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:

• 1-year: 20-40%
• 3-year: 40-72%

When to Use: Workloads with consistent, predictable usage

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 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

# 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