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FinOps Operating System

An open-source operating framework for FinOps teams.

This repository provides practical templates, playbooks, KPIs, governance models, reporting structures, and operational runbooks for running FinOps across AWS, Azure, GCP, Kubernetes, SaaS, data platforms, and AI workloads.

Purpose

FinOps teams need more than concepts. They need repeatable operating practices.

This repository helps teams:

  • Build a FinOps operating model
  • Define governance and accountability
  • Improve cloud cost visibility
  • Create showback and chargeback models
  • Track KPIs and business value
  • Manage commitments and optimization
  • Govern AI and GPU spend
  • Run executive cost reviews
  • Standardize anomaly response
  • Mature from crawl to walk to run

Repository Structure

Repository Structure

Strategy

Allocation

KPIs

AI FinOps

Optimization

Operations

Executive Reporting

Assessments


Roadmap

Version 1.0

Completed:

  • FinOps Charter
  • KPI Dictionary
  • AI FinOps Governance Framework
  • Showback and Chargeback Framework
  • AWS Cost Optimization Playbook
  • Cost Anomaly Management Runbook
  • Executive Reporting Template
  • FinOps Maturity Assessment

Planned

  • Operating Model
  • Azure Optimization Playbook
  • Kubernetes FinOps Framework
  • Forecasting Framework
  • Dashboard Library
  • SQL Library
  • Automation Library
  • SaaS FinOps Framework
  • Data Platform FinOps Framework

Version 1 Focus

Version 1 includes:

  • FinOps Charter
  • Operating Model
  • KPI Dictionary
  • AWS Optimization Playbook
  • Azure Optimization Playbook
  • AI FinOps Governance Framework
  • Chargeback Framework
  • Executive Monthly Review Template
  • Anomaly Management Runbook
  • FinOps Maturity Assessment

Audience

This repository is for:

  • FinOps practitioners
  • Cloud engineers
  • Cloud operations teams
  • Finance teams
  • Product owners
  • Engineering leaders
  • Technology executives

License

MIT License.

About

Open-source FinOps Operating System for AWS, Azure, GCP, Kubernetes, and AI workloads. Includes governance frameworks, cost allocation models, KPI libraries, FOCUS standards, optimization playbooks, dashboards, automation patterns, and real-world case studies.

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