# Jongio Azd Copilot Azure Cost Optimization

> Azure Cost Optimization Skill

- Skill: `tomevault-io/jongio-azd-copilot-azure-cost-optimization` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/jongio-azd-copilot-azure-cost-optimization`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/jongio-azd-copilot-azure-cost-optimization/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/jongio-azd-copilot-azure-cost-optimization

---


# Azure Cost Optimization Skill

Analyze Azure subscriptions to identify cost savings through orphaned resource cleanup, rightsizing, and optimization recommendations based on actual usage data.

## When to Use This Skill

Use this skill when the user asks to:
- Optimize Azure costs or reduce spending
- Analyze Azure subscription for cost savings
- Generate cost optimization report
- Find orphaned or unused resources
- Rightsize Azure VMs, containers, or services
- Identify where they're overspending in Azure
- **Optimize Redis costs specifically** - See [Azure Redis Cost Optimization](./references/azure-redis.md) for Redis-specific analysis

## Instructions

Follow these steps in conversation with the user:

### Step 0: Validate Prerequisites

Before starting, verify these tools and permissions are available:

**Required Tools:**
- Azure CLI installed and authenticated (`az login`)
- Azure CLI extensions: `costmanagement`, `resource-graph`
- Azure Quick Review (azqr) installed - See [Azure Quick Review](./references/azure-quick-review.md) for details

**Required Permissions:**
- Cost Management Reader role
- Monitoring Reader role
- Reader role on subscription/resource group

**Verification commands:**
```powershell
az --version
az account show
az extension show --name costmanagement
azqr version
```

### Step 1: Load Best Practices

Get Azure cost optimization best practices to inform recommendations:

```javascript
// Use Azure MCP best practices tool
mcp_azure_mcp_get_azure_bestpractices({
  intent: "Get cost optimization best practices",
  command: "get_bestpractices",
  parameters: { resource: "cost-optimization", action: "all" }
})
```

### Step 1.5: Redis-Specific Analysis (Conditional)

**If the user specifically requests Redis cost optimization**, use the specialized Redis skill:

📋 **Reference**: [Azure Redis Cost Optimization](./references/azure-redis.md)

**When to use Redis-specific analysis:**
- User mentions "Redis", "Azure Cache for Redis", or "Azure Managed Redis"
- Focus is on Redis resource optimization, not general subscription analysis
- User wants Redis-specific recommendations (SKU downgrade, failed caches, etc.)

**Key capabilities:**
- Interactive subscription filtering (prefix, ID, or "all subscriptions")
- Redis-specific optimization rules (failed caches, oversized tiers, missing tags)
- Pre-built report templates for Redis cost analysis
- Uses `redis_list` command

**Report templates available:**
- [Subscription-level Redis summary](./templates/redis-subscription-level-report.md)
- [Detailed Redis cache analysis](./templates/redis-detailed-cache-analysis.md)

> **Note**: For general subscription-wide cost optimization (including Redis), continue with Step 2. For Redis-only focused analysis, follow the instructions in the Redis-specific reference document.
### Step 1.6: Choose Analysis Scope (for Redis-specific analysis)

**If performing Redis cost optimization**, ask the user to select their analysis scope:

**Prompt the user with these options:**
1. **Specific Subscription ID** - Analyze a single subscription
2. **Subscription Name** - Use display name instead of ID
3. **Subscription Prefix** - Analyze all subscriptions starting with a prefix (e.g., "CacheTeam")
4. **All My Subscriptions** - Scan all accessible subscriptions
5. **Tenant-wide** - Analyze entire organization

Wait for user response before proceeding to Step 2.

### Step 2: Run Azure Quick Review

Run azqr to find orphaned resources (immediate cost savings):

📋 **Reference**: [Azure Quick Review](./references/azure-quick-review.md) - Detailed instructions for running azqr scans

```javascript
// Use Azure MCP extension_azqr tool
extension_azqr({
  subscription: "<SUBSCRIPTION_ID>",
  "resource-group": "<RESOURCE_GROUP>"  // optional
})
```

**What to look for in azqr results:**
- Orphaned resources: unattached disks, unused NICs, idle NAT gateways
- Over-provisioned resources: excessive retention periods, oversized SKUs
- Missing cost tags: resources without proper cost allocation

> **Note**: The Azure Quick Review reference document includes instructions for creating filter configurations, saving output to the `output/` folder, and interpreting results for cost optimization.

### Step 3: Discover Resources

For efficient cross-subscription resource discovery, use Azure Resource Graph. See [Azure Resource Graph Queries](references/azure-resource-graph.md) for orphaned resource detection and cost optimization patterns.

List all resources in the subscription using Azure MCP tools or CLI:

```powershell
# Get subscription info
az account show

# List all resources
az resource list --subscription "<SUBSCRIPTION_ID>" --resource-group "<RESOURCE_GROUP>"

# Use MCP tools for specific services (preferred):
# - Storage accounts, Cosmos DB, Key Vaults: use Azure MCP tools
# - Redis caches: use mcp_azure_mcp_redis tool (see ./references/azure-redis.md)
# - Web apps, VMs, SQL: use az CLI commands
```

### Step 4: Query Actual Costs

Get actual cost data from Azure Cost Management API (last 30 days):

**Create cost query file:**

Create `temp/cost-query.json` with:
```json
{
  "type": "ActualCost",
  "timeframe": "Custom",
  "timePeriod": {
    "from": "<START_DATE>",  
    "to": "<END_DATE>"
  },
  "dataset": {
    "granularity": "None",
    "aggregation": {
      "totalCost": {
        "name": "Cost",
        "function": "Sum"
      }
    },
    "grouping": [
      {
        "type": "Dimension",
        "name": "ResourceId"
      }
    ]
  }
}
```

> **Action Required**: Calculate `<START_DATE>` (30 days ago) and `<END_DATE>` (today) in ISO 8601 format (e.g., `2025-11-03T00:00:00Z`).

**Execute cost query:**
```powershell
# Create temp folder
New-Item -ItemType Directory -Path "temp" -Force

# Query using REST API (more reliable than az costmanagement query)
az rest --method post `
  --url "https://management.azure.com/subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/Microsoft.CostManagement/query?api-version=2023-11-01" `
  --body '@temp/cost-query.json'
```

**Important:** Save the query results to `output/cost-query-result<timestamp>.json` for audit trail.

### Step 5: Validate Pricing

Fetch current pricing from official Azure pricing pages using `fetch_webpage`:

```javascript
// Validate pricing for key services
fetch_webpage({
  urls: ["https://azure.microsoft.com/en-us/pricing/details/container-apps/"],
  query: "pricing tiers and costs"
})
```

**Key services to validate:**
- Container Apps: https://azure.microsoft.com/pricing/details/container-apps/
- Virtual Machines: https://azure.microsoft.com/pricing/details/virtual-machines/
- App Service: https://azure.microsoft.com/pricing/details/app-service/
- Log Analytics: https://azure.microsoft.com/pricing/details/monitor/

> **Important**: Check for free tier allowances - many Azure services have generous free limits that may explain $0 costs.

### Step 6: Collect Utilization Metrics

Query Azure Monitor for utilization data (last 14 days) to support rightsizing recommendations:

```powershell
# Calculate dates for last 14 days
$startTime = (Get-Date).AddDays(-14).ToString("yyyy-MM-ddTHH:mm:ssZ")
$endTime = Get-Date -Format "yyyy-MM-ddTHH:mm:ssZ"

# VM CPU utilization
az monitor metrics list `
  --resource "<RESOURCE_ID>" `
  --metric "Percentage CPU" `
  --interval PT1H `
  --aggregation Average `
  --start-time $startTime `
  --end-time $endTime

# App Service Plan utilization
az monitor metrics list `
  --resource "<RESOURCE_ID>" `
  --metric "CpuTime,Requests" `
  --interval PT1H `
  --aggregation Total `
  --start-time $startTime `
  --end-time $endTime

# Storage capacity
az monitor metrics list `
  --resource "<RESOURCE_ID>" `
  --metric "UsedCapacity,BlobCount" `
  --interval PT1H `
  --aggregation Average `
  --start-time $startTime `
  --end-time $endTime
```

### Step 7: Generate Optimization Report

Create a comprehensive cost optimization report in the `output/` folder:

**Use the `create_file` tool** with path `output/costoptimizereport<YYYYMMDD_HHMMSS>.md`:

**Report Structure:**
```markdown
# Azure Cost Optimization Report
**Generated**: <timestamp>

## Executive Summary
- Total Monthly Cost: $X (💰 ACTUAL DATA)
- Top Cost Drivers: [List top 3 resources with Azure Portal links]

## Cost Breakdown
[Table with top 10 resources by cost, including Azure Portal links]

## Free Tier Analysis
[Resources operating within free tiers showing $0 cost]

## Orphaned Resources (Immediate Savings)
[From azqr - resources that can be deleted immediately]
- Resource name with Portal link - $X/month savings

## Optimization Recommendations

### Priority 1: High Impact, Low Risk
[Example: Delete orphaned resources]
- 💰 ACTUAL cost: $X/month
- 📊 ESTIMATED savings: $Y/month
- Commands to execute (with warnings)

### Priority 2: Medium Impact, Medium Risk
[Example: Rightsize VM from D4s_v5 to D2s_v5]
- 💰 ACTUAL baseline: D4s_v5, $X/month
- 📈 ACTUAL metrics: CPU 8%, Memory 30%
- 💵 VALIDATED pricing: D4s_v5 $Y/hr, D2s_v5 $Z/hr
- 📊 ESTIMATED savings: $S/month
- Commands to execute

### Priority 3: Long-term Optimization
[Example: Reserved Instances, Storage tiering]

## Total Estimated Savings
- Monthly: $X
- Annual: $Y

## Implementation Commands
[Safe commands with approval warnings]

## Validation Appendix

### Data Sources and Files
- **Cost Query Results**: `output/cost-query-result<timestamp>.json`
  - Raw cost data from Azure Cost Management API
  - Audit trail proving actual costs at report generation time
  - Keep for at least 12 months for historical comparison
  - Contains every resource's exact cost over the analysis period
- **Pricing Sources**: [Links to Azure pricing pages]
- **Free Tier Allowances**: [Applicable allowances]

> **Note**: The `temp/cost-query.json` file (if present) is a temporary query template and can be safely deleted. All permanent audit data is in the `output/` folder.
```

**Portal Link Format:**
```
https://portal.azure.com/#@<TENANT_ID>/resource/subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/<RESOURCE_PROVIDER>/<RESOURCE_TYPE>/<RESOURCE_NAME>/overview
```

### Step 8: Save Audit Trail

Save all cost query results for validation:

**Use the `create_file` tool** with path `output/cost-query-result<YYYYMMDD_HHMMSS>.json`:

```json
{
  "timestamp": "<ISO_8601>",
  "subscription": "<SUBSCRIPTION_ID>",
  "resourceGroup": "<RESOURCE_GROUP>",
  "queries": [
    {
      "queryType": "ActualCost",
      "timeframe": "MonthToDate",
      "query": { },
      "response": { }
    }
  ]
}
```

### Step 9: Clean Up Temporary Files

Remove temporary query files and folder after the report is generated:

```powershell
# Delete entire temp folder (no longer needed)
Remove-Item -Path "temp" -Recurse -Force -ErrorAction SilentlyContinue
```

> **Note**: The `temp/cost-query.json` file is only needed during API execution. The actual query and results are preserved in `output/cost-query-result*.json` for audit purposes.

## Output

The skill generates:
1. **Cost Optimization Report** (`output/costoptimizereport<timestamp>.md`)
   - Executive summary with total costs and top drivers
   - Detailed cost breakdown with Azure Portal links
   - Prioritized recommendations with actual data and estimated savings
   - Implementation commands with safety warnings

2. **Cost Query Results** (`output/cost-query-result<timestamp>.json`)
   - Audit trail of all cost queries and responses
   - Validation evidence for recommendations

## Important Notes

### Data Classification
- 💰 **ACTUAL DATA** = Retrieved from Azure Cost Management API
- 📈 **ACTUAL METRICS** = Retrieved from Azure Monitor
- 💵 **VALIDATED PRICING** = Retrieved from official Azure pricing pages
- 📊 **ESTIMATED SAVINGS** = Calculated based on actual data and validated pricing

### Best Practices
- Always query actual costs first - never estimate or assume
- Validate pricing from official sources - account for free tiers
- Use REST API for cost queries (more reliable than `az costmanagement query`)
- Save audit trail - include all queries and responses
- Include Azure Portal links for all resources
- Use UTF-8 encoding when creating report files
- For costs < $10/month, emphasize operational improvements over financial savings
- Never execute destructive operations without explicit approval

### Common Pitfalls
- **Assuming costs**: Always query actual data from Cost Management API
- **Ignoring free tiers**: Many services have generous allowances (e.g., Container Apps: 180K vCPU-sec free/month)
- **Using wrong date ranges**: 30 days for costs, 14 days for utilization
- **Broken Portal links**: Verify tenant ID and resource ID format
- **Cost query failures**: Use `az rest` with JSON body, not `az costmanagement query`

### Safety Requirements
- Get approval before deleting resources
- Test changes in non-production first
- Provide dry-run commands for validation
- Include rollback procedures
- Monitor impact after implementation

## SDK Quick References

- **Redis Management**: [.NET](references/sdk/azure-resource-manager-redis-dotnet.md)

---
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<!-- tomevault:4.0:skill_md:2026-04-13 -->