Weeks 1–2
Visibility
Consolidated billing data, built cost dashboards by account, service, and team, and established the baseline.
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CASE STUDY · FINOPS & CLOUD COST
Reducing cloud spend by 85% with a FinOps operating model
A cost assessment and targeted optimization program removed idle capacity, right-sized workloads, and gave engineering and finance a shared view of spend.
Industry
SaaS & technology
Scale
4 cloud accounts · 1,100+ resources · 6 product teams
Duration
10 weeks
Service
FinOps & Cloud Cost
85%
reduction in monthly cloud spend
96%
of spend allocated to an owner, up from 30%
78%
commitment coverage on steady workloads
< 1 month
payback on the engagement
THE CHALLENGE
Where things stood.
Cloud spend had grown faster than revenue, and nobody could say which team or product was responsible for most of it.
Non-production environments ran around the clock, many workloads were sized for peak traffic that never arrived, and commitment discounts were largely unused.
OUR APPROACH
How the engagement ran.
Delivered in phases with a weekly status review and a steering check-in at each milestone.
Weeks 3–4
Allocation
Defined a tagging standard, enforced it in infrastructure code, and mapped untagged spend to owners.
Weeks 5–8
Optimize
Decommissioned idle resources, right-sized compute and databases, scheduled non-production shutdowns, and adopted savings plans for steady workloads.
Weeks 9–10
Operate
Introduced monthly cost reviews, budget alerts, and anomaly detection so savings would hold.
Technology stack.
AWS
Google Cloud
Terraform
Kubernetes
RESULTS
Before and after.
Measured against the baseline agreed at the start of the engagement.
| Measure | Before | After |
|---|---|---|
| Monthly cloud spend | Baseline | 85% lower |
| Spend allocated to an owner | 30% | 96% |
| Idle and orphaned resources | 300+ | Decommissioned |
| Commitment coverage (steady state) | < 20% | 78% |
| Cost review cadence | Ad hoc | Monthly, with budget alerts |
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START A CONVERSATION
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