# Azure cost optimization governance

## What people get wrong

- They chase potential savings before establishing cost visibility, ownership, and clean allocation.
- They buy reservations or savings plans before right-sizing and removing idle resources.
- They treat budgets as hard controls when they are primarily alerts and automation triggers.
- They add Advisor recommendation totals together even though recommendation datasets can overlap.
- They optimize one subscription while shared services, logs, networking, and commitments sit elsewhere.

## Officially grounded service shape

Microsoft Learn frames Cost Management as an ongoing organizational practice with planning, visibility, accountability, optimization, and iteration. Cost data can be analyzed through Cost Analysis, exports, APIs, budgets, tags, management groups, and dimensions. Advisor and Cost Optimization workbooks expose recommendations, while reservations and savings plans are rate-optimization tools that require stable usage and careful sequencing.

## Non-negotiable design rules

1. Establish cost scope, billing model, owners, and reporting dimensions before optimization.
2. Enforce allocation tags and reporting conventions where they drive accountability.
3. Use budgets and alerts with named response owners.
4. Remove waste and right-size before purchasing commitments.
5. Treat Advisor and workbook recommendations as leads, not orders.
6. Validate actual savings after implementation.
7. Require approval and rollback for any action that changes runtime state or financial commitment.

## Minimal safe implementation flow

1. Map billing/resource hierarchy and cost ownership.
2. Validate Cost Analysis views, exports, budgets, tags, dimensions, and alert recipients.
3. Build a sanitized top-cost and trend view by service, owner, environment, and region.
4. Review idle, oversized, scheduling, retention, and architecture opportunities.
5. Review rate optimization only after baseline usage is clean.
6. Turn recommendations into owner-approved work items with impact, rollback, and measurement.
7. Reconcile realized savings against actual cost data after the billing cycle.

## High-risk assumptions to kill

- Budgets alert; they do not inherently stop spend unless connected automation and ownership exist.
- Advisor recommendations are leads, not guaranteed savings, and recommendation totals can overlap or be operationally unsafe.
- Commitment purchases are dangerous before idle waste, rightsizing, and usage stability are proven.
- Tag coverage is not allocation quality if owners, environments, applications, or inherited tags are inconsistent.
- Cost exports and billing data can contain sensitive business context; do not request raw dumps in chat.

## Safe command/code verification targets

- Inspect budget definitions for scope, thresholds, forecast/actual triggers, recipients, action groups, and named response owner.
- Review export definitions and report pipelines for dataset type, destination, schedule, retention, sanitization, and downstream access controls.
- Check dashboards or queries for top services, owner/environment dimensions, amortized versus actual views, commitment utilization, and anomaly trends.
- Verify optimization tickets include expected impact, operational risk, approval, rollback, and post-billing-cycle measurement.
- Confirm reservation or savings-plan recommendations are backed by stable utilization windows and do not double-count rightsizing or deletion savings.

## Safe verification targets

- Budget thresholds, recipients, action groups, and runbook response.
- Cost exports: actual, amortized, FOCUS, price sheet, reservation, and recommendation datasets where appropriate.
- Top services, anomalous growth, idle resources, underutilized commitments, and log/storage retention.
- Tag coverage and allocation quality by owner/environment/application.
- Advisor recommendations with overlap and feasibility review.
- Before/after actuals for implemented optimizations.

## When to push back

Push back on savings guarantees, blind resource deletion, unowned recommendations, raw billing data requests, immediate commitment purchases, or optimization plans without measurement and rollback.

# MCP and evidence path for Azure cost optimization governance

Use Microsoft Learn documentation through the user's configured documentation MCP as the first grounding path for Azure service behavior. This file defines evidence boundaries; it must not imply that documentation proves the user's tenant, subscriptions, RBAC, quotas, billing agreement, deployed resources, or production readiness.

## Evidence ladder

1. `docs_only`: Microsoft Learn documentation and official architecture guidance. Use for documented behavior, caveats, and safe review criteria.
2. `sampled_read_only`: configured-environment evidence from read-only tools, if available and explicitly scoped. Use only for the sampled resource/time window.
3. `user_supplied`: sanitized outputs, IaC, diagrams, billing summaries, or metrics provided by the user. Treat as unverified unless independently checked.
4. `mutation_ready`: documentation plus current-state evidence plus explicit approval, blast-radius statement, and rollback path.

## Rules

- Do not expose environment-specific implementation details in committed docs or user-facing guidance.
- Do not ask for credentials, tokens, tenant identifiers, subscription identifiers, billing account identifiers, connection strings, private keys, customer data, or raw secrets.
- If current-state evidence was not sampled, say `not sampled`; do not imply it.
- If evidence is representative or partial, say so. A sample does not prove broad regional availability, billing accuracy, policy compliance, or production readiness.
- Prefer read-only evidence before mutation planning. Stop for approval before write operations.

## Final-answer evidence language

Use phrases like:

- "Based on Microsoft Learn documentation..."
- "Configured-environment evidence was not sampled in this review."
- "The following is an inference from the provided configuration, not proven live state."
- "This recommendation is mutation-ready only after explicit approval and rollback review."

# Official sources for Azure Cost Optimization Governor

Use Microsoft Learn documentation through the user's configured documentation MCP before recommending Azure cost optimizations. Documentation proves tool behavior and best practices; it does not prove the user's utilization, commitment coverage, budget ownership, or actual savings.

## Primary Microsoft Learn sources

| Source | Review implication |
| --- | --- |
| [How to optimize your cloud investment with Cost Management](https://learn.microsoft.com/en-us/azure/cost-management-billing/costs/cost-mgt-best-practices) | Use for planning, visibility, accountability, cost analysis, exports, budgets, APIs, savings plans, reservations, and iteration. |
| [What is Microsoft Cost Management](https://learn.microsoft.com/en-us/azure/cost-management-billing/costs/overview-cost-management) | Ground Cost Management capabilities and Advisor as first stop for optimization recommendations. |
| [Create and manage budgets](https://learn.microsoft.com/en-us/azure/cost-management-billing/costs/tutorial-acm-create-budgets) | Use for budget thresholds and alerting; budgets inform and automate actions, they are not hard spend caps. |
| [Create and manage Cost Management exports](https://learn.microsoft.com/en-us/azure/cost-management-billing/costs/tutorial-improved-exports) | Use for actual/amortized/FOCUS exports, price sheet, reservation, and recommendation datasets. |
| [Azure Advisor cost recommendations](https://learn.microsoft.com/en-us/azure/advisor/advisor-reference-cost-recommendations) | Use for recommendation classes and savings opportunities, but verify overlap and current utilization. |
| [Cost Optimization workbook](https://learn.microsoft.com/en-us/azure/advisor/advisor-workbook-cost-optimization) | Use for Advisor workbook-driven optimization across rate and usage recommendations. |
| [Savings plan recommendations](https://learn.microsoft.com/en-us/azure/cost-management-billing/savings-plan/purchase-recommendations) | Use for lookback, simulations, stale-data safeguards, and overcommitment risks. |
| [Decide between a savings plan and a reservation](https://learn.microsoft.com/en-us/azure/cost-management-billing/savings-plan/decide-between-savings-plan-reservation) | Use for right-size-first sequencing and commitment selection. |

## Source-grounding rules

- Do not promise savings; label them as potential until implemented and measured.
- Do not recommend commitments before waste removal and utilization stability checks.
- Do not treat budgets as enforcement unless action groups or automation are explicitly designed.
- Cost exports and cost data can contain sensitive business information; request sanitized summaries only.

# Safety checklist for Azure Cost Optimization Governor

## Non-negotiable gates

- Never ask for invoices, billing account identifiers, enrollment identifiers, tenant identifiers, subscription identifiers, customer names, or raw exported cost data containing sensitive business details.
- Do not recommend deleting, resizing, stopping, or changing commitments without owner, impact, rollback, and utilization evidence.
- Do not purchase or recommend purchase of reservations or savings plans until waste is removed and baseline usage is stable.
- Treat budgets as alerts/automation triggers, not guaranteed hard stops.
- Require explicit approval before budget automation, resource shutdown, rightsizing, commitment purchase, export creation, tag enforcement, or policy remediation.

## High-risk assumptions to kill

- "Advisor savings are additive." Recommendation datasets can overlap.
- "Potential savings equal realized savings." Realized savings require implementation and measurement.
- "Budgets prevent overruns." They notify and can trigger automation; spend can still accrue.
- "Commitments fix waste." Discounts reduce rates, not unused resources.
- "Tags are enough." Tags must be enforced, inherited where appropriate, and used by reporting owners.

## Evidence labels

- `docs_only`: Microsoft Learn guidance only.
- `cost_sample`: sanitized Cost Management/Advisor/export evidence reviewed.
- `owner_confirmed`: resource or cost center owner confirmed action scope.
- `savings_validated`: before/after actuals prove realized savings.
- `mutation_ready`: approval, impact, rollback, and monitoring are documented.

## Minimum safe evidence

- Scope, billing model, management group/subscription/resource-group boundaries, and reporting owners.
- Budget thresholds, alert recipients, action groups, and response runbook.
- Cost analysis views, exports, dimensions, tags, and chargeback model.
- Advisor recommendations with overlap analysis and owner review.
- Utilization history before rightsizing or commitment decisions.

# Workflow and output contract for Azure Cost Optimization Governor

## Minimal safe workflow

1. Classify the request: spend visibility, budget governance, tagging, exports, rightsizing, rate optimization, or optimization approval.
2. Ground the review in Microsoft Learn through the user's configured documentation MCP.
3. Establish scope and evidence: docs only, sanitized cost sample, Advisor recommendation, export schema, or owner-confirmed action.
4. Separate visibility gaps from savings opportunities.
5. Rank opportunities: waste removal, rightsizing, scheduling, storage/log retention, reservations, savings plans, and architecture changes.
6. For each action, require owner, blast radius, rollback, and measurement method.
7. Return potential savings carefully, never as guaranteed realized savings.

## Output contract

```markdown
## Verdict
<credible governance | conditional | high-risk | docs-only advisory>

## Evidence level
- Documentation: <sources used>
- Cost evidence: <cost_sample|owner_confirmed|not sampled>

## Findings
1. <finding> — Evidence: <docs_only|cost_sample|owner_confirmed|inference>

## Optimization backlog
| Priority | Action | Evidence needed | Risk | Owner |
| --- | --- | --- | --- | --- |

## Guardrails
- <budget/export/tag/policy control>

## Safe next actions
- <least-risk next step>
```

## Pushback triggers

Push back on unowned recommendations, immediate deletion, blind commitment purchases, unsanitized billing data, savings guarantees, or optimization plans without before/after measurement.