Enterprise cloud projects pour unnecessary amounts of cash down the drain. Here are a few causes and some tips to avoid waste. Credit: Thinkstock IT has a long history of problems with budgets and money. Budget overruns for IT projects are more the rule than the exception. Typically, there are a few core culprits. First, many in IT, including myself until about 20 years ago, don’t really understand budgeting or how to predict what things will cost. Most choose whatever resources they think they will need with the objective of achieving the best possible outcome. Second, most budget managers and other leaders have a tendency to expect overruns, as there are rarely repercussions for spending more than they planned. Extra expenses became more perplexing when enterprises began to leverage cloud computing but the overruns continued. I really thought most of the overspending would go away with the rise of cloud computing. After all, cloud costs are much easier to predict because of utility-based pricing. Also, the cost models are much cleaner. Companies don’t have to deal with data center cost allocations, physical equipment costs and deprecation, and enterprise software license costs that keep going up when the service and value of the software keep going down. However, enterprises waste one-third of today’s cloud computing investments, according to a new survey of more than 750 businesses. This latest Flexera survey on the state of cloud computing reveals that companies have a hard time deploying cloud projects that work at their most efficient. Instead, a big chunk of cloud investment goes to waste. When the survey asked how much of cloud expenditure is efficient, the estimate was 68%. If you do some quick math, this leaves 32% waste in cloud spending. Also, survey respondents reported that cloud projects come in at an average of 13% over budget. Although there are many reasons for cost overruns, this is egregious. Why is this much money being wasted? I have a few observations. First and most obvious, finops processes, skills, and tools are not following cloud deployments into enterprises. Organizations lack ongoing monitoring and management of cloud costs. If we cranked the air conditioning to 64 degrees in the summer, would we be surprised when our electric bill came in much higher? Without actively monitoring cloud usage and costs and taking steps to reduce them to more efficient levels, cost overruns are a forgone conclusion. Second, cloud projects often lack active cost governance processes, skills, and tools. This is different from finops activities but closely related. Cloud cost governance means that we enforce spending policies, which in turn forces cloud admins, developers, and even users to be more careful about how they leverage a cloud resource. Most of the time, cost overruns are linked to unused cloud computing servers or storage systems being allocated and left running. They are typically not things that would affect the business, just general cloud computing housekeeping. Finally, and perhaps least understood, is the fact that we don’t often build efficient and fully optimized cloud solutions. Instead, we build cloud deployments with an eye toward the accepted or hyped solution, such as containers or serverless, rather than choosing a minimum viable solution that will drive the most optimized solution for the business. We need solutions that can return the greatest value to the business for the least amount of money to build, deploy, and operate. Don’t misunderstand me. I’m not saying these technologies aren’t the right fit. I am saying that we rarely focus on which solution will be the most optimized; we pick the solution that better matches our emotions. Yes, most solutions can be made to work, but when we do this, we leave money on the table. We drive costs higher for the project, deployment, and ongoing operations. This is where much of the 32% inefficiency numbers come from. It’s time to get our finops and cloud governance solutions in order. If we go through an economic downturn, tomorrow you’ll wish you had all that money you wasted today. Related content analysis Generative AI won’t fix cloud migration You’ve probably heard how generative AI will solve all cloud migration problems. It’s not that simple. Generative AI could actually make it harder and more costly. By David Linthicum Jul 12, 2024 5 mins Generative AI Artificial Intelligence Cloud Computing analysis All the brilliance of AI on minimalist platforms Buy all the processing and storage you can or go with a minimum viable platform? AI developers and designers are dividing into two camps. 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