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Cloud Repatriation: When Moving Workloads Back From the Public Cloud Makes Sense

Table of contents

Key takeaways

  • Steady workloads tend to cost less on owned infrastructure. Workloads with sudden peaks usually cost less in the public cloud.
  • Rightsizing and commitment discounts can shrink the gap between public cloud and owned infrastructure costs so much that moving no longer pays off.
  • Cloud providers waive exit fees for customers who leave, and the EU Data Act bans switching charges from January 2027.
  • After repatriation, the public cloud can stay in use as a disaster recovery site.

Cloud repatriation means moving applications, data, or virtual machines from a public cloud back to infrastructure a company controls. That can be a private cloud, an on-premises data center, or a colocation facility. Most projects cover selected workloads; full repatriation is rare.

What is cloud repatriation?

For years, “cloud first” was the default strategy, and many teams moved as much as they could. Most companies now run a mix of environments: according to Flexera’s 2026 State of the Cloud Report, 73% of organizations use a hybrid cloud. In a hybrid setup, cloud repatriation is part of workload placement. The terms below often get mixed up, so here is how they differ.
Term What it means Typical scope
Cloud repatriation Moving workloads or data from public cloud to private, on-premises, or colocation infrastructure One app, a data tier, or a group of VMs
Reverse cloud migration Another name for repatriation that puts the stress on the direction of the move Same as repatriation
Cloud exit Leaving a public cloud provider completely, for on-premises or another cloud All workloads and data
Workload placement The ongoing practice of deciding where each workload should run The whole portfolio

Cloud repatriation trends: why companies move workloads back

In October 2024, IDC called repatriation a growing trend, though only 8–9% of companies planned to repatriate workloads fully. Organizations typically bring back specific workload elements, such as production data, backup and disaster recovery processes, and compute resources. The most common reasons fall into four groups.

Cost of steady workloads

Pay-as-you-go pricing suits variable demand well. A workload that runs at the same level around the clock is another matter, and over a few years it can cost more in the cloud than on owned hardware. On-demand pricing lets you scale up and down at any time, and a workload that never scales still pays for that option without using it.

Egress fees

Data that leaves a public cloud is billed per gigabyte, and for data-heavy applications egress can grow into a large share of the bill. In a private data center or colocation facility, internet bandwidth is usually priced by capacity rather than per gigabyte, so heavy outbound traffic does not raise the bill in the same way. The cost of leaving has also come down. In early 2024, Google Cloud, AWS, and Microsoft Azure began waiving egress fees for customers who move their data out. The conditions differ: Google Cloud and Azure require a full exit with the account or all subscriptions closed, while AWS also covers moving all data off a single service. EU customers also get a legal guarantee: the Data Act bans switching charges, egress included, from 12 January 2027. The waivers and the Data Act both cover switching only. If some workloads stay in the cloud, you still pay for traffic between environments.

AI and GPU workloads

Production inference can keep expensive GPUs busy day and night, and at that level of use owning them can cost less than renting. In a Cloudera-commissioned survey conducted in June 2026, 84% of 1,500 IT architects and infrastructure leads said AI workloads have raised their infrastructure costs. Two-thirds reported moving AI workloads from public cloud back to private cloud or on-premises during the past year. For latency-sensitive AI applications, shared public cloud infrastructure can also become a performance bottleneck.

Security and data sovereignty

Concerns about data breaches and compliance also push some workloads back. Companies in regulated industries, such as finance and healthcare, need to know where their data lives and who can reach it. For some, that means moving sensitive systems to a private cloud. Others move to a sovereign cloud such as STACKIT, which keeps data in EU data centers.

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Full vs partial repatriation: which workloads are good candidates?

Full repatriation suits companies with stable demand, a large cloud bill that barely changes from month to month, and their own operations team. Most others choose partial repatriation, moving the workloads where owned infrastructure clearly wins and leaving the rest in the cloud.

Good candidates for repatriation Better kept in the public cloud
Production workloads with a flat 24/7 load: they pay on-demand prices for capacity they always use Seasonal workloads: owned hardware would sit idle between peaks
Large databases and storage tiers with high egress: every transfer out adds to the bill Short-lived dev environments and proofs of concept: they end before purchased servers pay off
Production AI inference with constant GPU use: the GPUs are busy all the time Experiments that need the newest GPUs for a few weeks: buying that hardware for a short test is rarely worth it
Systems with strict data residency or audit rules: owned infrastructure makes data location easy to prove Apps built on managed, provider-specific services: each service would have to be replaced or rebuilt
Legacy VMs lifted and shifted unchanged: they use no cloud-native services, so they move without rework Global services that need many regions: matching that footprint means running many data centers

Idle or oversized workloads are a separate case. Flexera’s 2026 report puts wasted cloud spend at 29%, its first rise in five years. That waste is a cost-management problem, and moving the workloads to owned hardware keeps it in place.

Cloud vs on-premises cost: how to compare TCO

Three-year TCO for 200 steady VMs: public cloud on-demand $1.91M, optimized $1.50M, private cloud $1.45M

Comparing cloud vs on-premises costs is harder than it looks. In Flexera’s 2026 survey, 43% of respondents cited it as a cloud migration challenge, ranking it third. A fair comparison uses the same time horizon on both sides (typically three to five years) and the same service level.

 

This formula applies to both public and private cloud:

 

TCO = upfront costs + monthly running costs × number of months

 

In the public cloud, almost everything is a running cost: compute, storage, egress, support, and managed services. A private cloud moves much of the spending upfront into hardware and the migration project. It also adds running costs for data center space, licenses, operations staff, and a backup or DR site.

Worked example

The figures below are illustrative. The example assumes 200 steady production VMs over three years.

Cost line Public cloud, 3 years Private cloud, 3 years
Compute and storage $1,620,000 ($45,000/month) $450,000 (hardware)
Egress $108,000 ($3,000/month) —
Data center, power, and network — $216,000 ($6,000/month)
Support, licenses, and managed services $180,000 ($5,000/month) $180,000 ($5,000/month)
One-time migration project — $80,000
DR and backup site (kept in the public cloud) — $72,000 ($2,000/month)
Total $1,908,000 $1,448,000

In this scenario, the private cloud saves $460,000 over three years, or about 24%. With $530,000 spent upfront on hardware and migration, payback comes after roughly 19 months. The public cloud figures assume the compute and storage line includes backup and multi-zone redundancy.

Optimizing the cloud side changes the picture. If commitment discounts and rightsizing cut the cloud compute and storage line by a quarter, the gap drops to about $55,000, too thin to justify a move on cost alone.

Cloud exit strategy step by step

Six-step cloud exit plan: assess, choose the target, replicate, test, cut over, protect

Even a partial move needs a plan that works like a cloud exit strategy. It follows the logic of any migration project, only in reverse.

  1. Assess. List workloads, dependencies, data volumes, and current costs, then mark each one as move, keep, or rework.
  2. Choose the target. Pick a platform your team can run long term. Weigh existing skills, licensing costs, and whether VMs need to run next to containers, as they do on KubeVirt and Red Hat OpenShift Virtualization. Many teams choose a KVM-based platform such as OpenStack or OpenNebula. Size compute and storage with growth in mind.
  3. Replicate. Copy VMs and data in the background, then keep the copies in sync until cutover.
  4. Test. Run test migrations in an isolated network to check integrations and boot order without touching production.
  5. Cut over. Run a final incremental sync during a short, planned maintenance window, with a rollback plan ready.
  6. Protect. Have disaster recovery and backup in place for the new platform before you switch off the cloud resources.

Risks of reverse cloud migration and how to reduce them

Problems in a repatriation project often trace back to costs or dependencies missed during planning. The table lists the common ones and how to reduce them.

Risk How to reduce it
Hidden dependencies on managed cloud services Map dependencies early and plan replacements for proprietary databases, queues, and identity services
Underestimated hardware and staff costs Put refresh cycles, spare capacity, and operations salaries into the TCO model
Downtime during cutover Replicate continuously and rehearse with test migrations, so the final switch stays short
Lost resilience after leaving multi-region cloud Set up disaster recovery to a second site; a public cloud region works
Egress costs during the move Check provider waivers, and budget for traffic if some workloads stay in the cloud
Skills gap Train the team before cutover or bring in a managed service provider

Publicly reported examples: 37signals, Dropbox, and GEICO

Three companies have described their moves in their own words. Each moved a different share of its workloads.

37signals

The company behind Basecamp and HEY moved seven cloud apps from AWS onto its own hardware. According to CTO David Heinemeier Hansson, its cloud bill fell from a $3.2 million yearly run rate to $1.3 million in 2024, and the remaining $1.3 million was all for AWS S3 storage. In 2025, 37signals moved that data too: several petabytes went to Pure Storage systems in its two data centers, and AWS waived $250,000 in egress fees for the transfer. Hansson expects total savings of more than $10 million over five years. One reason the savings beat the original $7 million estimate: the new servers fit within the company’s existing rack and power limits.

Dropbox

The company’s S-1 filing describes how it moved most of its user content to its own custom-built infrastructure in colocation facilities during 2015 and 2016. In its 2018 annual report, Dropbox said it stored more than 90% of user data on its own infrastructure. At the time, AWS handled the rest, which makes this a case of partial repatriation.

GEICO

The US insurer’s infrastructure team describes its move in a white paper published by the Open Compute Project. By 2023, GEICO was spending more than $300 million a year on public cloud. More than 1,000 servers now run in two colocation facilities, with OpenStack handling provisioning, and the company aims to bring back at least half of its cloud workloads. According to the paper, unit costs have dropped by more than 50% per compute core and more than 60% per gigabyte of storage, compared with both its previous OEM hardware and equivalent public cloud services. All three ran large, stable workloads and had experienced engineering teams to run their own infrastructure.

How Hystax Platform supports cloud repatriation

The platform covers the technical side of repatriation: the move itself, then disaster recovery and backup afterward.

Hystax Migration moves VMs from AWS, Azure, Google Cloud, and Oracle Cloud to private, sovereign, and virtualization platforms. With public cloud sources, a replication agent runs inside each guest OS and copies data in the background while production keeps running. After the first copy, only changed blocks travel over the network.

  • Supported targets include OpenStack, Red Hat OpenStack Services on OpenShift, OpenNebula, Apache CloudStack, KubeVirt, Red Hat OpenShift Virtualization, Oracle Linux KVM, Oracle Linux Virtualization Manager, Virtuozzo, CloudSigma, STACKIT, VMware, and oVirt.
  • Direct2Target writes data straight to the target disks without relying on the platform’s management APIs, so any environment with disk-level write access can serve as a target.
  • Test migrations run in an isolated network, with no limit on how many. The final cutover takes 1 to 3 minutes on average.
  • Migration plans set boot order and network settings, so applications start in the right sequence.


Constructor Group, a global research, education, and technology ecosystem, used Hystax Migration to
move its workloads from Google Cloud to Virtuozzo. The company cited long-term cost and platform dependency as reasons for leaving, and it wanted a platform it could control and tune more fully. Its applications stayed online throughout the transition.

Hystax Disaster Recovery protects the workloads after the move. Leaving a hyperscaler doesn’t mean giving up the public cloud as a safety net: with cross-cloud disaster recovery, AWS, Azure, or Google Cloud can serve as the recovery site. Replicas are kept there as volumes and snapshots, and full VMs start only when they’re needed.

For longer retention, Hystax Backup writes restore points to S3-compatible object storage or to NFS and Samba shares. On S3-compatible storage configured with Object Lock, restore points stay immutable for the retention period.

You can deploy the software in your own environment, so replication data stays under your control. Managed service providers get a multi-tenant partner portal for running several customer projects at once. Supported migration scenarios are listed on the cloud migration page.

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Frequently asked questions

What is cloud repatriation in simple terms?

It means taking workloads or data out of a public cloud and running them on infrastructure your company controls. For example, a database with a steady load might move from AWS to an OpenStack private cloud.

Is reverse cloud migration the same as cloud repatriation?

The two terms describe the same move. A cloud exit is a different term: it means leaving a provider completely, and the workloads can go on-premises or to another cloud.

Does cloud repatriation always save money?

No. Savings show up for steady, predictable workloads at scale. Workloads with sudden peaks can cost more, and so can projects that underestimate hardware, staff, or migration costs. Build a three- to five-year TCO model first.

How long does a repatriation project take?

There is no typical figure: duration depends on the number of workloads, the data volume, and network bandwidth. Production stays online during replication, and the Hystax cutover itself averages 1 to 3 minutes.

Can I keep using the public cloud after repatriation?

Many companies do. A common hybrid setup keeps steady workloads in a private cloud and uses the public cloud for sudden peaks, experiments, and disaster recovery.

Do I need agents to migrate VMs from AWS, Azure, or Google Cloud?

For these sources, yes. Hystax replicates public cloud VMs through an agent installed in the guest OS. Replication without in-guest agents is available only for VMware, oVirt, and OpenStack sources.

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