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: 30-72% vs On-Demand
Term: 1 or 3 years
Payment: All/Partial/No upfront
Flexibility: Standard or Convertible

Savings Plans

Compute Savings Plans: 66% savings
EC2 Instance Savings Plans: 72% savings
Applies to: EC2, Fargate, Lambda
Flexible across: Instance families, regions, OS

Spot Instances

Savings: Up to 90% vs On-Demand
Best for: Batch jobs, CI/CD, stateless workloads
Risk: 2-minute interruption notice
Strategy: Mix with On-Demand for resilience

S3 Cost Optimization

resource "aws_s3_bucket_lifecycle_configuration" "example" {
  bucket = aws_s3_bucket.example.id

  rule {
    id     = "transition-to-ia"
    status = "Enabled"

    transition {
      days          = 30
      storage_class = "STANDARD_IA"
    }

    transition {
      days          = 90
      storage_class = "GLACIER"
    }

    expiration {
      days = 365
    }
  }
}

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