Case Study — Mortgage. Cloud COST Optimization
Cloud Cost Optimization for a Leading Mortgage Provider
Our client, a major U.S.-based mortgage lender, faced growing AWS bills despite stable usage. Their dev environment was overprovisioned with static infrastructure and lacked autoscaling, leading to inflated RDS, EC2, and EBS costs. We partnered to right-size their architecture, implement intelligent scheduling, and deploy autoscaling — driving significant cost reductions without compromising performance.
Success Highlights
Key Details
Industry: Fintech / Mortgage Lending Geographies: US
Platform: Multi-account AWS environment with cost optimization tooling
Business Challenge
Our client needed to reduce AWS infrastructure costs while improving elasticity and long-term operational efficiency.
Our Solution Approach
We designed a multi-phase AWS cost optimization strategy, combining resource right-sizing, intelligent automation, and governance enhancements.
1 · Analyze
Assess Cloud Usage and Performance Metrics
We reviewed billing reports, CloudWatch metrics, and configurations to identify underutilized services and performance bottlenecks.
2 · Architect
Scalable, Cost-Optimized AWS Environment
Designed a right-sized RDS instances, migrated to T3 burstable types, and introduced Reserved Instances for steady workloads
3 · Automate
Deploy Autoscaling and Scheduling Logic
We implemented autoscaling for ECS, built CPU/memory-based thresholds, and automated shutdowns of idle resources outside business hours.
4 · Govern
Establish Guardrails, Tagging, and Documentation
Implemented tagging policies, alerting mechanisms, backup routines, and communication protocols to improve transparency and control.
Technical Highlights
RDS downsizing from db.m5.xlarge to T3 instances
ECS autoscaling enabled via CloudWatch thresholds
Intelligent shutdown scheduling using Lambda and AWS EventBridge
Reserved Instances strategy for predictable workloads
Resource tagging for cost ownership and accountability
function optimizeAWSCosts(account):
infraData = collectCloudWatchMetrics(account)
usageReport = fetchBillingReport(account)
for service in account.services:
if isUnderutilized(service):
rightSize(service)
if isIdleOutsideBusinessHours(service):
scheduleShutdown(service)
if isPredictableWorkload(service):
applyReservedInstance(service)
tagResources(account)
setAlertingGuardrails(account)
documentChanges(account)
return “Optimization Complete”
Business Outcomes
Our solutions delivered tangible improvements in cloud efficiency, cost savings, and operational scalability.
50%
RDS cost reduction through right-sizing and burstable instances
29%
projected AWS savings via Reserved Instance adoption
80%
idle time reduction achieved through dynamic ECS autoscaling
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