Franciscan Solutions – AWS FinOps Case Study

CustomerFranciscan Solutions

IndustryEducation Technology

Timeline4 Months

RegionAWS Mumbai (ap-south-1)

This case study details how Mist Avinya supported Franciscan Solutions in improving AWS cost visibility, governance, and forecasting accuracy through 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

Established a cross-functional framework integrating 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.

Franciscan Solutions Architecture Diagram — High-availability AWS architecture featuring EC2, DynamoDB, and centralized FinOps governance analytics.

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.