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Cloud Engineering

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.

Scope an engagement

Engagements from $12,000. Or start with the Exposure Review at $4,500.

Pricing status: confirmed. PinkCloud quotes from these figures.

Prices exclude any applicable tax.

What an engagement looks like

Scoped as fixed-window work with a written deliverable. No retainers you cannot exit, no findings held back for a follow-on sale.

Position

The savings that survive are architectural.

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.

  • Common finding

    Untagged shared infrastructure

    The largest line item belongs to no team, so no team optimizes it.

  • Common finding

    Egress nobody modelled

    Cross-AZ and cross-region transfer priced per gigabyte, generated by a topology chosen for convenience.

  • Common finding

    Standing capacity as insurance

    Over-provisioning that persists because an autoscaler failed once, years ago.

  • Common finding

    GPU utilization in the teens

    Reserved accelerators idling between batches, billed continuously.

Order

Cloud Assessment

Two weeks on where the money actually goes before anything is changed, or on what CI/CD, environment topology and the identity model really look like, delivered as a costed list of opportunities with effort estimates against a baseline you agree up front.

Two weeks at the published floor for the cloud practice. The floor covers up to 3 distinct systems, models or accounts; beyond that, each further block of up to 3 systems adds 10 percent, capped at 30 percent, and more than 12 systems needs a scoping call.

Two weeks buys the shorter of the practice's shapes, chosen at the scoping call: the Cost attribution and FinOps review (the site scopes it at 2–3 weeks, diagnostic) or the Platform and delivery review (2–4 weeks, assessment). The cost shape finds out where the money actually goes before anything is changed: tag hygiene, shared-resource allocation, and per-team or per-feature unit economics — cost per tenant, per request, per thousand tokens. The platform shape assesses CI/CD, infrastructure-as-code and environment topology against delivery speed and blast radius together, including the identity model: who and what can reach production, and how much of that is standing privilege that should be temporary.

Coverage is AWS, GCP and Azure, plus Kubernetes, Terraform and the managed data and inference services. We will not quote a saving before looking, and you should be wary of anyone who does; if the honest answer is that the estate is already lean, that is the finding, and it arrives in week two rather than month four.

assessment

Two weeks on where the money actually goes before anything is changed, or on what CI/CD, environment topology and the identity model really look like, delivered as a costed list of opportunities with effort estimates against a baseline you agree up front.

$12,000

2 weeks

120 hours at $100/hour

Pricing status: confirmed. PinkCloud quotes from these figures.

Prices exclude any applicable tax.

Deliverables

  • A written deliverable, named in the proposal before the work starts
  • Cost shape — cost attribution: tag hygiene, shared-resource allocation, and per-team or per-feature unit economics (cost per tenant, per request, per thousand tokens)
  • Cost shape — a costed list of opportunities with effort estimates, so you decide what is worth doing
  • Cost shape — the baseline the savings from any later work are measured against, agreed up front
  • Platform shape — CI/CD, infrastructure-as-code and environment topology assessed against delivery speed and blast radius
  • Platform shape — deployment frequency and change-failure rate as measured, not aspirational
  • Platform shape — the identity model: who and what can reach production, and how much of that is standing privilege

Exclusions

  • The practice's longer shapes: the Optimization programme (4–8 weeks, implementation) and Performance engineering (3–6 weeks, targeted), which are quoted as engagements at a weekly rate
  • Implementing the changes: the diagnostic produces a costed list of opportunities with effort estimates, and you decide what is worth doing
  • Reselling cloud capacity: we are not a reseller and we hold no marketplace margin
  • A percentage of savings: engagements are fixed-fee, which is what keeps the advice honest
  • A compliance certificate or an audit opinion: a larger firm with an audit practice will serve you better and cost less
  • Compliance evidence deliverables: these add 10 percent to the floor
  • Staff augmentation: fixed-scope work with an end date, not two engineers embedded for six months
  • Incident response and on-call cover: we are not an incident-response retainer and we do not carry a pager
  • On-site attendance: delivery is remote by default, and on-site work needs a scoping call
  • None of the above is a refusal: everything here has a route and a rate. Work outside this scope is quoted at our published hourly rate — as a change request during the engagement, or as a separate engagement afterwards — and is agreed in writing before it starts. The assessment itself is an agreed budget of 120 hours at that rate
Order

Questions we get asked

Are you reselling cloud capacity or taking a cut of savings?
Neither. We are not a reseller, we hold no marketplace margin, and we do not take a percentage of what we save you. Engagements are fixed-fee, which keeps the advice honest — there is no upside for us in recommending a commitment you should not make.
Which providers do you cover?
AWS, GCP, and Azure, plus the layers most teams actually run on top of them — Kubernetes, Terraform, and the managed data and inference services. Multi-cloud estates are common in the cost work, since the duplication between them is frequently where the waste is.
How much can we expect to save?
We will not quote a number before looking, and you should be wary of anyone who does. The diagnostic produces a costed list of opportunities with effort estimates, and you decide what is worth doing. If the honest answer is that your estate is already lean, that is the finding, and it arrives in week two rather than month four.
Will optimization make us less reliable?
It can, if it is done as a spreadsheet exercise. Every change is assessed for its effect on failure modes as well as its effect on the bill — removing redundancy is a cost saving right up until the moment it is an incident. Reliability constraints are agreed before the optimization work starts, and changes ship behind the same review as any other production change.
Do you handle AI workload costs specifically?
Yes, and it is increasingly the reason people call. Inference economics behave differently from traditional compute: cost scales with usage in a way that makes abuse a billing event, batching and caching decisions dominate unit cost, and idle GPU capacity is expensive in a way idle CPU never was. This overlaps directly with the AI security practice.