Cloud Cost Intelligence Agent
Automated FinOps analysis
Designed a multi-phase cloud cost analysis agent that collects data from 18 Azure services, runs 13 anomaly detection algorithms, and generates actionable cost optimization recommendations. The agent operates in 3 phases: data collection, analysis, and recommendation generation. It identified unused resources, over-provisioned services, and scheduling opportunities that resulted in a 30% reduction in cloud spend.
30%
cost reduction
18
data collectors
13
anomaly detectors
3
analysis phases
Architecture & Implementation
How it's built
18 data collectors spanning compute, storage, networking, and PaaS
3-phase pipeline: collection → analysis → recommendations
13 anomaly detection algorithms for spend patterns
Resource utilization scoring and right-sizing suggestions
Scheduling recommendations for non-production workloads
Cost allocation and tagging compliance checks