FinOps — Cloud Infrastructure Cost Optimization
Optimization of cloud spending through data-driven cost analysis
Client: A large industrial construction enterprise, Germany
$2M+
accumulated savings over two years
$450K
saved annually through VM rightsizing
$300K
saved annually on storage optimization
Challenge
Cloud spend was high for the wrong reasons: underutilized virtual machines and inefficient resource allocation. Usage had to come down without performance following it.
Solution
An in-depth analysis of VM usage that identified overprovisioned and unused resources for rightsizing or removal, turned into actionable recommendations through Azure tooling and Power BI — and then into automated cost-saving strategies.
Implementation
- 01Cloud server utilization monitored across CPU, memory, IOPS, GPU and price
- 02Underused machines and unlinked disks identified
- 03Optimization recommendations delivered through Azure APIs and Power BI
- 04Recommendation engine started, to automate future savings and track implementation
- 05Continuous support and detailed reporting
Business impact
$450K saved annually through VM rightsizing
$300K saved annually on storage optimization
$2M+ accumulated savings over two years
Ongoing savings from automated recommendations and cost governance
Technology stack
Have a complex system to build or modernize?
Tell us what must change. We will bring the relevant domain and engineering leads into the conversation.