FinOps is the discipline enterprises need to optimize cloud spending

Signing up for cloud services is easy. But getting control of cloud spending can be a persistent challenge for an enterprise focused on making the most of its technology investment.

Gartner predicted worldwide end-user spending on public cloud services would grow 20.7% in 2023, to $591.8 billion. A survey for Foundry’s Cloud Computing Study 2023 found that lowering total cost of ownership ranks in the top three drivers of cloud computing initiatives, but controlling cloud costs was the top challenge that slows or stalls cloud adoption.

“The cloud makes it easy to build and grow solutions, but costs can quickly spiral out of control,” says Jay Upchurch, Executive Vice President and CIO with leading AI and analytics software company, SAS. Upchurch is an accomplished IT executive with more than 24 years of experience leading global managed hosting, managed application, cloud, and SaaS organizations.

Dealing with unanticipated costs

Concerns that cloud and distributed computing costs will exceed expectations leave organizations with two primary paths to keep control of expenses  :

  • Reduce the computing power needed to minimize costs while still achieving the desired business outcome
  • Turn off cloud resources faster to save on costs

“If you’re focused on moving fast and onboarding customers, it’s easy to miss the mark on cost efficiency,” says Upchurch. “Going back after the fact to optimize for cost while you’re still trying to operate and grow can make things even harder.”

Achieving cost-efficiency and maximizing productivity requires an ability to account for the time that cloud resources are used and the number of workloads you can execute when cloud resources are up and running. Another key factor is the efficient use of available CPUs.

Those factors are at the heart of the evolving culture and practice of FinOps. According to the FinOps Foundation’s Technical Advisory Council, FinOps combines lessons of finance and DevOps to bring accountability to cloud spending “by helping engineering, finance, technology, and business teams to collaborate on data-driven spending decisions.”  

Using that financial information, organizations can make near real-time decisions to optimize costs. By quickly showing engineers the financial implications of feature development and product changes, for example, they can optimize features for cost in the same way they tune for performance or uptime.

Align cost and performance insights

“To take action on cloud financial information, it’s important to attribute costs back to the teams that generate the spend,” says Upchurch. “Those teams are in the best seat to take advantage of the cloud’s elasticity.”

All cloud vendors provide some capabilities for daily or even hourly reports on cloud costs to provide recommendations for lowering costs. But more organizations are using multiple cloud environments, which can make it difficult to track and align cost and performance insights across an enterprise. With more efficient analytics, organizations can achieve better results in less time, gaining better value from their cloud investments.

The SAS® Viya® AI and analytics platform, unveiled in 2016 for private and public clouds, builds on more than 40 years of SAS’ analytics innovation to better manage data, develop models, and deploy insights, including optimizing cloud costs. For more insights into how to make cloud economics work for your organization, click here.

Can you run analytics in the cloud? Sure. Will it deliver the same level of performance? For many, that’s the real question…” Pat Richards Director, AI & Analytics, Intel Download this whitepaper to learn about the top 5 questions IT leaders are really asking about cloud analytics, SAS® and Microsoft Azure, and the straight answers they deserve to hear.