• Rising and unpredictable cloud costs due to multiple teams deploying resources independently.
• Lack of cost visibility and reporting, making it hard for management to allocate budgets effectively.
• Manual cost optimization processes were time-consuming and error-prone.
• Need to balance cost savings with performance and uptime, avoiding disruptions to production services.
• Difficulty forecasting future cloud spend for scaling and budgeting purposes.

• Implemented a cloud cost monitoring platform across AWS and Azure, providing real-time dashboards and alerts.
• Built automated tagging and resource tracking policies to associate costs with projects, teams, and business units.
• Developed cost optimization scripts and policies, including:
  • Right-sizing instances
  • Auto-scaling adjustments
  • Idle resource termination
  • Reserved instance recommendations
• Created budgeting and forecasting models using historical usage data and predictive analytics.
• Integrated FinOps workflow with DevOps pipelines to enforce cost-aware deployments.
• Provided monthly reports and executive dashboards for leadership to monitor spending trends and ROI.

Impact

• Reduced cloud infrastructure costs by 25% annually
• Improved cost visibility and accountability across teams.
• Enabled predictive budgeting for future projects and expansions.
• Increased operational efficiency by automating cost optimization and reporting.
• Strengthened collaboration between finance, IT, and engineering teams for better resource planning.