Cloud Repatriation Is Harder Than You Think

Guest Editorial by Ofer Regev, CTO and Head of Network Operations, Faddom

Transferring workloads from public cloud environments back to on-premises infrastructure is becoming more common. According to IDC, 80% of organizations expect to move some compute or storage resources in-house by the end of 2025. Forrester notes that these efforts are now focusing on workloads that are deeply integrated with internal systems, rather than just simple lift-and-shift scenarios.

Ofer Regev

While the reasons for repatriation - such as cost management, compliance, and performance - are clear, the process itself presents a different set of challenges. Reverse migrations often fail not because the cloud was a poor fit, but because organizations underestimate the technical and operational risks associated with untangling workloads adapted to the cloud.

To avoid merely swapping one set of problems for another, IT leaders must rethink how they plan and execute repatriation efforts. Here are five critical considerations that can determine the success or failure of these projects.

5 Critical Considerations to Prevent Repatriation Failure

Before moving any workloads back from the cloud, IT teams should consider more than just potential cost savings. They need to evaluate whether their infrastructure, processes, and visibility are prepared for the transition. Five critical factors are often overlooked, yet they can significantly hinder even the most well-planned repatriation projects.

Repatriation is not simply a reverse lift-and-shift process. Workloads that have developed in the cloud often have specific architectural dependencies that are not present in on-premises environments. These dependencies can include managed services like identity providers, autoscaling groups, proprietary storage solutions, and serverless components. As a result, moving a workload back on-premises typically requires substantial refactoring and a thorough risk assessment. Untangling these complex layers is more than just a migration; it represents a structural transformation. If the service expectations are not met, repatriated applications may experience poor performance or even fail completely.

Change validation requires real context. Repatriation is not just a technical move. It is a change management event. However, many teams begin this process without a clear understanding of what the environment looked like prior to the transition. When issues occur after the move, the lack of a before-and-after comparison turns root cause analysis into a guessing game. Historical snapshots of system states are crucial for confirming that changes were implemented as intended and that no critical dependencies were lost in the process. Without this context, teams end up spending valuable time troubleshooting issues that could have been quickly verified.

You cannot migrate what you cannot see. Accurate workload planning relies on complete visibility, which includes not only documented assets but also shadow infrastructure, dynamic service relationships, and internal east-west traffic flows. Static tools such as CMDBs or Visio diagrams often fall out of date quickly and fail to capture real-time behavior. These gaps create blind spots during the repatriation process. Application dependency mapping addresses this issue by illustrating how systems truly interact at both the network and application layers. Without this mapping, teams risk disrupting critical connections that may not be evident on paper.

Dependency gaps lead to post-migration outages. In many environments, small, overlooked components can cause significant disruptions. A forgotten cron job, a misconfigured logging service, or a disconnected queue may seem unimportant until the application that relies on them starts to fail silently. These operational links are challenging to track without continuous mapping, and they are often missed during hurried migrations. Repatriating a workload without considering all its interdependencies can degrade performance, increase the number of incidents, and undermine user confidence.

AI and governance make workloads harder to unwind. When organizations decide to repatriate AI workloads and compliance-sensitive applications to gain better cost control or to meet privacy requirements, they face significant challenges. These AI pipelines often depend on scalable storage, GPU-based compute instances, or managed orchestration platforms that are closely integrated with cloud environments. Additionally, transferring workloads that involve protected data necessitates further compliance checks when moving to a new environment. Redesigning these systems for on-premises infrastructure requires re-evaluating all aspects, from access control to storage formats.

Hybrid Is the Real Destination

Repatriation does not mean abandoning the cloud. Instead, it reflects a broader shift towards a hybrid infrastructure. This model strategically distributes workloads across cloud and on-premises environments based on performance, cost, and governance criteria. However, achieving the right balance requires operational discipline that many organizations currently lack. Visibility, validation, and documentation are essential prerequisites, not mere afterthoughts.

Organizations that view repatriation as a simple rollback are more likely to face challenges. In contrast, those that utilize real-time dependency data, maintain architectural clarity, and adopt forward-looking governance models are much better positioned for success.

Conclusion: Visibility First, Then Movement

Every decision leaves a footprint. Repatriation is a complex transformation that demands more than a technical migration tool.

What appears to be a move back to familiar ground is, in practice, a high-stakes rebuild. These are complex systems, and workloads that have matured in the cloud often rely on architectures, services, and integrations that cannot be replicated on-premises without significant effort. The risks involved are not simply technical; they are operational, architectural, and strategic.

Success depends on having real-time visibility into dependencies, context-aware change validation, an honest inventory of what workloads really need to function, and a disciplined approach to execution. Without these foundations, efforts to regain control may only introduce new layers of complexity.

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Ofer Regev has 18 years’ experience in the IT industry. He currently serves as CTO and head of network operations for Faddom (formerly VNT), a startup that raised $12 million to help companies map IT infrastructure wherever it lives. Faddom is used to map and monitor over 1 million application instances at organizations like Coca Cola, NetApp, and UCLA. He previously served in the IDF's elite computing and information services unit, Mamram.