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Virtual machine hypervisor doesn't play a critical role in HCI choice

Hyper-converged infrastructure is about simplifying IT administration, so organizations should be after simple, automated hypervisor configuration and management.

A hypervisor is an integral part of any hyper-converged infrastructure implementation, but the brand of virtual machine hypervisor that IT departments use in an HCI deployment is not important in the long run.

Simplifying ongoing IT operations is the endgame of HCI; IT administrators want to reduce or eliminate hypervisor management tasks, which inform buying decisions. And IT departments standing up an HCI might want to use the same virtual machine hypervisor they're used to. But vendors that package hypervisor technologies with their HCI products hope IT departments will use those tools.

To be clear, hypervisors are not an interchangeable commodity. An IT admin is unlikely to use a virtual machine hypervisor that requires deep tuning and configuration for an HCI deployment. HCI ideally suits scale-out workloads, general-purpose virtualization and mainstream, business-critical applications. HCI is less adapted to support huge virtual machines (VMs) -- such as those that require quad-socket physical servers -- and some niche uses, such as high-frequency stock trading.

An IT admin is unlikely to use those hypervisor technologies that require deep tuning and configuration for an HCI deployment.

For the majority of deployments, there are a small number of standard configurations that work with specific hardware combinations. Automatically deploying these standard configurations is part of HCI's value. Ultimately, most customers shouldn't care which virtual machine hypervisor they use or how to optimize it.

Resource delivery more important than consumption

IT admins must care more about how their systems consume resources and spend less time worrying about how resources are delivered. Part of the value of a HCI platform is that it should configure the entire hypervisor automatically. The platform should automatically apply the correct advanced settings and configuration for the best reliability and performance. When that happens, the IT department can spend its time looking at VMs and making sure the applications inside the VMs are running optimally.

Another way to think about this is to approach HCI similarly to VMs in the public cloud. Customers do not care that Amazon Web Services uses Xen as its hypervisor and Google Cloud Platform uses Kernel-based Virtual Machine (KVM), nor do they care that Microsoft's Azure uses some variation of Hyper-V. Customers care about the VMs they work on. Not caring about what is under the VM is a central part of using public cloud infrastructure-as-a-service products. Apply the same principle to a private cloud delivered on top of an HCI platform: "I get my VMs, and I don't care what hypervisor supports the HCI."

An example of an HCI where customers don't care about the virtual machine hypervisor is Scale Computing. Under the hood, Scale uses KVM as a hypervisor, but customers never see KVM. There is a Scale Computing management layer that is centered on the VMs, and it is this management layer that the clients use. Scale has a whole expert system to manage the system; it takes care of optimal settings and system health. Customers just run VMs and make sure the applications inside these VMs do their job.

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