Case Study
FinOps Cost Optimization Portal
Analytics portal that tracks cloud spend, flags anomalies and recommends cost saving actions.
PythonFastAPIPostgreSQLRedisDocker
Problem Statement
Engineering teams lacked visibility into cost spikes and underutilized resources across cloud services.
Dataset / Scale
Daily billing exports, 12+ services, multi-account aggregation with trend analysis.
Architecture Diagram
ETL layer transforms billing exports
Anomaly detection pipeline + rule-based alerts
Dashboard API with cached aggregates
Role based access for team reporting
ML / LLM Pipeline
Extract billing data → Normalize → AggregateDetect anomalies → Notify → ReportSurface recommendations → Track savings
System Design
- FastAPI backend with async endpoints
- Redis caching for dashboards
- PostgreSQL analytics tables
- Dockerized deployment
Engineering Challenges
- Reducing noisy alerts for short lived spikes
- Keeping dashboards under 200ms p95
- Aligning cost tags across teams
Metrics
- 25% faster anomaly detection
- 18% monthly savings identified
- 200ms p95 dashboard latency
Screenshots
Cost anomaly heatmap by service
Optimization recommendations view
Monthly savings report dashboard