Run it
DevOps and FinOps for teams whose infrastructure bill grew faster than their traffic. We find where the money and the milliseconds go, then do the work to fix it — measured against a baseline you agree to up front.
Engagements from £12,000. Or start with a Exposure Review from £4,500.
Scoped as fixed-window work with a written deliverable. No retainers you cannot exit, no findings held back for a follow-on sale.
2–3 weeks · diagnostic
Find out where the money actually goes before changing anything. Tag hygiene, shared-resource allocation, and per-team or per-feature unit economics — cost per tenant, per request, per thousand tokens. Most organizations discover their largest line item is something nobody owns, and that the second largest is egress they did not know they were paying for.
4–8 weeks · implementation
Execution against the diagnostic: rightsizing, commitment coverage, storage tiering, and the architectural changes that matter more than any of those — killing chatty cross-AZ traffic, fixing retry storms, and removing the always-on capacity that exists because an autoscaler was never trusted. Savings are tracked against a baseline agreed up front.
3–6 weeks · targeted
Latency and throughput work driven by profiling rather than intuition. Tail latency, connection pooling, cache topology, and the database access patterns behind most of it. Where the workload is inference, this includes batching strategy, quantization trade-offs, and GPU utilization — which is usually far lower than anyone assumes.
2–4 weeks · assessment
CI/CD, infrastructure-as-code, and environment topology assessed against delivery speed and blast radius together. Deployment frequency and change-failure rate as measured, not aspirational. Includes the identity model: who and what can reach production, and how much of that is standing privilege that should be temporary.
Position
Rightsizing and commitment coverage are real, and we do them. They are also the easy half, they are largely one-off, and the estate drifts back within two quarters if nothing structural changed.
The durable reductions come from removing work rather than buying it cheaper: the cross-AZ chatter in a service mesh nobody tuned, the retry policy amplifying a downstream failure into a spend spike, the nightly job re-reading a dataset it could have cached. Those do not drift back.
The largest line item belongs to no team, so no team optimizes it.
Cross-AZ and cross-region transfer priced per gigabyte, generated by a topology chosen for convenience.
Over-provisioning that persists because an autoscaler failed once, years ago.
Reserved accelerators idling between batches, billed continuously.