Don’t look now, but 25% of organizations surveyed in the United Kingdom have already moved half or more of their cloud-based workloads back to on-premises infrastructures. This is according to a recent study by Citrix, a Cloud Software Group business unit.The survey questioned 350 IT leaders on their current approaches to cloud computing. The survey also showed that 93% of respondents had been involved with a cloud repatriation project in the past three years. That is a lot of repatriation. Why?Cost, not cloudSecurity issues and high project expectations were reported as the top motivators (33%) for relocating some cloud-based workloads back to on-premises infrastructures such as enterprise data centers, colocation providers, and managed service providers (MSPs).Another significant driver was the failure to meet internal expectations, at 24%. “Unmet expectations” describes most technology trends I’ve been involved with, including client/server, enterprise application integration, service-oriented architecture. and now cloud. Those surveyed also cited unexpected costs, performance issues, compatibility problems, and service downtime. The most common motivator for repatriation I’ve been seeing is cost. In the survey, more than 43% of IT leaders found that moving applications and data from on-premises to the cloud was more expensive than expected. Although not a part of the survey, the cost of operating applications and storing data on the cloud has also been significantly more expensive than most enterprises expected. The cost-benefit analysis of cloud versus on-premises infrastructure varies greatly depending on the organization. None of this should be surprising. The cloud had no way of delivering on the hype of 2010 to 2015 that gushed about lower costs, better agility, and better innovation. Well, two out of three is not bad, right? The cost of the cloud is where things usually go off the rails. The cloud is still the most convenient platform for building and deploying new systems, such as generative AI, and it also has the latest and greatest of pretty much everything. However, when enterprises run workloads and data sets using traditional infrastructure patterns, such as business applications that process and store data the same way they did when on-premises, there is a negative cost impact to using a public cloud.In other words, those who attempted to use the cloud as a simple host for their workloads and took no steps to optimize those workloads for their new location had much larger bills than expected. Moreover, they didn’t gain any real advantage by leveraging a public cloud for those specific workloads. The cloud is a good fit for modern applications that leverage a group of services, such as serverless, containers, or clustering. However, that doesn’t describe most enterprise applications.Don’t feel sorry for the public cloud providersThe cloud providers may be losing workloads and data sets that never should have been on a public cloud in the first place, but they will still enjoy explosive growth. Thank the AI gods that shone down upon them the reality that they are the most convenient place to build and host generative AI applications and data.Any losses from repatriation will be quickly replaced by the vast amounts of infrastructure needed to build and run AI-based systems. This includes new applications as well as existing applications that will be AI-enabled. Enterprises are also expanding their use of the cloud because AI systems are processor and storage pigs and need state-of-the-art frameworks, genAI ecosystems, and large language models that cloud providers are happy to host. Cha-ching!As I’ve said a few times here, cloud conferences have become genAI conferences, which will continue for several years. The cloud providers understand where their bread is going to be buttered. This is all healthy if you ask me. I would be concerned if enterprises understood that the cloud was draining money from IT without a return and kept moving in that direction. Enterprises are course-correcting for some applications and data sets that never should have moved to the cloud in the first place. They didn’t bother to do the math before making the move. I did, and now they have an expensive “I told you so” coming.
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