Leading US Travel Firm Saves $8M+ in Annual AWS Spend Leveraging Coforge FinOps CoE
Overview
A global travel technology leader, operating multiple brands and receiving over 80 million monthly visits, was facing escalating AWS cloud costs. Despite taking initial FinOps steps such as rightsizing, shutting down idle instances, and tagging for accountability, cost containment remained a challenge.
The client had already implemented foundational FinOps practices but continued to see a steady rise in cloud expenses. These traditional measures were no longer sufficient to drive meaningful savings. They needed a more advanced, sustainable strategy that could reduce costs without affecting performance or scalability. To address this, they engaged Coforge as a strategic partner to lead the next phase of their cloud optimization journey.
Solution.
Coforge deployed a FinOps Center of Excellence and comprehensively analyzed AWS consumption patterns, architectural inefficiencies, and DevOps processes. The engagement spanned 8 months and involved collaboration across infrastructure, DevOps, and finance teams. Coforge implemented eight targeted cost-optimization initiatives, including:
Cluster Modernization: Upgraded 250+ Amazon EKS clusters to the latest supported version to eliminate legacy support costs.
Instance Optimization: Migrated 1,800+ EC2 instances to Graviton-based nodes for better price-performance ratios.
Application Re-architecture: Transformed 80+ monolithic applications into serverless or microservices-based architectures to reduce idle resource usage.
Dynamic Autoscaling: Implemented Karpenter to dynamically provision the most cost-effective EC2 instance types, including spot instances, for autoscaling.
Database Migration: Transitioned 800+ Microsoft SQL Server databases to Aurora PostgreSQL using Coforge’s proprietary DB automation accelerators.
CI/CD FinOps Integration: Embedded FinOps cost checks into 450+ CI/CD pipelines to drive cost-aware deployments.
Policy Enforcement: Kyverno was deployed to enforce real-time Kubernetes resource policies and prevent waste across EKS clusters.
Real-Time Anomaly Detection: Developed and deployed ML-based anomaly detection models to proactively flag cost spikes for immediate remediation.
The Impact
$8M+
Annual Cloud Cost Savings through Strategic FinOps Execution
16%
Year-on-Year Reduction in overall AWS spend
100%
Compliance Achieved with Embedded Cloud Cost Policies Across All Environments
92%
Forecasting Accuracy for cloud consumption and budgeting
Standardized FinOps practices were implemented across all brands and DevOps teams to ensure long-term sustainability. Building on this foundation, six advanced initiatives were identified in Phase 2, with an expected annual savings of $12M
