As Azure usage scaled, following multiple client migrations and hybrid cloud rollouts, costs began to spiral. What started as a $12,000/month spend had grown to over $19,000 in just six months. I spearheaded a cross-functional effort to reduce spending without compromising performance, availability, or security.

The first step was visibility. I deployed Azure Cost Management, Azure Advisor, and integrated Log Analytics and Application Insights for deeper usage insights. To visualize the data, I built an internal Power BI dashboard that mapped cost trends across clients, resource groups, and project workloads and transformed raw billing data into actionable intelligence.

I managed the optimization in three key areas:

• I identified underutilized VMs and scaled them down based on 30-day performance patterns. Using Azure Metrics and custom scripts, we reconfigured VM sizes, downgraded storage tiers, and scheduled idle resources to auto-shutdown using Azure Automation.
  
  
• For always-on workloads, I implemented 1- and 3-year Reserved Instances, reducing compute costs by up to 57%. A Python script I developed parsed VM uptime patterns to recommend the best RI terms per client and subscription.
  
  

Cleanup & Automation: We removed over 60 unattached disks, stale IPs, and orphaned backups. I built PowerShell cleanup scripts triggered via Azure Automation, ensuring these cost leaks were automatically flagged and addressed on a recurring basis.