Cloud Cost Optimization

/cost-optimization

Systematically reduce cloud infrastructure spending across AWS, Azure, GCP, and OCI while maintaining performance and reliability. This is about the cloud bill, not product pricing: the user pastes a bill breakdown, Cost Explorer export, Terraform, or a description of their infrastructure; deliver a prioritized savings plan, rightsizing recommendations, and ready-to-apply config snippets as chat artifacts.

When to Use

• Reduce cloud spending
• Right-size resources
• Implement cost governance
• Optimize multi-cloud costs
• Meet budget constraints

Cost Optimization Framework

1. Visibility: cost allocation tags, cost management tools, budget alerts, cost dashboards.
2. Right-Sizing: analyze utilization, downsize over-provisioned resources, auto-scaling, remove idle resources.
3. Pricing Models: reserved capacity, spot/preemptible instances, savings plans, committed use discounts.
4. Architecture Optimization: managed services, caching, data transfer optimization, 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: up to 66% savings
EC2 Instance Savings Plans: up to 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: reuse Windows Server and SQL Server licenses, up to 80% savings combined with RI.
• Azure Advisor: right-size VMs, delete unused resources, reserved capacity and storage recommendations.

GCP Cost Optimization

• Committed Use Discounts: 1 or 3 year commitment, up to 57% savings, resource-based or spend-based.
• Sustained Use Discounts: automatic, up to 30% for long-running instances, no commitment.
• Preemptible VMs: up to 80% savings, 24-hour max runtime, best for batch workloads.

OCI Cost Optimization

• Flexible Shapes: scale OCPUs and memory independently, match sizing to workload demand.
• Commitments and Budgets: annual commitments for predictable spend, compartment-level budgets with alerts, OCI Cost Analysis forecasts.
• Preemptible Capacity: batch and ephemeral workloads, interruption-tolerant autoscaling groups, mix with standard capacity for critical services.

Tagging Strategy

locals {
  common_tags = {
    Environment = "production"
    Project     = "my-project"
    CostCenter  = "engineering"
    Owner       = "[email protected]"
    ManagedBy   = "terraform"
  }
}

resource "aws_instance" "example" {
  ami           = "ami-12345678"
  instance_type = "t3.medium"

  tags = merge(
    local.common_tags,
    {
      Name = "web-server"
    }
  )
}

See references/tagging-standards.md for the tagging standard.

Cost Monitoring

# 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 = ["[email protected]"]
  }
}

Anomaly detection: AWS Cost Anomaly Detection, Azure Cost Management alerts, GCP Budget alerts, OCI Budgets and Cost Analysis.

Architecture Patterns

1. Serverless First: Lambda/Functions for event-driven work; pay only for execution, no idle costs.
2. Right-Sized Databases: small instances in dev/staging, sized-with-replicas in production only.
3. Multi-Tier Storage: hot in Standard, warm in Standard-IA (30 days), cold in Glacier (90 days), archive in Deep Archive (365 days).
4. Auto-Scaling: scale on utilization alarms instead of provisioning for peak.

Cost Optimization Checklist

• Implement cost allocation tags
• Delete unused resources (EBS volumes, EIPs, snapshots)
• Right-size instances based on utilization
• Use reserved capacity for steady workloads
• Implement auto-scaling
• Optimize storage classes and lifecycle policies
• Enable cost anomaly detection and budget alerts
• Use spot/preemptible instances for interruption-tolerant work
• Optimize data transfer costs
• Review costs weekly

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

Usage

/cost-optimization $ARGUMENTS