Amazon EC2 – Consider Using a Preferred Instance Type

Organizations frequently deploy Amazon EC2 instances without carefully considering the most cost-effective and performance-optimized instance types. This policy ensures that machine types are restricted to meet your organization’s specific requirements, driving both cost efficiency and operational performance.

Detailed Explanation

Why This Policy Matters

Selecting the right EC2 instance type is crucial for:

• Cost optimization
• Performance efficiency
• Resource alignment
• Predictable cloud spending

Cost Reduction Potential

Implementing a strategic instance type selection can lead to significant cost savings:

• Potential savings range: 20-40% of compute infrastructure expenses
• Annual impact: Can reduce cloud spending by tens to hundreds of thousands of dollars for medium to large organizations

Cost Savings Examples

1. Small Workload (10 instances)
   • Switching from r5.2xlarge to r5.large
   • Estimated annual savings: $24,000
   • Reduced monthly cost from $2,000 to $800 per instance
2. Medium Enterprise (50 instances)
   • Optimizing instance families across development environments
   • Potential annual savings: $120,000 to $200,000

Implementation Guide

Infrastructure-as-Code Restricting Instance Types Example (Terraform)

variable "allowed_instance_types" {
  type    = list(string)
  default = [
    "t3.medium",
    "c5.large",
    "m5.xlarge"
  ]
}

resource "aws_instance" "example" {
  # Enforce allowed instance types
  instance_type = contains(var.allowed_instance_types, var.selected_instance_type)
    ? var.selected_instance_type
    : var.allowed_instance_types[0]
}

Manual Implementation Steps

1. Inventory Current Instances
   • Document all existing EC2 instance types
   • Analyze current usage patterns
   • Identify over-provisioned or under-utilized instances
2. Define Organizational Standards
   • Create a whitelist of approved instance types
   • Consider factors like:
     • Performance requirements
     • Cost constraints
     • Workload characteristics
3. Implement Controls
   • Use AWS Service Control Policies (SCPs)
   • Configure AWS Config rules
   • Leverage Infracost to prevent and identify non-compliant instances before deployment

Best Practices

• Right-size instances regularly
• Use AWS Cost Explorer for recommendations
• Leverage reserved instances for stable workloads
• Implement automated monitoring

Example Scenarios

Scenario 1: Development Environment

• Before: Random instance type selection
• After: Standardized t3.medium instances
• Result: 35% cost reduction, improved predictability

Scenario 2: Production Workloads

• Challenge: Performance-critical applications
• Solution: Carefully selected compute-optimized instances
• Outcome: Better performance, controlled costs

Considerations and Caveats

Potential Limitations:

• Some specialized workloads might require specific instance types
• Performance testing may be necessary
• Migration costs should be evaluated

Frequently Asked Questions (FAQs)