The pandemic has spiked cloud spending, and enterprises are unhappy with their bills. Best practices are emerging to get costs under control. Employees working remotely for much of 2020 caused a huge uptick in cloud spending at the same time enterprises struggled to contain cloud expenses. In many cases, increases were directly due to the pandemic and changes in IT systems to accommodate the new normal. In other cases, companies lacked the automated oversight necessary to contain cloud spending. FinOps Foundation, a nonprofit trade association, recently released detailed findings from a survey of more than 800 FinOps practitioners with a total annual cloud spend of more than $30 billion. About half of the respondents (49%) had no automation in place to manage cloud costs. Of those who had some automation, almost one-third had automated notifications (31%) and tagging hygiene (29%). Only 13% had automated rightsizing and 9% had automated spot use. These are typical patterns, tools, and solutions to manage cloud spending. For those of us in the cloud game, this is old news. We’ve already heard grumblings about cloud managers who faint at the sight of their bills—not because the bills were incorrect, but because they were unexpected and out of budget. They complain that there is no way to anticipate the size of the cloud spend, manage cloud operations to reduce costs ongoing, or plan in advance to optimize long-term cloud expenses. While we can certainly blame the pandemic, there is no excuse for enterprises that do not employ cloud cost-governance methodologies. Governance tools can place limits on cloud spending, and other tools can monitor and manage ongoing expenses. I suspect that half of the 2020 cloud spending was avoidable. The lack of resource planning resulted in many storage and computing instances that were spun up beyond what was needed and, in some cases, never spun back down after use. The best practices are easy to understand. First, put a cloud cost-governance system in place to automate spending management, including tools that set and enforce policies, monitor usage, do chargebacks and showbacks, as well as help with advance planning to adhere to budget restrictions. These systems often pay for themselves in a month, usually less. Second, provide cloud cost-management training. Surprisingly, there’s not much pursuit of cloud cost management as a skill. Most people in the cloud game opt for better-known architecture and/or development roles. Until now, we’ve either avoided creating cloud governance roles, or the tasks involved landed in the wrong hands because we didn’t understand where these roles should reside. I often find them in cloud migration teams, of all places. That might be good for a migration project, but in reality, the role is more about centralized operations and control. Somebody needs to set up these governance systems and maintain them ongoing. Although the cloudops team is often charged with the oversight of all governance operations, I would argue that this special-purpose task needs to be in the hands of a person who understands the business as well as the cloud tech. Where does cloud cost governance reside in your organization? Where should it reside? Related content analysis Strategies to navigate the pitfalls of cloud costs Cloud providers waste a lot of their customers’ cloud dollars, but enterprises can take action. By David Linthicum Nov 15, 2024 6 mins Cloud Architecture Cloud Management Cloud Computing analysis Understanding Hyperlight, Microsoft’s minimal VM manager Microsoft is making its Rust-based, functions-focused VM tool available on Azure at last, ready to help event-driven applications at scale. By Simon Bisson Nov 14, 2024 8 mins Microsoft Azure Rust Serverless Computing how-to Docker tutorial: Get started with Docker volumes Learn the ins, outs, and limits of Docker's native technology for integrating containers with local file systems. By Serdar Yegulalp Nov 13, 2024 8 mins Devops Cloud Computing Software Development news Red Hat OpenShift AI unveils model registry, data drift detection Cloud-based AI and machine learning platform also adds support for Nvidia NIM, AMD GPUs, the vLLM runtime for KServe, KServe Modelcars, and LoRA fine-tuning. By Paul Krill Nov 12, 2024 3 mins Generative AI PaaS Artificial Intelligence Resources Videos