Azure Cloud FinOps & Cost Optimization

Achieve up to 30% cloud cost reduction and strengthen financial accountability with EPAM’s Cloud FinOps & Cost Optimization Implementation. Designed for CIOs, cloud platform owners, FinOps practitioners, engineering leaders, and finance teams, this engagement resolves fragmented cost visibility, inefficient resource usage, inconsistent tagging, weak governance, and unclear cost ownership across Azure and multi‑cloud environments. EPAM combines FinOps governance, engineering guardrails, and data-driven optimization using Azure Cost Management, Microsoft Fabric, and Power BI to improve forecasting, allocation accuracy, and sustainable cost control.

What You Will Receive

• FinOps Maturity Assessment: Scoring across FinOps capabilities with strengths, gaps, quick wins, and a prioritized roadmap.
• Cost Optimization Assessment & Backlog: A quantified backlog across compute, storage, network, databases, and AI/ML with savings estimates.
• FinOps Operating Model & Governance: Roles, RACI, KPIs, tagging standards, budget/forecast processes, and chargeback/showback models.
• Cost Management Platform Blueprint: Architecture and setup guidance for a unified cost & usage platform (e.g., Fabric + Power BI).
• AI-Driven FinOps Enablement: Optional FinOps Copilot patterns with Azure OpenAI for automated insights and anomaly triage.
• Microsoft 365 Licensing Optimization: Identification of unused licenses and cost‑saving opportunities.
• Engineering Artifacts: Policy-as-code guardrails, tagging frameworks, automation scripts, dashboards, SOPs, and forecasting guidelines.
• Knowledge Transfer: Workshops, cost reviews, and a 3–12 month optimization roadmap.

Agenda (Typical 3–5 Week Implementation)

Week 1 — Discovery & Assessment

• Evaluate tagging, cost allocation, forecasting, governance, and reporting workflows.
• Analyze spend patterns, waste categories, anomalies, and reservation/savings plan coverage.
• Review data readiness across Azure Cost Management and identify reporting gaps.
• Define baselines and target KPIs (allocation accuracy, forecasting accuracy, discount coverage, cost‑reduction potential).

Week 2 — Optimization Assessment & Backlog

• Perform deep-dive optimization across compute, storage, network, DB, container, and AI/ML workloads.
• Create a quantified backlog with savings estimates and prioritization.
• Refine anomaly detection approach and tuning.
• Identify automation candidates (cleanup rules, right‑sizing, scheduling, archiving policies).

Week 3 — Operating Model, Governance & KPIs

• Define roles (Engineering, Finance, Product Owners) and RACI.
• Establish governance cadences, approval workflows, and accountability controls.
• Standardize tagging, taxonomy, and cost allocation models.
• Design dashboards for transparency, forecasting, unit economics, and KPI tracking.

Week 4 — Engineering Implementation (Optional)

• Deploy policy-as-code for tagging compliance, cost boundaries, and cleanup/right‑sizing.
• Configure budgets, alerts, and reservation/savings plan governance.
• Implement reporting pipelines and publish Power BI dashboards.
• Provide reusable scripts, automation templates, and runbooks.

Week 5 — Enablement, Documentation & Handover

• Deliver training for engineering, finance, and business teams.
• Provide final artifacts: optimization backlog, dashboards, governance documentation, SOPs, and KPI targets.
• Present a 3–12 month roadmap for continuous FinOps evolution.

Expected Outcomes

• Up to 30% cost reduction through prioritized optimization and automated guardrails.
• Up to 90% allocation accuracy via standardized tagging and governance.
• Up to 88% forecasting accuracy through improved data quality and dashboards.
• Up to 80% discount coverage through reservation/savings plan governance.
• Unified cloud cost visibility via Power BI and a scalable Microsoft Fabric-based data foundation.

EPAM’s Cloud FinOps & Cost Optimization Implementation provides the governance, operating model, engineering guardrails, and actionable artifacts needed to reduce waste, improve predictability, and sustain long‑term cloud financial discipline.