Cloud
The full domain, and the other capabilities within it.
Cloud Optimization
You cannot reduce a bill you cannot attribute.
What this is
Cloud optimization makes cloud spend visible, attributable and adjustable. Usage telemetry, tagging and allocation come first; then right-sizing, commitment planning and autoscaling; then the guardrails that stop the gains eroding.
The failure mode is the one-off cost exercise. Somebody deletes unused volumes, resizes a few instances and reports a saving, and six months later the bill is back where it started because nothing changed about how resources get created. Optimization that is not wired into provisioning and budgets is a project, not a capability.
When you need it
If more than one of these is true, this is usually the right place to start.
- The monthly cloud bill is understood by one person and explained to nobody.
- A large share of spend lands in an untagged or shared bucket that no team owns.
- Environments provisioned for a project are still running long after the project ended.
- Commitments and reservations were bought once and have never been reviewed against actual usage.
What the scope covers
- Usage and cost telemetry collected across accounts, subscriptions and projects into one comparable view.
- Tagging standard and enforcement, so allocation is a property of provisioning rather than a monthly reconciliation.
- Right-sizing analysis based on observed utilisation over a representative period, not on a peak-day snapshot.
- Commitment and discount planning matched to the workload baseline you can actually defend.
- Budgets, alerts, showback reporting and policy guardrails that keep new resources inside the model.
What you receive
| Deliverable | What it contains |
|---|---|
| Cost allocation model | Every account, tag and shared cost mapped to an owning team or service, with the unallocated residue stated rather than hidden. |
| Right-sizing plan | Per-resource recommendations carrying the utilisation evidence behind each one and the risk of acting on it. |
| Commitment strategy | Coverage targets set against the stable baseline, with flexible headroom left deliberately uncommitted. |
| Guardrails and budgets | Provisioning policy, budget thresholds and alerts wired to the owners who can actually act on them. |
Reference architecture
A reference, not a template. Your estate decides which parts apply and in what order they arrive.
How success is measured
Targets are agreed with you before the work starts, and reported against for its duration.
- Proportion of spend attributable to a named owner, tracked as continuous tagging coverage rather than a one-time audit.
- Utilisation of committed capacity against what was purchased, reviewed each billing period.
- Unit cost per workload or per transaction against its own baseline, so growth and waste can be told apart.
Questions we are asked
How much can we save?
Nobody can answer that before seeing your usage data, and a number quoted in a proposal is a sales artefact. What can be said in advance is where savings usually sit: idle non-production environments, over-provisioned databases, unattached storage and uncommitted steady-state compute. The size depends entirely on how much of that you have.
Will right-sizing put performance at risk?
It can, which is why the evidence period matters. A recommendation drawn from a quiet fortnight will resize something that needed the headroom at month-end. We work from a period that includes your known peaks, change in stages, and keep the previous size as a documented rollback.
Should we buy reservations or commitments?
For the part of your usage that is genuinely steady, yes; the discount is real and the risk is low. The mistake is committing to a baseline that includes workloads you are about to change or retire. Commit to the floor you are confident about, leave the uncertain part on demand, and revisit as the picture firms up.
Is this a project or something ongoing?
Both, and treating it only as the first is why costs return. The project establishes allocation, removes the obvious waste and sets the commitments. What keeps it is the routine: budgets with owners, a review each billing cycle, and provisioning rules that stop untagged and oversized resources being created in the first place.
Who should own cloud cost?
The teams that create the spend, supported by a central function that supplies the data and the standard. Cost owned only centrally becomes a report nobody acts on. Cost owned locally without a shared model becomes four teams calculating differently. Showback works when the numbers reach the people who can change them.
Do we need a dedicated cost tool?
Not always. Native billing and cost tooling is sufficient for a single-platform estate with clean tagging. A third-party tool earns its licence when you span several platforms, need chargeback with a shared-cost model, or want a view your finance function can reconcile. Fix the tagging first either way, because no tool can allocate data that was never labelled.
Continue reading
Business Continuity
Impact analysis, RPO and RTO targets, failover design and tested runbooks, so recovery is something you have rehearsed rather than something you assume.
Cloud Migration
Application inventory, landing zone design and wave-based cutover for moving workloads to AWS, Azure or GCP with dependencies mapped before the window.
Start with an assessment
The fastest way to a useful answer is a short, scoped look at what you already have.