case study
Industry
Specialist Engineering & Construction
Cloud Suite
Microsoft Azure
Results
Identified £63,000 in immediate annual savings
context
Client Context & Background
The client, a specialist engineering and construction firm, was facing a common cloud challenge: paying for resources that were no longer delivering value. A lack of consistent tagging meant the team couldn't easily see which projects were profitable or where money was being wasted. Unused servers and databases were still running and silently draining the budget, many machines were far more powerful than necessary for the workloads they supported, and a legacy data lake was costing roughly £3,600 every month in lost potential savings due to delays in retiring it.
Results
Results & Outcomes Achieved
The engagement identified £63,000 in immediate annual savings without disrupting operations. This broke down into £26,300 from Virtual Machines through orphaned resource removal and rightsizing, £15,900 from disks through redundant resource cleanup and Premium-to-Standard downgrades, £11,700 from storage through reservations and decommissioning the legacy data lake, and £9,700 from databases through termination of unused resources and expert rightsizing review. Beyond the numbers, the engagement revealed which customers and services were profitable, gave leadership a plan to move from Crawl to Walk stage FinOps maturity, and established a governance model to prevent costs from spiralling again.
Process
Our Process & Key Observations
Finabeo conducted a two-week analysis of the client's cloud environment using a Remove–Rightsize–Reserve model to find quick wins that wouldn't disrupt business operations. Optimus was used to identify orphaned and underutilised VM resources, storage disks associated with dormant VMs, and redundant disks suitable for removal or downgrade. A strategic rightsizing plan was delivered as Phase 1, followed by a reserved instance optimisation plan as Phase 2. Databases were reviewed for termination and rightsizing candidates, and storage reservation and decommissioning opportunities were costed. Recommendations were paired with a governance model and maturity roadmap.
