Move the workloads. Leave the mistakes.

Lift, shift, regret

The cloud charges rent on every architectural shortcut, monthly, forever. Move the machines without touching the design and you inherit the same failure modes at a higher price — plus a new vocabulary for explaining them to the board.

• A bill that grows faster than usage, and nobody can say which team owns which half.
• Downtime windows negotiated with customers a quarter in advance.
• A compliance question at 70% complete that stops everything.
• One provider’s proprietary services quietly becoming your architecture.

A migration with an exit at every step

We inventory what you actually run, sort it by risk and data gravity, and move the cheap wins first so early savings fund the hard parts. Every workload gets its own plan, its own rollback, and its own cost target — agreed before anything moves.

• Workload inventory with dependencies, data gravity, and a risk score per system
• Target architecture with a cost projection per workload, reviewed before you commit
• Infrastructure as code for every environment — no console archaeology, no snowflake servers
• Cutover runbooks with rehearsal results, rollback steps, and a downtime budget per workload
• Cost guardrails in place: budgets, alerts, autoscaling policies, right-sized instances
• A post-migration report putting projected spend next to actual spend, workload by workload

1. 01

   Inventory

   Everything you run, what depends on it, and what it costs today — including the two servers nobody will claim.

2. 02

   Sequence

   Order the moves so the early wins fund the hard ones, and nothing business-critical goes first.

3. 03

   Migrate

   Rehearse, cut over, verify against the old system, and keep the rollback path warm until the new stack has earned trust.

4. 04

   Optimise

   Right-size against real usage, set the guardrails, and hand over the dashboards that keep the bill honest.

Cost control here is a delivered result, not a slogan. Rebuilding SeoStack’s analytics platform produced a 50× performance gain over BigQuery and cut infrastructure cost by more than 80% — because the architecture changed, not just the address. That is the question we ask of every workload before it moves.

• Which cloud should we choose?

  Whichever fits your workloads, your team’s skills, and your compliance boundary. We carry no reseller margin, so the recommendation is free of at least that bias.

• How much downtime will there be?

  That is a design decision, not a fixed number. We set a downtime budget per workload up front, rehearse against it, and price what driving it to near zero would take. Anyone quoting you a figure before seeing your systems is guessing.

• What about data residency and compliance?

  Decided during inventory, not discovered in month six. Data gravity and legal boundaries drive the sequence. We have built a multi-tenant platform for German legal tech — claims, foreclosure, dunning — where strict data isolation was the requirement rather than a checkbox.

• What if we want to stop halfway?

  Then you stop. Sequencing exists so every stage leaves you in a working, defensible state — including the one where you decide the remaining workloads stay exactly where they are.