Skip to content

JeyaPrakashI/Multi-Cloud-Governance-Ledger-FOCUS-1.3

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

27 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

☁️ Multi-Cloud FOCUS 1.3 Governance Ledger 💰

Medium Article

Role Positioning: AI FinOps Lead | Platform Architect

Strategic Focus: Cost of Revenue (COR) Ownership & Automated Accountability

📌 Executive Summary

This project demonstrates a unified cloud financial ecosystem that normalizes billing data from AWS, Azure, and Snowflake into a single source of truth. Using the FOCUS 1.3 Standard, it provides the "standardized and consistent reporting" required for enterprise-scale environments.

The engine features a proactive Financial Governance layer that triggers self-healing protocols (auto-shutdown) via Logic Apps to eliminate runaway spend in non-production environments.


📈 Dashboard & Performance

Project #2 Dashboard

Figure 1: Executive view of consolidated spend across three providers with real-time governance alerts.


🚦 Governance & Automation Logic

This framework enforces accountability by automating the response to budget variances:

  1. Threshold Detection: Azure Monitor identifies spend exceeding $0.80 (80% of budget).
  2. Webhook Trigger: An HTTP Webhook signal is sent to the orchestration layer.
  3. Self-Healing: A Logic App workflow deallocates Development VMs to halt spend immediately.
  4. Validation: The final cost is capped at $0.85, successfully preventing a major budget breach.

🛠️ Technical Architecture

  • Data Standard: FOCUS 1.3 (FinOps Open Cost & Usage Specification) for cross-cloud normalization.
  • Ingestion: Automated transformation of fragmented CSV/JSON billing exports.
  • Visualization: Power BI Executive Dashboard designed for VP Engineering/CFO reviews.
  • Automation: JSON-based Logic App workflow definitions for cloud resource management.

📊 Business Impact & Unit Economics

  • COR Isolation: Clearly separated Production spend ($317.15) from Experimental spend ($19.35) to protect gross margins.
  • Spend Transparency: Identified a 75.78% spend concentration in Snowflake, enabling targeted vendor negotiations.
  • Risk Mitigation: Implemented automated "guardrails" that eliminate 100% of runaway lab spend.

📁 Repository Structure

  • /Dashboard/: Power BI templates and UI assets.
  • /Data/: Sample FOCUS 1.3 normalized datasets for AWS, Azure, and Snowflake.
  • /Automation/: Logic-App-Workflow.json and governance policy definitions.
  • /scripts/: [PROPRIETARY] Multi-cloud normalization engine logic (See generate_master_ledger.py for logic overview).

Note on Proprietary Logic: To protect intellectual property, the functional Python source code for the normalization engine is restricted. A high-level logic overview is provided within the scripts directory. Functional walkthroughs are available upon request during the interview process.


🔗 Links & References


Releases

No releases published

Packages

 
 
 

Contributors

Languages