AWS cost optimisation and FinOps

Cloud bills grow quietly. Nobody approves the increase; it accumulates from resources that were provisioned for a reason that has since disappeared.

We find that spend, prove it against live usage, and remove it - then put the practices in place so it does not silently return.

Confirmed, not estimated

There is a large difference between “this instance looks over-provisioned” and “this instance has run below 5% CPU for ninety days”. We measure before recommending, and we separate the changes that carry zero risk from the ones that need a change window.

The first pass usually finds the same categories: gateways provisioned for traffic that no longer flows, snapshots from years ago with no lifecycle policy, addresses attached to nothing, and stopped instances still billing for their storage. That work is typically deletable in week one with no code change and no downtime.

Then the structural savings

Rightsizing and Graviton migration usually deliver more than the quick wins, but they need care - a change window, a rollback plan, and load testing where it matters. Commitment planning comes after that, because buying a Savings Plan against a workload you are about to halve in size locks in the wrong number.

Storage is consistently under-examined. Lifecycle policies, intelligent tiering on backup and log buckets, and cleaning up incomplete multipart uploads are unglamorous and reliably worthwhile.

FinOps, so it holds

One-off optimisation decays. Within a year you are back where you started unless something changes structurally.

We set up tagging so cost is attributable to a team and a service, showback so those teams see what they spend, anomaly detection so a runaway workload surfaces in hours instead of at month end, and a quarterly review cadence so it stays a habit rather than a project.

Start with our free cost audit. We will tell you what is recoverable before you commit to anything.