Cloud Cost Optimization
Strategies and patterns for optimizing cloud costs across AWS, Azure, GCP, and OCI.
Purpose
Implement systematic cost optimization strategies to reduce cloud spending while maintaining performance and reliability.
When to Use
- Reduce cloud spending
- Right-size resources
- Implement cost governance
- Optimize multi-cloud costs
- Meet budget constraints
Cost Optimization Framework
1. Visibility
- Implement cost allocation tags
- Use cloud cost management tools
- Set up budget alerts
- Create cost dashboards
2. Right-Sizing
- Analyze resource utilization
- Downsize over-provisioned resources
- Use auto-scaling
- Remove idle resources
3. Pricing Models
- Use reserved capacity
- Leverage spot/preemptible instances
- Implement savings plans
- Use committed use discounts
4. Architecture Optimization
- Use managed services
- Implement caching
- Optimize data transfer
- Use lifecycle policies
AWS Cost Optimization
Reserved Instances
Savings Plans
Spot Instances
S3 Cost Optimization
Azure Cost Optimization
Reserved VM Instances
- 1 or 3 year terms
- Up to 72% savings
- Flexible sizing
- Exchangeable
Azure Hybrid Benefit
- Use existing Windows Server licenses
- Up to 80% savings with RI
- Available for Windows and SQL Server
Azure Advisor Recommendations
- Right-size VMs
- Delete unused resources
- Use reserved capacity
- Optimize storage
GCP Cost Optimization
Committed Use Discounts
- 1 or 3 year commitment
- Up to 57% savings
- Applies to vCPUs and memory
- Resource-based or spend-based
Sustained Use Discounts
- Automatic discounts
- Up to 30% for running instances
- No commitment required
- Applies to Compute Engine, GKE
Preemptible VMs
- Up to 80% savings
- 24-hour maximum runtime
- Best for batch workloads
OCI Cost Optimization
Flexible Shapes
- Scale OCPUs and memory independently
- Match instance sizing to workload demand
- Reduce wasted capacity from fixed VM shapes
Commitments and Budgets
- Use annual commitments for predictable spend
- Set compartment-level budgets with alerts
- Track monthly forecasts with OCI Cost Analysis
Preemptible Capacity
- Use preemptible instances for batch and ephemeral workloads
- Keep interruption-tolerant autoscaling groups
- Mix with standard capacity for critical services
Tagging Strategy
AWS Tagging
Reference: See references/tagging-standards.md
Cost Monitoring
Budget Alerts
Cost Anomaly Detection
- AWS Cost Anomaly Detection
- Azure Cost Management alerts
- GCP Budget alerts
- OCI Budgets and Cost Analysis
Architecture Patterns
Pattern 1: Serverless First
- Use Lambda/Functions for event-driven
- Pay only for execution time
- Auto-scaling included
- No idle costs
Pattern 2: Right-Sized Databases
Pattern 3: Multi-Tier Storage
Pattern 4: Auto-Scaling
Cost Optimization Checklist
- Implement cost allocation tags
- Delete unused resources (EBS, EIPs, snapshots)
- Right-size instances based on utilization
- Use reserved capacity for steady workloads
- Implement auto-scaling
- Optimize storage classes
- Use lifecycle policies
- Enable cost anomaly detection
- Set budget alerts
- Review costs weekly
- Use spot/preemptible instances
- Optimize data transfer costs
- Implement caching layers
- Use managed services
- Monitor and optimize continuously
Tools
- AWS: Cost Explorer, Cost Anomaly Detection, Compute Optimizer
- Azure: Cost Management, Advisor
- GCP: Cost Management, Recommender
- OCI: Cost Analysis, Budgets, Cloud Advisor
- Multi-cloud: CloudHealth, Cloudability, Kubecost
Related Skills
terraform-module-library- For resource provisioningmulti-cloud-architecture- For cloud selection


