cost-optimization

# 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. ```markdown # 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