Identify and quantify cost savings across Azure subscriptions by analyzing actual costs,
utilization metrics, and generating actionable optimization recommendations. USE FOR:
optimize Azure costs, reduce Azure spending, reduce Azure expenses, analyze Azure costs,
find cost savings, generate cost optimization report, find orphaned resources, rightsize VMs,
cost analysis, reduce waste, Azure spending analysis, find unused resources, optimize Redis
costs. DO NOT USE FOR: deploying resources (use azure-deploy), general Azure diagnostics
(use azure-diagnostics), security issues (use azure-security)
Azure Cost Optimization Skill
Analyze Azure subscriptions to identify cost savings through orphaned resource cleanup, rightsizing, and optimization recommendations based on actual usage data.
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.
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
List all resources in the subscription using Azure MCP tools or CLI:
# 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):
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:
# 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:
# 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.
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.
