Source: wshobson/agents Original Plugin: cloud-infrastructure
Cloud Cost Optimization
Strategies and patterns for optimizing cloud costs across AWS, Azure, and GCP.
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
HCL
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
- 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
Tagging Strategy
AWS Tagging
HCL
locals {
  common_tags = {
    Environment = "production"
    Project     = "my-project"
    CostCenter  = "engineering"
    Owner       = "team@example.com"
    ManagedBy   = "terraform"
  }
}
resource "aws_instance" "example" {
  ami           = "ami-12345678"
  instance_type = "t3.medium"
  tags = merge(
    local.common_tags,
    {
      Name = "web-server"
    }
  )
}
Reference: See references/tagging-standards.md
Cost Monitoring
Budget Alerts
HCL
# AWS Budget
resource "aws_budgets_budget" "monthly" {
  name              = "monthly-budget"
  budget_type       = "COST"
  limit_amount      = "1000"
  limit_unit        = "USD"
  time_period_start = "2024-01-01_00:00"
  time_unit         = "MONTHLY"
  notification {
    comparison_operator        = "GREATER_THAN"
    threshold                  = 80
    threshold_type            = "PERCENTAGE"
    notification_type         = "ACTUAL"
    subscriber_email_addresses = ["team@example.com"]
  }
}
Cost Anomaly Detection
- AWS Cost Anomaly Detection
- Azure Cost Management alerts
- GCP Budget alerts
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
Development: t3.small RDS
Staging: t3.large RDS
Production: r6g.2xlarge RDS with read replicas
Pattern 3: Multi-Tier Storage
Hot data: S3 Standard
Warm data: S3 Standard-IA (30 days)
Cold data: S3 Glacier (90 days)
Archive: S3 Deep Archive (365 days)
Pattern 4: Auto-Scaling
HCL
resource "aws_autoscaling_policy" "scale_up" {
  name                   = "scale-up"
  scaling_adjustment     = 2
  adjustment_type        = "ChangeInCapacity"
  cooldown              = 300
  autoscaling_group_name = aws_autoscaling_group.main.name
}
resource "aws_cloudwatch_metric_alarm" "cpu_high" {
  alarm_name          = "cpu-high"
  comparison_operator = "GreaterThanThreshold"
  evaluation_periods  = "2"
  metric_name         = "CPUUtilization"
  namespace           = "AWS/EC2"
  period              = "60"
  statistic           = "Average"
  threshold           = "80"
  alarm_actions       = [aws_autoscaling_policy.scale_up.arn]
}
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
- Multi-cloud: CloudHealth, Cloudability, Kubecost
Reference Files
- references/tagging-standards.md- Tagging conventions
- assets/cost-analysis-template.xlsx- Cost analysis spreadsheet
Related Skills
- terraform-module-library- For resource provisioning
- multi-cloud-architecture- For cloud selection