Soaring costs and control concerns are driving companies to repatriate workloads and blend cloud and on-prem for better performance and predictability.
After a decade of “cloud-first” being the default strategy, many organizations question whether their workloads truly belong in the cloud. Cloud repatriation has risen as businesses wrestle with soaring cloud bills and performance needs. While companies are still investing in cloud architectures, they are more intentionally deciding where each workload should live for greater control and predictability.
What Is Cloud Repatriation?
Cloud repatriation is the act of moving applications, workloads and data off public cloud platforms and back into:
- Privately owned on-premise data centers
- Private clouds
- Hybrid configurations
The purpose of it is to regain cost predictability, reduce latency and meet security needs. Most repatriation is selective and often produces a hybrid architecture that matches each workload to the environment where it performs best.
Industry polling shows 67% of enterprises have already repatriated some workloads, and a large share plan to move additional workloads in the next two years. While public clouds remain useful for non-critical systems, cloud repatriation is becoming a mainstream infrastructure option for mission-critical ones.
Key Drivers Behind the Move to On-Premise
From cost and performance to compliance and control, the following drivers are shaping repatriation decisions.
1. The Growing Deficit in Technical Support
As organizations scale, hyperscalers’ standardized support model can feel impersonal and slow when incidents occur. Teams often report frustration navigating triage queues and limited access to those who understand their unique stacks. These delays and information gaps increase downtime and make recovery harder. That lack of responsive, human-centric support is a major reason some prefer to run systems locally.
The desire for more human interaction shows up within a broader market expectation. One industry report found that 82% of U.S. consumers still prefer more human interaction in customer service, even while more businesses automate their processes. This sentiment maps directly to technical support, with business leaders increasingly valuing named contracts and in-house expertise.
2. Unpredictable Costs and Bill Shock
Cloud bills can be deceptively variable, as metered charges, storage tiers and data-egress fees add up quickly and are hard to forecast. As a result, many organizations routinely overshoot cloud budgets. One industry index found that 62% of respondents exceeded their cloud storage budgets in 2024, with a growing share reporting major overruns.
Visibility and unit-cost attribution remain persistent problems, so teams often cannot tell which services or teams are driving the waste. Only some organizations fully understand where their cloud dollars go. As budget overruns become widespread, it shows how brittle cloud cost forecasts can be without tight FinOps practices.
3. Enhanced Security and Data Compliance
On-premises or private-cloud deployments are attractive to regulated industries because they offer strict data sovereignty and direct control over encryption keys and access policies. These controls reduce exposure to shared-responsibility gaps and third-party supply-chain risk. Misconfigurations and risky integrations remain common cloud breach vectors, which is why many security teams prefer the tighter governance of local infrastructure.
Security concerns usually drive selective repatriation rather than a full exit. This process commonly involves teams moving archives with strict residency rules or datasets that must withstand rigorous audits back on-site or into private clouds while leaving experimental workloads in public clouds.
4. Performance Latency and Lack of Control
Some workloads perform better when they are closer to users or to the data that drives them. For instance, large transactional databases demand predictable, low-latency networks, and public clouds can struggle to guarantee that scale. Owning the stacks lets teams reduce hop count and run specialized caching strategies that squeeze extra throughput out of a system.
That is why some organizations selectively move performance-critical systems back on-premises or into colocations. For example, GEICO publicly disclosed its repatriation effort in 2024 due to cost and performance concerns. Since then, it has rebuilt a private cloud and brought many workloads back under direct control.
A Framework for Your Infrastructure Decision
If your organization is considering cloud repatriation, the following steps can help you decide whether it is the right step forward.
Audit Your Workloads
Start listing every application, including its owner, peak and steady-state resource needs, data sensitivity, and business criticality. For each workload, ask simple questions — is performance predictable or spiky? Does the data have residency or compliance constraints? Group workloads into buckets so you can spot patterns and recommend candidate placements rather than guessing case-by-case.
Conduct a Total Cost of Ownership (TCO) Analysis
Model cloud operations versus a local approach over three to five years and include direct and indirect costs. Run a few scenarios and explicitly surface the big cost levers. The point is to reveal where on-premises delivers sustained savings or where cloud’s elasticity still wins.
Evaluate the User Experience Impact
Tie technical trade-offs back to business outcomes by creating short journey maps for key users. Journey maps create a visual narrative of the user’s experience, highlighting moments of delight and friction so teams can target fixes that drive business outcomes.
Walk through touchpoints where latency and downtime hurt outcomes and measure those that matter. The journey map can help you prioritize which workloads to pilot. Once you move one candidate, you can measure results against your TCO and user metrics and iterate.
Finding the Right Balance
Repatriation is a pragmatic way to right-size where work runs based on cost, performance and user impact. When implementing it, you can use a simple framework to understand if it is the right move to improve business outcomes.
