Cloud maturity models grade how an enterprise is progressing to the cloud, but these rankings don't show the whole picture Credit: Thinkstock I use them all the time: models or frameworks that allow you to compare your cloud maturity ranking with a set of criteria, letting you know where you sit in your progress toward the cloud. Scores typically range from a low level of “nonexistent use of cloud,” to the highest ranks of “cloud optimized,” or something to that effect. Of course, most enterprises are somewhere in between: an “early adopter” to “cloud preferred.” These maturity rankings typically come with sets of criteria which allow you to self-evaluate your use of cloud technology. Questions range from: “Do you use serverless or container technology?” to queries around the use of cloud-based security and governance. In the past I’ve found these maturity models to be good tools, in that I could show leaders how their company ranked in terms of cloud computing maturity. This educates the leaders and shows them how they compare with their peers. At times the models would become selling tools. The idea was to conduct a scientific analysis of an enterprise’s current state and where it should be headed. However, it really invoked an emotional response, and perhaps pushed enterprises in the wrong directions at times. The issue that I have now with the many cloud computing maturity models out there—and there are many—is that people often rely on them too much. They can dilute the larger picture of the right way to do cloud adoption and how an organization should set the appropriate priorities. For instance, it never should be about using a specific cloud-based technology, such as serverless, containers, Kubernetes, or machine learning. It’s about leveraging the cloud for the right purposes that are consistent with serving the business. These maturity models do offer a beneficial measure of culture and internal processes, which are actually more important than adopting trendy cloud technology. Indeed, unless technology is employed specifically to serve the needs of the business, technology (including cloud technology) can take you back a few steps. You’re ultimately not aligning business requirements with the correct and pragmatic use of cloud and noncloud technology. Don’t get me wrong, there are some helpful and some not so helpful maturity models out there. As I practice enterprise cloud migrations, including assessment and planning, I use some of these models as foundational benchmarks at times. However, these will never be my only metric, or else we’re likely to move in the wrong directions. Just saying. 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