Containers are a good way to provide value to cloud computing migrations, but many in IT rely on them too much Credit: Thinkstock According to Grand View Research, and pretty much every other IT research firm: “The global application container market size was valued at USD 1.5 billion in 2018 and is expected to register a CAGR of 26.5% from 2019 to 2025.” You don’t have to read an analyst report to see the growth in containers. Almost all the projects I’m on these days have containerization as a core thread as enterprises move rapidly to cloud-based platforms. You can’t blame them: You get portability, scalability, and better support for multicloud, built into container-based enabling technology, such as Kubernetes. However, as I pointed out before, there are additional costs in moving to containers. Containers are not a fit for all application and data workloads. Finally, you’ll be hard pressed to find enough people to get container-enabled applications done and operating properly. There are just not that many good container developers and designers around. At issue is the tendency to “manage by magazine” when it comes to selecting technology. We skip over our own core business requirements, moving directly to a fashionable technology such as containers, serverless, or machine learning. Indeed, IT is myopic around outlying solutions that may exist out of the mainstream hype-driven thinking. Containerization is a good fit for a lot of workloads, but not all. In many instances the workloads are just not economically viable when considering the cost of modifying the applications to work as containers. They require major rewrites, and that adds a great deal of risk and cost. Containers have a great deal of momentum in IT these days—so much so that we’re making mistakes misapplying container-based technology. If you take an objective look, for as much as 30 percent of applications ported to containers (or even built net-new), the architecture and fit to purpose is not a match with containers. We need to look objectively at all the new opportunities we have in front of us to improve functions and value of applications. Core to this is understanding what is really needed, including purpose, security, governance, and operational requirements. Then take an objective look at which enabling technology minimizes cost, reduces risk, and maximizes ROI. 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