use cases include keeping data in the public cloud but processing it locally, and vice versa. In this case, instead of trying to run the same workload in two different places, the enterprise separates the workload by function. This is why this method is gaining popularity.
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