Making your cloud deployment cost-efficient kills two birds with one stone: It saves money and helps your sustainability goals. Credit: Thinkstock Sustainability and cloud computing go hand in hand. Cloud computing’s ability to share resources naturally leads to more efficient use of those resources. This sharing model gives cloud computing its ability to provide sustainability in the wide, but we must optimize the use of those assets to provide sustainability in the narrow. The goal is to optimize cloud computing costs using finops and the tools that drive these processes. At the same time, these tools also help maximize the sustainability of our cloud deployments. Indeed, moving to public cloud platforms is a half measure toward increasing sustainability. You’ll find the best carbon benefits by optimizing cloud resources, which simultaneously means optimizing for cost efficiency. They are tightly coupled, for the most part. An example would be moving an application and an attached database to a public cloud from a traditional data center. If you do not refactor the application, it will not leverage cloud-native services. The result is an unoptimized lift-and-shift migration (most of today’s application migrations to the cloud). A partial sustainability benefit is immediate. An application running in a public cloud can share resources via multitenancy, requiring fewer resources (such as storage and compute) to carry out the same functions. Thus, the application requires less power. However, since our example workload was not optimized for the cloud platform host, it’s largely cost-inefficient. The odds are good it’s spinning up more resources than it should and not taking advantage of cloud-native features that will allow it to operate less expensively. Many enterprises are experiencing high costs for cloud computing, as I’ve previously described. These are self-inflicted wounds, a byproduct of not taking the time to refactor and optimize the workloads for the public clouds they will run on. As a result, many enterprises loop back to those applications to rewrite, refactor, or containerize them so they won’t generate such an enormous cloud bill each month. My point is that optimization has benefits beyond saving money. If you want to ensure that you’re optimized for sustainability—which management and investors are certainly interested in—start a finops program. Cost-optimized workloads do the most with the least resources, which improves your carbon output at the same time. I’m not the first person to make this link. Most technology providers that build and sell finops tools have already added sustainability metrics into their tech—or will soon. We can rarely solve two problems with the same effort and investments, but that is the case with cloud sustainability and optimization. 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. By David Linthicum Jul 09, 2024 5 mins Generative AI Cloud Architecture Artificial Intelligence analysis The next 10 years for cloud computing Despite AI's explosive growth, the industry still needs to face facts that customers are unhappy about costs and vendor lock-in. By David Linthicum Jul 05, 2024 5 mins Amazon Web Services Google Cloud Platform Microsoft Azure analysis Serverless cloud technology fades away Serverless was a big deal for a hot minute, but now it seems old-fashioned, even though its basic elements, agility and scalability, are still relevant. By David Linthicum Jul 02, 2024 4 mins Serverless Computing Cloud Computing Software Development Resources Videos