Graviton instances powered by AWS-designed ARM-based processors provide a cost-effective alternative to traditional x86 instances in Amazon OpenSearch deployments. By strategically selecting Graviton instances, organizations can achieve meaningful cost savings without compromising performance.
Why This Policy Matters
Cost Efficiency
- Up to 20% lower instance costs compared to equivalent x86 instances
- Direct reduction in cloud infrastructure expenses
- Consistent performance characteristics with traditional instances
Performance Considerations
- ARM-based Graviton processors offer comparable computational capabilities
- Optimized for cloud-native workloads
- Efficient processing for search and analytics environments
Potential Cost Savings
Comparative Instance Pricing Example
| Instance Type | Monthly Cost | Cost Difference |
|---|---|---|
| m5.xlarge.search | $160/month | Baseline |
| m6g.xlarge.search | $110/month | 31.25% savings |
Annual Potential Savings: Depending on cluster size and configuration, organizations could save thousands of dollars annually by adopting Graviton instances.
Implementation Guide
Infrastructure-as-Code Example (Terraform)
resource "aws_opensearch_domain" "example" {
# Before (x86 instance)
# instance_type = "m5.xlarge.search"
# After (Graviton instance)
instance_type = "m6g.xlarge.search"
}Manual Migration Steps
- Assess current OpenSearch cluster configuration
- Identify compatible Graviton instance types
- Plan maintenance window for migration
- Create snapshot of existing cluster
- Launch new Graviton-based cluster
- Migrate data and configurations
- Validate performance and functionality
- Decommission old cluster
Best Practices
- Staged Migration: Implement changes incrementally
- Performance Testing: Validate workload compatibility
- Monitoring: Track performance metrics during transition
- Cost Tracking: Compare pre and post-migration expenses
Recommended Tools
- Infracost: Identifies and estimates potential cost savings before implementation
- AWS Cost Explorer
- AWS Migration Hub
Example Scenarios
Scenario 1: Search-Heavy Workload
A media company running large OpenSearch clusters for log analytics could save approximately $50,000 annually by migrating to Graviton instances.
Scenario 2: Development Environment
A startup with multiple staging environments could reduce monthly infrastructure costs by 25-30% through strategic Graviton adoption.
Considerations and Caveats
Potential Limitations
- Some specialized workloads might require thorough testing
- Legacy applications with x86-specific dependencies
- Specific region availability of Graviton instances
Compatibility Checks
- Verify application compatibility
- Review performance requirements
- Consider incremental migration approach