By name: cost-optimization description: Analyze Azure architectures for cost optimization opportunities, provide savings recommendations, and calculate ROI for improvements. metadata: author: Thomas Thornton version: "1.0.0" last-updated: "2026-05-19"
Cost Optimization Skill
Analyze Azure costs and identify optimization opportunities across compute, storage, networking, and data services. Provide actionable recommendations with savings estimates.
When to Use
- Review architecture costs and identify waste
- Optimize existing Azure deployments
- Right-size over-provisioned resources
- Implement reserved instances and savings plans
- Set up cost monitoring and alerts
- Reduce monthly Azure bills
Cost Optimization Categories
1. Right-Sizing
Adjust resource SKUs to match actual usage patterns.
Target Resources:
- Virtual Machines
- App Service Plans
- SQL Databases
- Cosmos DB throughput
- Azure Cache for Redis
Analysis Method:
- Review 30-day metrics (CPU, memory, DTU utilization)
- Identify resources with < 40% average utilization
- Recommend smaller SKU or scaling adjustments
Typical Savings: 30-50%
2. Reserved Instances & Savings Plans
Commit to 1-year or 3-year terms for predictable workloads.
Eligible Services:
- Virtual Machines
- App Service Plans
- Azure SQL Database
- Cosmos DB
- Azure Cache for Redis
Savings (typical ranges — always verify with the azure-pricing skill using price-type: Reservation):
- 1-year: 20-40%
- 3-year: 40-72%
When to Use: Workloads with consistent, predictable usage
To confirm exact RI rates: use tool_search_tool_regex with pattern pricing, then call the tool with price-type: Reservation and include-savings-plan: true for the specific SKU and region. Compare the returned retailPrice against the Consumption rate to calculate the actual saving percentage.
3. Auto-Scaling
Scale resources based on demand instead of static provisioning.
Applicable Services:
- App Service
- Virtual Machine Scale Sets
- Container Apps
- AKS node pools
- Cosmos DB autoscale
Typical Savings: 20-40% (eliminates idle capacity during off-peak)
4. Storage Tiering
Move infrequently accessed data to cheaper storage tiers.
Blob Storage Tiers:
- Hot: Frequent access (< 30 days old)
- Cool: Infrequent access (30-90 days), 50% cheaper
- Archive: Rare access (> 90 days), 90% cheaper
Implementation: Lifecycle management policies
Typical Savings: 50-90% on archived data
5. Eliminate Waste
Identify and remove unused resources.
Common Waste:
- Unattached disks
- Stopped (but not deallocated) VMs
- Orphaned public IPs
- Unused App Service Plans
- Old snapshots and backups
- Idle Load Balancers
Typical Savings: £200-2,000/month per environment
Cost Analysis Process
Step 0: Retrieve Live Pricing with Azure MCP Pricing Tool
Before estimating any costs, invoke the azure-pricing skill to fetch real retail prices.
First, use tool_search_tool_regex with pattern pricing to discover the exact tool name — do not hardcode it. Then call the tool with:
sku: <ARM SKU e.g. Standard_D4ds_v5>
service: <e.g. Virtual Machines, Azure Kubernetes Service>
region: <ARM region slug e.g. uksouth, eastus>
currency: GBP
price-type: Consumption # on-demand baseline
include-savings-plan: true # returns 1yr/3yr rates in nested array
Then follow up with price-type: Reservation to retrieve exact reserved instance rates.
Monthly cost formula: hourly_price × 730
Important: The tool requires a specific SKU or service name — do not call it with only a broad category (e.g. "Virtual Machines"). Confirm the SKU before calling.
Build a three-column cost table per resource:
| Resource | Pay-as-you-go | 1-yr Reserved | 3-yr Reserved |
|---|---|---|---|
| (data from pricing tool) |
Step 1: Gather Current Costs
Extract cost data from Azure Cost Management:
- Last 30-60 days of spending by resource
- Group by resource type and resource group
- Identify top 10 cost contributors
Step 2: Analyze Resource Utilization
For each major resource:
- Compute: Average CPU, memory utilization
- Database: DTU/vCore usage, storage growth
- Storage: Access patterns, growth rate
- Networking: Bandwidth usage, idle resources
Step 3: Identify Opportunities
Categorize findings:
- Quick Wins: < 1 hour, immediate savings (delete unused resources)
- Right-Sizing: < 1 day, 30-50% savings
- Reserved Instances: < 1 hour setup, 1-3 year commitment
- Architecture Changes: > 1 week, significant redesign
Step 4: Calculate ROI
For each recommendation:
- Current monthly cost
- Optimized monthly cost
- Monthly savings
- Implementation effort (hours)
- Break-even time
Output Format
Note: All cost figures in the template below are illustrative placeholders. Before populating any analysis, use the
azure-pricingskill to retrieve actual retail prices per SKU and region (currency: GBP by default). Never copy heuristic amounts into a real recommendation — always fetch live prices.
# Cost Optimization Analysis
**Architecture**: [Name]
**Current Monthly Cost**: £X,XXX
**Optimized Monthly Cost**: £X,XXX
**Potential Savings**: £XXX/month (XX%)
**Annual Savings**: £X,XXX
---
## Executive Summary
[2-3 sentences on current spending, biggest opportunities, recommended priorities]
---
## Current Cost Breakdown
| Category | Monthly Cost | % of Total |
|----------|-------------|------------|
| Compute | £1,200 | 45% |
| Database | £800 | 30% |
| Storage | £300 | 11% |
| Networking | £250 | 9% |
| Monitoring | £150 | 5% |
| **Total** | **£2,700** | **100%** |
---
## Optimization Opportunities
### Priority 1: Quick Wins (< 1 day effort)
#### Opportunity #1: Delete Unattached Disks
**Current Cost**: £80/month
**Savings**: £80/month (100%)
**Effort**: 30 minutes
**Risk**: Low (verify not needed)
**Action**:
1. Identify unattached disks: `az disk list --query "[?diskState=='Unattached']"`
2. Verify with team (ensure not needed)
3. Delete: `az disk delete --ids <disk-id>`
#### Opportunity #2: Stop Unused Dev/Test VMs After Hours
**Current Cost**: £500/month (VM running 24/7)
**Savings**: £300/month (60%)
**Effort**: 2 hours (automation script)
**Risk**: Low (dev environment)
**Action**: Auto-shutdown policy: 7 PM - 7 AM weekdays, all day weekends
---
### Priority 2: Right-Sizing (< 1 week effort)
#### Opportunity #3: Downsize App Service Plan
**Current**: P2v3 (2 cores, 8GB RAM) - Avg CPU: 20%, RAM: 35%
**Current Cost**: £292/month
**Recommended**: P1v3 (2 cores, 4GB RAM)
**Optimized Cost**: £146/month
**Savings**: £146/month (50%)
**Effort**: 4 hours (testing + validation)
**Risk**: Medium (test performance after change)
**Action**:
1. Validate scaling limits in lower SKU
2. Scale down during low-traffic window
3. Monitor performance for 48 hours
4. Rollback if issues detected
#### Opportunity #4: SQL Database DTU Optimization
**Current**: S3 (100 DTU) - Avg DTU: 35%
**Current Cost**: £300/month
**Recommended**: S1 (20 DTU) with auto-scaling to S2
**Optimized Cost**: £120/month (avg)
**Savings**: £180/month (60%)
**Effort**: 1 day (testing + validation)
**Risk**: Medium (requires performance testing)
---
### Priority 3: Commitment Savings (< 1 hour setup)
#### Opportunity #5: Reserved Instances for Production VMs
**Current**: 2x Standard_D4s_v3 VMs (pay-as-you-go)
**Current Cost**: £280/month per VM = £560/month
**Recommended**: 1-year reserved instance
**Optimized Cost**: £392/month (2 VMs)
**Savings**: £168/month (30%)
**Effort**: 30 minutes (purchase reservation)
**Risk**: Low (production VMs run continuously)
**Commitment**: 1 year
#### Opportunity #6: Azure SQL Reserved Capacity
**Current**: Pay-as-you-go
**Current Cost**: £300/month
**Recommended**: 1-year reserved capacity
**Optimized Cost**: £210/month
**Savings**: £90/month (30%)
**Effort**: 15 minutes
**Commitment**: 1 year
---
### Priority 4: Architecture Optimization (> 1 week)
#### Opportunity #7: Migrate to Serverless Cosmos DB
**Current**: Provisioned 1000 RU/s (24/7)
**Current Cost**: £58/month
**Recommended**: Serverless (pay-per-request)
**Optimized Cost**: £20/month (estimated based on usage patterns)
**Savings**: £38/month (65%)
**Effort**: 1 week (code changes + testing)
**Risk**: Medium (requires application changes)
#### Opportunity #8: Implement Storage Lifecycle Policies
**Current**: 2TB in Hot tier
**Current Cost**: £40/month
**Recommended**: Hot (30 days) → Cool (90 days) → Archive
**Optimized Cost**: £22/month
**Savings**: £18/month (45%)
**Effort**: 4 hours (policy setup)
**Risk**: Low (automated)
---
## Implementation Roadmap
### Month 1: Quick Wins
- Delete unattached disks [£80/month]
- Configure auto-shutdown for dev VMs [£300/month]
- **Month 1 Savings**: £380
### Month 2: Right-Sizing
- Downsize App Service Plan [£146/month]
- Optimize SQL Database DTU [£180/month]
- **Month 2 Savings**: £326
### Month 3: Commitment Savings
- Purchase VM Reserved Instances [£168/month]
- Purchase SQL Reserved Capacity [£90/month]
- **Month 3 Savings**: £258
### Months 4-6: Architecture Changes
- Migrate to Serverless Cosmos DB [£38/month]
- Implement Storage Lifecycle [£18/month]
- **Months 4-6 Savings**: £56
---
## Total Savings Summary
| Timeframe | Cumulative Monthly Savings | Annual Savings |
|-----------|---------------------------|----------------|
| Month 1 | £380 | £4,560 |
| Month 2 | £706 | £8,472 |
| Month 3 | £964 | £11,568 |
| Months 4-6 | £1,020/month | £12,240 |
**Final Optimized Cost**: £1,680/month (from £2,700)
**Total Annual Savings**: £12,240 (38% reduction)
---
## Cost Governance Recommendations
### 1. Set Up Budgets & Alerts
- Monthly budget: £1,800 (10% buffer)
- Alert at 50%, 80%, 90%, 100%
- Auto-notification to team leads
### 2. Tag Resources for Cost Allocation
Environment: Production | Staging | Development CostCenter: IT-12345 Project: ProjectName Owner: teamname@company.com
### 3. Regular Reviews
- Weekly: Review anomalies (via Cost Management)
- Monthly: Cost optimization review
- Quarterly: Reserved instance optimization
### 4. Enable Azure Advisor Recommendations
- Automatically flags optimization opportunities
- Cost, security, reliability, performance recommendations
---
## Conclusion
[Summary with total savings, timeline, and priorities]
Cost Optimization Best Practices
Start with Quick Wins: Delete unused resources first Monitor Before Changing: 30-day metrics for right-sizing decisions Test Performance: Validate after SKU changes Use Automation: Auto-shutdown, lifecycle policies, auto-scaling Set Budgets: Prevent surprise bills Tag Everything: Enable cost allocation and tracking Review Regularly: Monthly cost reviews catch drift Document Decisions: Why resources are sized as they are
Avoid: Blind right-sizing, skipping performance validation, ignoring monitoring, missing reservations