cost-optimization

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:

1. Review 30-day metrics (CPU, memory, DTU utilization)
2. Identify resources with < 40% average utilization
3. 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-pricing skill 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)
: £146/month
: £146/month (50%)
: 4 hours (testing + validation)
: Medium (test performance after change)
:
 Validate scaling limits in lower SKU
 Scale down during low-traffic window
 Monitor performance for 48 hours
 Rollback if issues detected


: S3 (100 DTU) - Avg DTU: 35%
: £300/month
: S1 (20 DTU) with auto-scaling to S2
: £120/month (avg)
: £180/month (60%)
: 1 day (testing + validation)
: Medium (requires performance testing)

---




: 2x Standardv3 VMs (pay-as-you-go)
: £280/month per VM = £560/month
: 1-year reserved instance
: £392/month (2 VMs)
: £168/month (30%)
: 30 minutes (purchase reservation)
: Low (production VMs run continuously)
: 1 year


: Pay-as-you-go
: £300/month
: 1-year reserved capacity
: £210/month
: £90/month (30%)
: 15 minutes
: 1 year

---




: Provisioned 1000 RU/s (24/7)
: £58/month
: Serverless (pay-per-request)
: £20/month (estimated based on usage patterns)
: £38/month (65%)
: 1 week (code changes + testing)
: Medium (requires application changes)


: 2TB in Hot tier
: £40/month
: Hot (30 days) → Cool (90 days) → Archive
: £22/month
: £18/month (45%)
: 4 hours (policy setup)
: Low (automated)

---




 Delete unattached disks [£80/month]
 Configure auto-shutdown for dev VMs [£300/month]
 : £380


 Downsize App Service Plan [£146/month]
 Optimize SQL Database DTU [£180/month]
 : £326


 Purchase VM Reserved Instances [£168/month]
 Purchase SQL Reserved Capacity [£90/month]
 : £258


 Migrate to Serverless Cosmos DB [£38/month]
 Implement Storage Lifecycle [£18/month]
 : £56

---



| 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 |

: £1,680/month (from £2,700)
: £12,240 (38% reduction)

---




 Monthly budget: £1,800 (10% buffer)
 Alert at 50%, 80%, 90%, 100%
 Auto-notification to team leads

Environment: Production | Staging | Development CostCenter: IT-12345 Project: ProjectName Owner: [e-mail]

### 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