Despite conflicting analyst opinions, we could be in a slowdown for application and data migration to public clouds. Here are 3 reasons I see. Credit: Thinkstock I don’t have data to back this up, so this is an educated assertion at best. I see three reasons why migration to the cloud may be going through a transitory slowdown. I’ve also seen some recent data points that seem to bear this out, and it makes logical sense based on where we are in market maturation. First, we can’t keep up the mad dash to the cloud that was driven by the pandemic. Those who thought that cloud adoption would slow down during the restrictions placed on businesses found the opposite. Indeed, public clouds are largely pandemic-proof when compared to physical data centers that could not be accessed during the lockdowns and quarantines. That, in conjunction with the explosion of remote work programs, had many governments and Global 2000 companies rush to the cloud. [ Also on InfoWorld: The best software development, cloud computing, data analytics, and machine learning products of 2022 ] We can’t keep up that pace forever, and thus we’re seeing a pullback in migration projects to get back to pre-pandemic paces. This is a good thing considering that planning and common-sense best practices were typically jettisoned as a trade-off for speed. For example, many companies will have to redo many of the applications that they just lifted and shifted quickly. The applications were not optimized for the new public cloud platform, are costing way more than they should, and are less reliable. Second, there are no cloud skills to be found. The skills shortage is like nothing I’ve seen in my career. It’s limiting most companies and governments as they consider how much migration they want to do versus how many skilled people they can find. Study after study points to the fact that the speed in moving to the cloud is largely determined by the number of talented humans organizations can find. Demand is still outpacing supply, and I suspect that this will slow down migration if it hasn’t already. Finally, we’ve already moved the easy workloads. We’ve gone through our “low-hanging fruit.” I’m seeing this more and more day to day: We are running out of the applications that leverage enabling technology that is easy to find analogs of in the public clouds, such as LAMP-based applications and data sets. This leaves older applications, such as those running on legacy systems. These older workloads represent another level of difficulty and often need major redesigns and recoding just to move to the cloud. You may have guessed that these are also less cost-effective in terms of the value that they may bring when moving them to the cloud. In many instances, less workload efficiency comes at a higher cost, and that removes any value gains. In many instances, the workloads are being moved because leadership sees those legacy platforms going away at some point. They are certainly not getting R&D dollars in these platforms these days, compared to cloud-focused technology. I don’t view a temporary slowdown as a bad thing, necessarily. I think that the rapid migration to the cloud over the past several years, combined with the lack of skills, has caused many organizations to make major errors that will eventually have to be fixed. Thus, you’re really moving to the cloud twice. First: lifting and shifting and moving on. Second: fixing all the blunders you made when you just lifted and shifted. Also, we’re going to have to get to those older applications at some point. Now that cloud computing platforms and application development and migration tools have matured a great deal after 14 years, there is no time like now to attempt to deal with those workloads. Sometimes you must go slower to go faster. Related content analysis Azure AI Foundry tools for changes in AI applications Microsoft’s launch of Azure AI Foundry at Ignite 2024 signals a welcome shift from chatbots to agents and to using AI for business process automation. By Simon Bisson Nov 20, 2024 7 mins Microsoft Azure Generative AI Development Tools analysis Succeeding with observability in the cloud Cloud observability practices are complex—just like the cloud deployments they seek to understand. The insights observability offers make it a challenge worth tackling. By David Linthicum Nov 19, 2024 5 mins Cloud Management Cloud Computing news Akka distributed computing platform adds Java SDK Akka enables development of applications that are primarily event-driven, deployable on Akka’s serverless platform or on AWS, Azure, or GCP cloud instances. By Paul Krill Nov 18, 2024 2 mins Java Scala Serverless Computing analysis Strategies to navigate the pitfalls of cloud costs Cloud providers waste a lot of their customers’ cloud dollars, but enterprises can take action. By David Linthicum Nov 15, 2024 6 mins Cloud Architecture Cloud Management Cloud Computing Resources Videos