One of the most compelling aspects of cloud computing has always been the potential for cost savings and increased efficiency. Seen through the lens of industrial de-verticalization, this clear value proposition was at the core of most organizations’ decision to migrate their software to the cloud.

The Value Proposition of De-Verticalization

The strategic logic for de-verticalization is illustrated by the trend which began in the 1990s of outsourcing facilities’ maintenance and janitorial services.

A company that specializes in–let’s say–underwriting insurance policies must dedicate its mindshare and resources to that function if it expects to compete at the top of its field. While it may have had talented janitors with the necessary equipment on staff, and while clean facilities are certainly important, facilities maintenance is a cost center that does not provide a strategic return on what matters most to an insurance company. Wouldn’t it make more sense for both insurance and janitorial experts to dedicate themselves separately to being the best at what they do and avail those services to a broader market?

This is even more true for a data center. The era of verticalized technology infrastructure seems largely behind us. Though it’s a source of nostalgia for us geeks who were at home among the whir of the server rack fans, it’s easy enough to see why shareholders might have viewed it differently. Infrastructure was a cost center within IT, while IT as a whole is increasingly seen as a cost center.

The idea of de-verticalization was first pitched as something that would save money and allow us to work more efficiently. The more efficient part was intuitive, but there was immediate skepticism that budgets would actually shed expenses as hoped. At the very least it would be a long haul.

The Road to Performance and Cost Optimization

We find ourselves now somewhere in the middle of that long haul. The efficiencies certainly have come to pass. Having the build script deploy a new service to a Kubernetes cluster on the cloud is certainly nicer than waiting weeks or months for a VM to be approved, provisioned, and set up. But while the cloud saves the company money in the aggregate, it doesn’t show up as cheaper at the unit level. So, it’s at that level where anything that can be shed from the budget will be a win to celebrate.

This is a good position to be in. Opportunities for optimization abound under a fortuitous new circumstance: the things that technologists care about, like performance and power, dovetail precisely with the things that finance cares about, like cost. With the cloud, they are two sides of the same coin at an almost microscopic level. This trend will only accelerate.

To the extent that providers of computational resources (whether public cloud, hypervisors, containers, or any self-hosted combination) have effectively monetized these resources on a granular level and made them available a la carte, performance optimization and cost optimization sit at different ends of a single dimension. Enhancing a system’s performance or efficiency will reduce resource consumption costs. However, cost reduction is limited by the degree to which trade-offs with performance are tolerable and clearly demarcated. Cloud resource optimization tools help organizations strike the ideal balance between the two.

Choosing the Right Cloud Resource Optimization Solution

With that premise in mind, selecting the right cloud resource optimization solution should start by considering how your organization wants to approach the problem. This decision is informed by overall company philosophy and culture, what specific problems or goals are driving the initiative, and an anticipation of where overlapping capabilities may fulfill future business needs.

If the intent is to solve existing performance issues or to ensure continued high availability at future scale while knowing (and having the data to illustrate) you are paying no more than is necessary, focus on solutions that lean heavily into performance-oriented optimization. This is especially the case for companies that are developing software technology as part of their core business.

If the intent is to rein in spiraling costs or even to score some budgeting wins without jeopardizing application performance, expand your consideration to solutions that offer a broader FinOps focus. Tools with a FinOps focus tend to emphasize informing engineers of cost impacts, and may even make some performance tuning suggestions, but they are overall less prescriptive from an implementation standpoint. Certain organizations may find this approach most effective even if they are approaching the problem from a performance point of view.

Now that many organizations have successfully migrated large portions of their application portfolio to the cloud, the remaining work is largely a matter of cleaning up and keeping the topology tidy. Why not trust that job to a tool that is purpose-made for optimizing cloud resources?

Next Steps

To learn more, take a look at GigaOm’s cloud resource optimization Key Criteria and Radar reports. These reports provide a comprehensive overview of the market, outline the criteria you’ll want to consider in a purchase decision, and evaluate how a number of vendors perform against those decision criteria.

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