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:

• 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

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

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