Containers are being sold as a cure-all for cloud computing systems, but they have a specific purpose, and in many instances should not be used. Credit: Philippe Put Containers seem to be the default approach for most systems migrating to the cloud or being built there, and for good reasons. They provide portability and scalability (using orchestration) that is more difficult to achieve with other enabling technology. Moreover, there is a healthy ecosystem around containers, and a solution is easier to define. However, much like other hyped technologies these days, such as AI, serverless, etc., we’re seeing many instances where containers are misapplied. Companies are choosing containers when other enabling technologies would be better, more cost-efficient solutions. Indeed, I think we’re leaving millions of dollars on the table by choosing a technology that’s not the right fit. We’re going after points for hype and another trending technology on the CV. The core downside of containers today is the overapplication of container development and the migration of existing applications to containers in “application modernization” projects. It’s not that containers don’t work—of course they do. But many things “work” that are hugely inefficient compared to other technologies. Most companies are chasing the benefit of portability for a workload that is unlikely to ever move from its target host platform. Also, and most importantly, they do not understand that to truly take advantage of what containers offer requires a complete re-architecture of the application in most instances, which they typically didn’t do. Net-new development has this problem as well. Enterprises are spending as much as four times the money to build the same application using container-based development and deployment versus more traditional methods. Also at issue, the container-based application could cost more to operate by using more cloud-based resources, such as storage and compute. It also costs more to secure and more to govern. When evaluating containers, here are a few core points to consider: Focus on returning value back to the business. It’s the old story of developers and engineers who don’t look out for the business as much as they should. Don’t follow the hype. Don’t overstate benefits, such as portability, that may never be used. If it costs twice or even four times the money to get there, what are the chances you’ll ever move an application? Understand operational costs. Containers may cost more to operate in the long term. I’m not saying don’t ever use containers, but understand the true cost of maintaining them over the years. Use architectural best practices. Applications often need to be redesigned for containers to be effective. “Wrapping” something doesn’t give you efficiency by default. This is a cautionary tale to point out the need for a healthy skepticism about any technology. I’m using containers as an example, but it could really be any technology. Keep an eye on the value returned to the business, and you’ll likely make the right calls. Related content opinion Stopping the rot in AI spending Emerging AI governance tools offer a step toward visibility and control of what’s happening in a company’s AI applications. By Matt Asay Oct 21, 2024 5 mins Generative AI Risk Management Artificial Intelligence opinion Making generative AI work for you Find the sweet spot where genAI boosts your productivity but doesn’t get you in over your head where you can’t tell good output from bad. By Matt Asay Oct 14, 2024 5 mins Generative AI Development Tools Emerging Technology opinion California’s vetoed AI bill: Bullet dodged, but not for long SB 1047 missed the mark. A far better solution to managing AI risks would be a unified federal regulatory approach that is adaptable, practical, and focused on real-world threats. By Kjell Carlsson Oct 08, 2024 8 mins Technology Industry Generative AI Artificial Intelligence opinion Crescendo makes AI boring—and profitable An AI startup is turning call centers into a successful model of using AI to support human employees. By Matt Asay Sep 30, 2024 6 mins Technology Industry Generative AI Artificial Intelligence Resources Videos