Azure Virtual Machines – Consider Using a Preferred Instance Type

Optimize Azure VM costs by standardizing and selecting the most cost-effective instance types that meet your organization’s performance and budget requirements.

Why This Policy Matters

Organizations often overspend on cloud infrastructure by selecting virtual machine types without careful consideration. Azure offers numerous VM series and sizes, each with different pricing, performance characteristics, and optimization potential. By implementing a strategic approach to VM selection, businesses can:

• Reduce cloud spending
• Improve resource utilization
• Standardize infrastructure
• Simplify cloud management

Cost Optimization Strategy

Selecting the right Azure Virtual Machine instance type is crucial for balancing performance needs and cost efficiency. Each VM series (D-series, B-series, F-series, etc.) offers unique characteristics:

• General purpose VMs: Balanced CPU-to-memory ratio
• Compute-optimized VMs: Higher CPU-to-memory ratio
• Memory-optimized VMs: Higher memory-to-CPU ratio
• Storage-optimized VMs: High disk throughput and I/O
• GPU VMs: Specialized graphics and compute workloads

Potential Cost Savings

Example cost scenarios demonstrate significant potential savings:

1. Standard vs. Optimized Instance
   • Standard D2 v4 (8 vCPUs, 32GB RAM): $180/month
   • Optimized B4ms (4 vCPUs, 16GB RAM): $120/month
   • Potential Monthly Savings: $60 (33% reduction)
2. Reserved Instance Optimization
   • Pay-as-you-go pricing: $200/month
   • 1-year reserved instance: $136/month
   • Potential Annual Savings: $768

Implementation Guide

Infrastructure-as-Code Remediation Example (Terraform)

Before

resource "azurerm_virtual_machine" "example" {
  vm_size = "Standard_D16_v4"  # Large, expensive instance
  # Other configuration
}

After

resource "azurerm_virtual_machine" "example" {
  vm_size = "Standard_B4ms"    # More cost-effective
  # Other configuration
}

Manual Implementation Steps

1. Assess current VM workloads and performance requirements
2. Review Azure VM sizing recommendations
3. Use Azure Cost Management tools
4. Implement right-sizing strategies
5. Monitor performance metrics

Best Practices

• Regularly review VM usage
• Use Azure Advisor recommendations
• Implement tagging for cost tracking
• Consider reserved instances
• Use auto-scaling when possible

Recommended Tools

• Infracost: Scan infrastructure code for cost optimization opportunities
• Azure Cost Management
• Azure Advisor
• Azure Performance Diagnostics

Example Scenarios

Scenario 1: Development Environment

• Before: Large Standard_D16_v4 VM
• After: Smaller Standard_B4ms VM
• Result: 40% cost reduction without impacting performance

Scenario 2: Machine Learning Workloads

• Optimization: Switch from general-purpose to compute-optimized instances
• Savings: Reduced compute costs while maintaining performance

Considerations and Caveats

• Performance Requirements: Always prioritize application performance
• Workload Complexity: Some applications require specific VM characteristics
• Migration Effort: Changing VM types might require application reconfiguration
• Licensing Implications: Some software licenses are tied to specific VM configurations

Frequently Asked Questions (FAQs)