This case study details how Mist Avinya supported Franciscan Solutions in improving AWS cost visibility, governance, and forecasting accuracy through the implementation of a structured FinOps operating model.
The Challenge
- Limited cost visibility across disparate environments and production workloads.
- Unpredictable AWS spend caused by significant seasonal traffic spikes.
- Inaccurate chargeback reporting due to inconsistent resource tagging.
- Difficulty balancing strict governance with the need for high application scalability.
The Strategic Solution
1. FinOps Operating Model
Mist Avinya established a cross-functional framework that integrated engineering, finance, and operations teams to align cloud spend with business value.
2. Visibility & Data Insights
- Leveraged AWS Cost and Usage Report (CUR) integrated with Aquila Clouds FinOps Optimizer.
- Enabled granular querying of cost data via Amazon Athena and Amazon S3.
- Standardized tagging policies to ensure 100% cost allocation ownership.
3. Optimization & Control
- Executed rightsizing and scheduling for EC2 workloads to match demand cycles.
- Automated storage costs through S3 lifecycle policies.
- Deployed AWS Budgets and anomaly detection for real-time spend alerts.
Architecture Overview
The infrastructure utilizes a highly available design across multiple Availability Zones. Core workloads run on Amazon EC2 and AWS Lambda, with data persistence managed through Amazon DynamoDB and Amazon S3.
Key Outcomes
| Performance Metric | Outcome achieved |
|---|---|
| Monthly Cost Reduction | 25–30% reduction over engagement |
| Tagging Compliance | >95% across all mandatory tags |
| Forecast Accuracy | Stabilized during seasonal demand peaks |
| Operational Control | Centralized policies and 24/7 monitoring |
Business Impact
- Financial Predictability: Established a reliable baseline for cloud budgeting.
- Reduced Overhead: Automation of governance policies reduced manual operational tasks.
- Strategic Alignment: Engineering usage is now directly aligned with financial accountability goals.