Cloud to on-prem,
without the cutover drama
Assessment, target architecture, migration and the operational handover after it. For teams moving off public cloud for cost, data residency or control — and for teams who just want their bill to match their utilisation.
Migration capabilities
A migration is mostly discovery and rehearsal. The move itself should be the least interesting day of the project.
Workload and dependency assessment
We map what actually runs: services, data stores, scheduled jobs, managed-service dependencies and the undocumented links between them. Nothing gets moved before it is on the map.
Target architecture design
Full on-premise, hybrid or multi-cloud, chosen against your data residency, latency and cost constraints — with the trade-offs of each option written down, not implied.
Kubernetes and container migration
Cluster topology, ingress, storage classes and secrets rebuilt on the target platform. Managed-service dependencies replaced with self-hosted equivalents that your team can operate.
Database and legacy migration
Schema and data movement with replication-based cutover, plus a route for legacy applications that were never designed to be portable.
CI/CD and observability continuity
Pipelines, staging environments, monitoring and structured logging are adapted alongside the workloads, so the day after cutover looks like the day before.
Cost analysis and right-sizing
We measure real utilisation, identify waste and size the target for it. The output is a spend model you can check against your own invoices.
Three ways to move, chosen deliberately
Most projects combine all three, applied per service group rather than to the whole estate at once.
Move workloads with minimal change to reach the target platform quickly, then optimise once the new environment is proven. Lowest risk, highest short-term duplication.
Rework the parts that are bound to a specific provider — managed queues, proprietary storage APIs, serverless entry points — so the result is genuinely portable.
Move one bounded service group at a time behind a stable interface, running both environments in parallel until each phase is verified. Cutover becomes routine rather than an event.
After go-live
What we work with
- Kubernetes
- Docker
- Helm
- Nomad
- PostgreSQL
- MongoDB
- ClickHouse
- Redis
- CI/CD pipelines
- Staging environments
- Infrastructure as code
- Rollback procedures
- OpenTelemetry
- Sentry
- Structured logging
- Runbooks
Connected expertise
Considering a move off public cloud?
Send us your current architecture and a recent bill. We will come back with a realistic assessment scope, a candidate target architecture and where the savings actually are.