Cloud Migration & Cost Optimisation

Two failure modes dominate. The first is lift-and-shift: the same architecture, now billed hourly, with none of the elasticity that justified the move. The second is the opposite — a rewrite so ambitious it never lands.

The useful path is usually in between, and it is sequenced so that value arrives early and the business is never holding its breath.

Migration

We start with a dependency-honest inventory: what talks to what, what the real data volumes are, and which systems are load-bearing for revenue. That determines the order of work. Anything that moves gets defined in Terraform on the way, because the second environment is where the savings are, and manual setup does not survive contact with a second environment.

Cost optimisation

Cloud overspend is rarely one big mistake. It is compute provisioned for a peak that lasts twenty minutes a day, storage tiers nobody revisited, environments idling overnight, data transfer nobody attributed, and managed services bought for convenience and never reviewed.

The first job is visibility — tagging and attribution good enough that costs land against the team or product responsible. That alone changes behaviour. Then the structural work: right-sizing, autoscaling that reflects real demand curves, scheduling non-production workloads down outside working hours, and dynamic resource allocation for batch and analytics loads.

What you walk away with

Reproducible infrastructure, a forecastable bill, and an internal cost-review habit that keeps it that way after we leave.