--- name: williamzujkowski/Cloud Cost Optimization Analyzer source: https://app.decimal.ai/s/williamzujkowski-cloud-cost-optimization-analyzer@1/SKILL.md source_sha256: 83af7e62eb0b --- ## Purpose & When-To-Use **Primary trigger conditions:** - Monthly cloud bill shows unexpected increase (>10% variance) - Budget alert fired indicating overspend - Regular cost optimization review cycle (quarterly FinOps practice) - Pre-budget planning phase requires accurate TCO estimates - Executive request for cloud cost reduction initiatives - Migration to cloud requires cost modeling - Reserved instance or savings plan renewal decision needed **When NOT to use this skill:** - Real-time cost tracking (use native dashboards instead) - One-time spot instance pricing lookup (use pricing calculators) - Architecture design phase (use cloud-aws-architect first) **Value proposition:** Identifies 30-40% of typical cloud waste through systematic analysis of rightsizing, commitment discounts, and idle resources using FinOps principles. ## Pre-Checks **Required inputs validation:** ```python NOW_ET = "2025-10-25T22:42:30-04:00" assert cloud_provider in ["aws", "azure", "gcp", "multi"], "Invalid cloud provider" assert cost_data_source is not None, "Cost data source required" assert time_range in ["7d", "30d", "90d"] or matches_custom_format(time_range) assert len(optimization_targets) > 0, "At least one optimization target required" # Data freshness check if cost_data_age > 24h: warn("Cost data is stale; recommendations may be outdated") # Minimum data volume check if time_range == "7d" and total_resources < 10: suggest("Use 30d+ range for better trend analysis") ``` **Authority checks:** - AWS: Cost Explorer API enabled, `ce:GetCostAndUsage` permission - Azure: Cost Management API access, Reader role on subscriptions - GCP: Cloud Billing API enabled, `billing.accounts.getSpendingInformation` permission **Source citations (accessed 2025-10-25T22:42:30-04:00):** - AWS Cost Management: https://aws.amazon.com/aws-cost-management/ - Azure Cost Optimization: https://azure.microsoft.com/solutions/cost-optimization/ - GCP Cost Management: https://cloud.google.com/cost-management - FinOps Framework: https://www.finops.org/framework/ - FinOps Principles: https://www.finops.org/framework/principles/ ## Procedure ### Tier 1 (≤2k tokens): Quick Cost Health Check **Goal:** Identify top 3 cost optimization opportunities in <5 minutes. **Steps:** 1. **Fetch cost summary** for specified time_range - Group by service/resource type - Calculate total spend and trend (% change from previous period) 2. **Quick waste scan** (top offenders only) - Stopped instances still attached to storage - Unattached EBS volumes / Azure managed disks / GCP persistent disks - Unused Elastic IPs / Public IPs / Static external IPs - Load balancers with zero traffic (last 7 days) 3. **Commitment coverage check** - Calculate % of compute spend covered by reserved instances / savings plans / committed use discounts - If <60% coverage → flag as optimization opportunity 4. **Output quick wins** (3 highest impact items) - Example: "Delete 15 unattached EBS volumes → save $450/month" - Example: "Purchase EC2 Savings Plan (3-year) → save $2,400/month" - Example: "Rightsize 8 over-provisioned RDS instances → save $1,200/month" **Token budget checkpoint:** ~1.5k tokens for API calls, analysis, and output formatting. ### Tier 2 (≤6k tokens): Comprehensive Cost Analysis **Goal:** Generate detailed, actionable cost optimization plan with quantified savings. **Extends T1 with:** 5. **Rightsizing analysis** - Fetch CloudWatch / Azure Monitor / GCP Monitoring metrics (CPU, memory, network utilization) - Identify resources with <20% utilization over 90th percentile - Recommend downsizing (example: m5.2xlarge → m5.xlarge saves $150/month) - Calculate savings per resource: `(current_price - recommended_price) * hours_per_month` 6. **Reserved instance / Savings plan optimization** - Analyze historical usage patterns (30d minimum, 90d preferred) - Identify stable workloads eligible for commitments - Calculate break-even point: `upfront_cost / monthly_savings` - Recommend commitment term (1-year vs 3-year) based on usage stability - **AWS:** Compare Compute Savings Plans vs EC2 RIs vs convertible RIs - **Azure:** Compare Reserved VM Instances vs Azure Hybrid Benefit - **GCP:** Compare Committed Use Discounts (CUD) vs Sustained Use Discounts (SUD) 7. **Storage optimization** - Identify candidates for lifecycle policies (hot → cool → archive) - **AWS S3:** Recommend Intelligent-Tiering or S3 Glacier transitions - **Azure Blob:** Recommend tiering to Cool or Archive - **GCP Cloud Storage:** Recommend Nearline or Coldline classes - Calculate savings: `(current_storage_cost - optimized_cost) * TB_stored` 8. **Network cost optimization** - Identify cross-region / cross-AZ traffic (expensive) - Recommend VPC endpoints / Private Link to avoid NAT gateway costs - Flag public internet egress (most expensive path) 9. **Cost anomaly detection** - Calculate baseline spend (average + 2 std deviations) - Flag spikes >20% above baseline - Attribute anomaly to specific service/resource 10. **FinOps maturity assessment** (basic) - Tag compliance: % resources with required cost allocation tags - Budget variance: actual vs budgeted spend - Commitment utilization: % of purchased RI/SP actually used - Waste ratio: idle_cost / total_cost **Authority sources (accessed 2025-10-25T22:42:30-04:00):** - AWS Reserved Instances: https://aws.amazon.com/ec2/pricing/reserved-instances/ - AWS Savings Plans: https://aws.amazon.com/savingsplans/ (up to 72% savings) - Azure Reserved Instances: https://learn.microsoft.com/azure/cost-management-billing/reservations/ - Azure Hybrid Benefit: https://azure.microsoft.com/pricing/hybrid-benefit/ (up to 36% for Windows Server) - GCP Committed Use Discounts: https://cloud.google.com/compute/docs/instances/committed-use-discounts-overview - FinOps "Crawl, Walk, Run" maturity: https://www.finops.org/framework/ **Output:** JSON report with sections: cost_summary, quick_wins (T1), rightsizing_recommendations, commitment_recommendations, storage_optimization, network_optimization, anomalies, finops_maturity_score. **Token budget checkpoint:** ~5k tokens (includes T1 + extended analysis + detailed output). ### Tier 3 (not implemented for T2 skill) Reserved for future enhancements: predictive cost forecasting, ML-based anomaly detection, multi-account/org-wide consolidation, custom FinOps policies. ## Decision Rules **When to abort:** - Cost data source returns 403/401 → insufficient permissions; emit setup instructions - Cost data empty or <7 days → insufficient data for analysis - All optimization targets already at maximum efficiency (rare) → report "no action needed" **Ambiguity thresholds:** - **Rightsizing confidence:** Only recommend if utilization <20% for 90% of time period (avoids false positives from bursty workloads) - **Commitment recommendations:** Require 90d minimum history AND <10% variance in daily usage to recommend 3-year term - **Anomaly detection:** Only flag if >20% deviation AND >$100 absolute difference (avoid noise) **Prioritization logic:** 1. **Highest ROI first:** `savings_per_month / implementation_effort` - Effort scale: Low (delete unused) < Medium (rightsize) < High (migrate architecture) 2. **Quick wins:** Zero-downtime changes (stop unused, delete orphaned) rank highest 3. **Risk-adjusted:** Downsizing production workloads requires manual approval; rank lower **FinOps principle application (accessed 2025-10-25T22:42:30-04:00):** Per FinOps Foundation principles (https://www.finops.org/framework/principles/): - **"Everyone takes ownership":** Tag all recommendations with owning team/project via cost allocation tags - **"Centralized optimization":** Reserved instance / savings plan purchases centralized; this skill generates recommendations for central FinOps team - **"Variable cost model as opportunity":** Emphasize autoscaling and spot instances as cost-saving strategies ## Output Contract **Schema (JSON):** ```json { "cost_analysis_report": { "period": "2025-09-25 to 2025-10-25", "cloud_provider": "aws", "total_spend": 47500.32, "waste_identified": 14250.10, "savings_potential": { "monthly": 12800.00, "annual": 153600.00, "percentage": 26.9 } }, "quick_wins": [ { "category": "unused_resources", "description": "Delete 12 unattached EBS volumes", "monthly_savings": 360.00, "implementation_effort": "low", "risk_level": "none" } ], "rightsizing_recommendations": [ { "resource_id": "i-0a1b2c3d4e5f6g7h8", "resource_type": "ec2_instance", "current_type": "m5.2xlarge", "recommended_type": "m5.xlarge", "utilization_avg": 18.5, "monthly_savings": 150.00, "confidence": "high" } ], "commitment_recommendations": [ { "service": "ec2_compute", "plan_type": "compute_savings_plan", "term": "3_year", "upfront": "partial", "monthly_commitment": 5000.00, "monthly_savings": 1200.00, "break_even_months": 4.2 } ], "waste_inventory": [ { "resource_id": "vol-0123456789abcdef", "type": "ebs_volume_unattached", "idle_days": 45, "monthly_cost": 30.00 } ], "action_plan": [ { "priority": 1, "action": "Delete unused resources", "impact": "high", "effort": "low", "items_count": 27, "monthly_savings": 810.00 } ] } ``` **Required fields:** cost_analysis_report (with total_spend, savings_potential), action_plan (prioritized). **Optional fields:** rightsizing_recommendations, commitment_recommendations (only if applicable). ## Examples ```yaml # Example: AWS cost optimization for over-provisioned workload input: cloud_provider: aws cost_data_source: cost_explorer_api optimization_targets: [compute, storage, network] budget_constraints: monthly_budget: 50000 alert_threshold: 0.90 time_range: 90d output: cost_analysis_report: total_spend: 47500.32 waste_identified: 14250.10 savings_potential: monthly: 12800 annual: 153600 percentage: 26.9 quick_wins: - category: unused_resources description: Delete 12 unattached EBS volumes monthly_savings: 360 rightsizing_recommendations: - resource_id: i-0a1b2c3d4e5f current_type: m5.2xlarge recommended_type: m5.xlarge utilization_avg: 18.5 monthly_savings: 150 ``` ## Quality Gates **Token budgets (enforced):** - **T1**: ≤2,000 tokens - quick health check with top 3 cost optimization opportunities - **T2**: ≤6,000 tokens - comprehensive analysis with rightsizing, commitments, storage optimization, anomalies, and FinOps maturity - **T3**: (not implemented) - reserved for predictive cost forecasting, ML-based anomaly detection, multi-account consolidation **Accuracy requirements:** - Cost calculations must match cloud provider billing (±2% tolerance) - Rightsizing recommendations validated against 90th percentile utilization metrics - Commitment savings verified against current pricing (as of NOW_ET) **Safety constraints:** - **No automatic resource deletion:** All recommendations require human approval - **Production safeguards:** Flag production resources; require elevated approval for changes - **Audit trail:** Log all API calls and recommendations with timestamps **Auditability:** - Cite source for all pricing data (AWS Pricing API, Azure Rate Card, GCP Pricing Calculator) - Include confidence scores for probabilistic recommendations (rightsizing, anomalies) - Record baseline metrics used for comparisons **Determinism:** - Same inputs + same cost data → same recommendations - Cost anomaly thresholds configurable (default: 20% deviation, $100 minimum) ## Resources **Official cloud provider documentation:** - AWS Cost Optimization Hub: https://docs.aws.amazon.com/cost-optimization-hub/ - AWS Trusted Advisor: https://aws.amazon.com/premiumsupport/technology/trusted-advisor/ - AWS Cost Explorer: https://aws.amazon.com/aws-cost-management/aws-cost-explorer/ - Azure Cost Management: https://learn.microsoft.com/azure/cost-management-billing/ - Azure Advisor: https://learn.microsoft.com/azure/advisor/advisor-cost-recommendations - GCP Recommender: https://cloud.google.com/recommender/docs - GCP Cloud Billing: https://cloud.google.com/billing/docs **FinOps Foundation resources:** - FinOps Framework: https://www.finops.org/framework/ - FinOps Principles (6 core tenets): https://www.finops.org/framework/principles/ - FinOps Maturity Model: https://www.finops.org/framework/maturity-model/ - FinOps Personas: https://www.finops.org/framework/personas/ **Third-party cost optimization guides:** - Cloud cost optimization best practices 2025: https://www.cloudzero.com/blog/aws-cost-management-best-practices/ (accessed 2025-10-25T22:42:30-04:00) - Azure cost optimization tactics: https://cast.ai/blog/azure-cost-optimization/ (accessed 2025-10-25T22:42:30-04:00) - GCP cost optimization tools: https://www.cloudzero.com/blog/gcp-cost-optimization-tools/ (accessed 2025-10-25T22:42:30-04:00) **Related skills:** - `cloud-aws-architect`: For architecture-level cost optimization during design phase - `devops-pipeline-architect`: For CI/CD cost optimization (ephemeral environments) - `cloud-native-deployment-orchestrator`: For Kubernetes cost optimization (cluster rightsizing)