Cloud Cost Optimization Project – Azure & AWS

Objective: To reduce cloud spend and improve resource efficiency across multi-cloud (Azure & AWS) environments through automation, right-sizing, and governance best practices.

Project Overview:

• Conducted detailed cost analysis and utilization assessment using Azure Cost Management, AWS Cost Explorer, and CloudWatch metrics to identify underutilized and idle resources.
• Implemented auto-scaling, instance right-sizing, and storage lifecycle policies to optimize compute and storage costs across both clouds.
• Applied Azure Advisor and AWS Trusted Advisor recommendations for performance tuning and cost reduction.
• Automated resource tagging, shutdown/startup schedules, and budget alerts using Azure Automation Runbooks and AWS Lambda scripts.
• Migrated workloads to reserved instances and spot instances where applicable, reducing compute costs by up to 30–40%.
• Defined FinOps governance policies and dashboards for continuous monitoring using Power BI / AWS Cost Anomaly Detection.
• Worked with DevOps teams to integrate cost visibility into CI/CD pipelines, ensuring efficient resource provisioning.
• Delivered monthly cost reports and savings analysis to leadership, highlighting ROI and optimization roadmap.

Tools & Technologies:

Azure Cost Management | AWS Cost Explorer | Azure Advisor | AWS Trusted Advisor | CloudWatch | Power BI | Terraform | Azure Automation | AWS Lambda | FinOps | CI/CD Pipelines

Key Achievements:

• Achieved 35% overall cost reduction without impacting performance or SLA.
• Established automated governance framework for continuous optimization across multi-cloud platforms.