Cloud and Virtualization - A Case of Déjà Vu

As today's businesses increasingly turn to the cloud to run their operations, seasoned enterprise technology professionals may recognize a familiar pattern. Years ago, virtualization emerged as a transformational technology with a similar pattern of business drivers; initially the promise of significant cost savings justified deployments. Just as virtualization evolved from a tactical cost-saving technology into a corporate strategy enabling enterprises to be responsive to changing business demands, cloud computing is following a similar path.

I talk frequently with IT professionals about their interest in and usage of cloud technologies, and I'm frequently struck by a strong sense of déjà vu from the time when virtualization was starting to take off and gain traction within enterprises across the globe. Virtualization was the seed that sparked the cloud revolution, although cloud has now taken its concepts significantly further. From the business drivers that drove adoption to usage patterns and issues around managing sprawl, there have been some remarkable similarities between cloud computing and virtualization.

The initial driver for virtualization - and the reason it gained traction quickly - was the ability to run multiple workloads on the same server, while isolated from each other, so organizations could safely utilize excess capacity on underutilized servers. IT was now able to run the same workloads on fewer servers - that means fewer servers to buy, fewer servers to power and fewer servers to maintain and very easy to justify purchasing. Over time, the hypervisor evolved and became more sophisticated, adding capabilities such as workload mobility features across clusters of servers and becoming robust enough for mission-critical workloads. This allowed for the optimization of resources across workloads and the beginning of software-controlled infrastructure.

As the cost effectiveness made virtualization ubiquitous, increasingly organizations got used to these time, flexibility and efficiency savings. The curse of cost optimization is that it doesn't take long to go from innovative disruptor to table stakes. As a result, the virtualization cost savings were increasingly taken for granted and the operational benefits drove the spread of virtualization. Organizations saw the benefits of business agility under software control through rapid provisioning and automation, high availability, resource aggregation and management, scale-out clustering, disaster recovery as a service and live migration, eliminating the need for planned downtime. And with that, virtualization became indispensable in the data center.

Agility and the removal of friction from once-laborious tasks is a powerful proposition. Virtualization's ability to dramatically enhance business agility, along with software control and management, became the fundamental driver of virtualization adoption. As with any new technology, however, this increase in adoption created challenges, including VM sprawl. Servicing and provisioning new virtual servers became incredibly simple - so simple that enterprises often lost track of them. This can lead to enormous waste, with resources consumed when they are not needed.

Virtualization continued to expand into what is now known as the Software-Defined Data Center (SDDC). The idea here was to take all data center infrastructure resources including network, storage, and security, and virtualize and aggregate them so they can be dynamically apportioned out to workloads. This is all accomplished under software control without any manual intervention or hardware modification. Hyper-converged infrastructure is one variant of the SDDC, where customers purchase a self-contained "building block" appliance that contains server, storage and network components in an integrated bundle. Virtual machines presented as programmable, software-controlled infrastructure is what ultimately enabled the cloud revolution. With public cloud, you purchase virtual machines for a specified interval and you no longer need to own, manage or maintain any of the hardware resources to run them on.

Cloud Computing: A Similar Path
Now that we have a sense of how virtualization evolved and took off, what does that have to do with the cloud revolution? The cloud, just like virtualization before it, first gained popularity because of the most basic business driver there is: cost savings. Why treat hardware like a fixed capex cost that you have to amortize over lengthy periods of time when you can treat it as an on-demand operational cost? The ability to only pay for what you use allows for enormous cost and resource savings. But, much like virtualization, even huge cost savings eventually get taken for granted because they evolve into expected table stakes - the baseline for moving forward.

Public cloud cost savings are now a given with a level playing field between providers. That leaves us with the operational and agility benefits of cloud computing as being the real driver of adoption. The cloud presents all the agility of the SDDC, but additionally allows organizations to offload all hardware purchase, configuration and maintenance to the cloud providers. Under some circumstances, software maintenance for operating systems, services and applications can be offloaded as well. This is one of the benefits of higher levels of abstraction such as Platform as a Service (PaaS) and Software as a Service (SaaS). When utilizing PaaS services, developers and IT are no longer responsible for the middleware services such as databases that they use in their applications. With SaaS, none of the implementation technologies and their operational maintenance are the responsibility of the end user.

With cloud-based services, the value is in the fact that IT is no longer running the application or service. They're not hosting it, managing it or updating it either. It's a simple transaction - paying for a service and using it to help run their business. That's the value proposition that's led to widespread SaaS adoption, which is on the verge of becoming the dominant model for businesses services and applications that don't provide a competitive differentiation.

As we look at the differences between the Software-Defined Data Center and public or hybrid clouds, elasticity - the ability to grow and shift workloads to rapidly supply resources on demand to cost-effectively handle peaks and lulls - emerges as a big one. While the SDDC can enable elasticity, it falls short when it comes to usage-based pricing. With an SDDC, organizations still must own enough hardware to handle simultaneous peak workload demands. When leveraging a public or hybrid cloud, organizations have the ability to handle burst capacity when they need it - and only when they need it. It eliminates the need to pay for resources not being used as a "just in case" expense.

The similarities between the paths of virtualization and cloud computing adoption are not all positive. We see a lot of the same problems being repeated - in particular the issue of sprawl. As we discussed earlier, VM sprawl became an issue because new machines became so easy to provision that it was easy to lose track. The same issues impact cloud services, with the big difference being that lost, misplaced or unused cloud services will cost organizations real money, not just waste previously purchased hardware. Both cloud-specific and comprehensive cross-cloud management solutions that prevent VM sprawl, provide resource visibility and rightsizing, and cost optimizations are increasingly in demand by today's cloud consumers.

Like virtualization a decade or so before it, cloud adoption began as a tool for cost savings - certainly a powerful lead-in that can grab attention and market share. But as cost savings become an inherent part of baseline budgets and projections, it's the ability to enable business agility that fueled virtualization to its ubiquitous adoption. As cloud adoption continues to grow, so will its evolution from cost-saving tactic to business enablement strategy.