AWS Cloud · FinOps

Cloud Cost Optimisation

Cost visibility, architectural efficiency and ongoing controls — including the spend patterns specific to AI workloads.

What usually brings people here

An AWS bill that grows faster than the business usually reflects architecture, not waste alone. Rightsizing helps once; the pattern that produced the cost keeps producing it.

How we approach it

We separate the three levers — buy better, use less, design differently — and work them in that order of effort. Tagging and allocation come first, because a cost you cannot attribute is a cost nobody owns.

Cost control loop

  1. 1

    Tag

    Environment, team, product

  2. 2

    Attribute

    Spend mapped to an owner

  3. 3

    Right-size

    Against observed utilisation

  4. 4

    Re-architect

    Where shape drives the cost

  5. 5

    Commit

    Sized to a settled baseline

  6. 6

    Monitor

    Budgets and anomaly alerts

Attribution comes first — a cost nobody owns is a cost nobody reduces.

Cost visibility and allocation

Attribution to a team, product or customer, so decisions have an owner.

  • Tagging strategy and enforcement
  • Cost allocation across accounts and workloads
  • Budgets, anomaly detection and alerting
  • Reporting that engineering and finance both recognise

Resource and architecture efficiency

Rightsizing addresses the symptom. Architecture addresses the cause.

  • Compute rightsizing and instance family selection
  • Storage lifecycle and tiering
  • Data transfer and egress reduction
  • Serverless and managed-service adoption where it lowers total cost

Commitments and purchasing

Savings Plans and Reserved Instances sized against real usage patterns rather than optimism.

  • Usage analysis and commitment modelling
  • Coverage and utilisation monitoring
  • Graviton and modern instance migration
  • Purchase cadence and review process

AI workload cost control

Token spend behaves differently to compute spend, and it needs its own controls.

  • Per-feature and per-agent token accounting
  • Model selection and routing by task complexity
  • Caching, batching and context-size discipline
  • Spend ceilings and runaway-loop protection

What you receive

  • Cost analysis with findings ranked by saving and effort
  • Tagging and allocation model, implemented
  • Commitment plan sized to actual usage
  • Monitoring, budgets and anomaly alerts
  • Optimisation roadmap with quick wins separated from architectural work

What should change

  • Spend attributable to a team or product
  • Infrastructure waste removed rather than rediscovered quarterly
  • AI workloads with a predictable cost ceiling
  • A review cadence that keeps the gains

AWS services we commonly use

  • AWS Cost Explorer
  • AWS Budgets
  • AWS Compute Optimizer
  • AWS Trusted Advisor
  • Amazon S3 Intelligent-Tiering
  • AWS Graviton
  • Amazon CloudWatch

Talk this through with an engineer

Thirty minutes is usually enough to establish whether this is the right service for your situation.

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