Migrating workloads to AWS Graviton instances with minimal disruption
Ready to slash your AWS compute costs by up to 40% while boosting performance? Migrating to AWS Graviton instances offers exactly that opportunity, but the transition requires careful planning to avoid compatibility pitfalls and service disruptions.
AWS Graviton processors, built on ARM-based architecture, deliver significant price-performance improvements over traditional x86 instances. However, many organizations hesitate to make the switch due to concerns about application compatibility, migration complexity, and potential downtime. The good news? With the right approach, you can migrate your workloads systematically while maintaining service continuity.
Think of Graviton migration like renovating your house while living in it—you need a phased approach that maintains essential functions while upgrading the underlying infrastructure. The key lies in understanding which rooms (workloads) to tackle first and how to minimize disruption during the transition.
Understanding AWS Graviton migration benefits
Before diving into the migration process, it’s crucial to understand why organizations are making this transition. Graviton4 instances demonstrate 12% performance gains over Graviton3 and an impressive 73% improvement over Graviton2 in video encoding workloads, according to AWS’s latest benchmarks.
The financial benefits are equally compelling. Organizations typically see:
- 30-40% cost reduction in compute expenses
- 20-25% performance improvements in memory-intensive workloads
- Enhanced energy efficiency compared to x86 architectures
Hykell has helped numerous clients achieve these benefits, with one global logistics company reducing compute costs by 30% while improving performance by 25% after migrating from C5 to C7g instances. Similarly, companies like Scoro have doubled their compute savings post-migration, demonstrating the tangible impact of strategic Graviton adoption.
The energy efficiency gains deserve special attention—ARM architecture processors consume significantly less power than their x86 counterparts while delivering comparable or superior performance. This translates to both cost savings and improved sustainability metrics for your organization.
Step-by-step migration methodology
Phase 1: Assessment and planning
Start by conducting a comprehensive workload assessment using AWS’s 4-step framework. This involves:
Inventory your current infrastructure: Document all EC2 instances, their configurations, and dependencies. The AWS Cost Optimization Hub provides centralized recommendations and ROI modeling to analyze historical usage patterns and identify prime candidates for migration.
Evaluate compatibility requirements: Not all applications are immediately compatible with ARM architecture. Focus on:
- Operating system compatibility (Amazon Linux 2, Ubuntu, CentOS support ARM)
- Application dependencies and third-party libraries
- Container images and their base architectures
- Database compatibility for managed services
Consider this phase similar to conducting a home inspection before renovation—you need to understand what’s working, what needs updating, and what potential issues might arise.
Prioritize workloads: Begin with stateless applications, development environments, and new deployments. These typically require minimal modification and offer the lowest risk. Development teams often find this approach builds confidence and expertise before tackling production workloads.
Phase 2: Environment preparation
Set up testing infrastructure: Create dedicated Graviton instances in your development environment. Use multi-architecture Auto Scaling Groups (ASGs) to test both x86 and ARM instances simultaneously, allowing direct performance comparisons.
Prepare your deployment tools: Update your Infrastructure as Code (IaC) templates:
- Modify AWS CloudFormation templates to support multiple architectures
- Update AWS CDK configurations for ARM compatibility
- Configure CI/CD pipelines to build multi-architecture container images
The AWS Graviton2 Runner provides an excellent testing environment for validating compatibility before production deployment.
Phase 3: Application optimization
Language and runtime considerations: Most modern applications work seamlessly on Graviton, but verification is essential:
- Python and Java applications typically run without modification, but test all dependencies thoroughly
- .NET applications are explicitly supported with specific optimization guides available
- Node.js, Go, and Rust generally work out-of-the-box on ARM
Container migration: If you’re using containerized workloads, rebuild your images for ARM64 architecture. Use Docker’s buildx functionality to create multi-platform images that support both x86 and ARM. This approach enables gradual rollouts while maintaining fallback options.
Address legacy dependencies: Some applications may rely on x86-specific binaries or libraries. The AWS Graviton transition guide provides strategies for handling these scenarios, including emulation options for critical legacy components.
Phase 4: Deployment and monitoring
Implement gradual rollout strategies: Use canary or blue-green deployment patterns to minimize risk:
- Deploy to a small percentage of traffic initially (5-10%)
- Monitor performance metrics closely using AWS CloudWatch
- Gradually increase traffic to Graviton instances (25%, 50%, 75%)
- Complete the migration once confidence is established
Performance tuning: Monitor key metrics during and after migration:
- CPU utilization patterns (ARM processors often show different usage characteristics)
- Memory throughput improvements
- Network performance changes
- Application response times and latency distributions
Think of this phase like a soft opening for a restaurant—you start with limited capacity to ensure everything works smoothly before opening fully to the public.
Compatibility considerations and common challenges
Programming language support
Fully supported languages: Python, Java, Node.js, Go, Rust, and .NET all have mature ARM64 support. Most applications written in these languages require minimal or no code changes. However, testing remains crucial—while the runtime may work perfectly, specific libraries or dependencies might have compatibility issues.
Potential compatibility issues: Legacy applications with compiled binaries, specific x86 assembly code, or older versions of runtime environments may require additional work. Create an inventory of these components early in your assessment phase.
Dependency management
Third-party libraries: Verify that all external dependencies support ARM64. Popular package managers (npm, pip, Maven) typically handle architecture differences automatically, but custom or proprietary libraries may need attention. Maintain a compatibility matrix to track testing results.
System-level dependencies: Some system utilities or monitoring agents may lack ARM64 versions. Plan alternative solutions or updated versions during your assessment phase. This is particularly important for security tools and performance monitoring agents.
Database considerations
AWS managed database services like RDS, DynamoDB, and ElastiCache work seamlessly with Graviton instances. However, self-managed databases may require specific ARM64 builds or configuration adjustments. Plan database migrations carefully, as they often represent the most critical components of your infrastructure.
Best practices for successful migration
Infrastructure optimization
Leverage Graviton-optimized AMIs: Use Amazon-provided AMIs specifically optimized for Graviton processors. These include performance tuning and ARM-specific optimizations out of the box, eliminating much of the manual configuration work.
Implement automated scaling: Configure Auto Scaling Groups with mixed instance types during transition periods. This allows you to maintain capacity while gradually shifting to Graviton instances. The Hykell FinOps Toolkit can automate many of these scaling decisions based on performance metrics.
Storage optimization: Consider pairing Graviton migration with EBS optimization. Upgrading from gp2 to gp3 volumes can provide additional performance and cost benefits alongside the Graviton transition. The combination often yields compounding savings and performance improvements.
Monitoring and validation
Establish baseline metrics: Document current performance metrics before migration. This enables accurate comparison and validates the benefits of your transition. Pay particular attention to application-specific KPIs, not just infrastructure metrics.
Use AWS CloudWatch extensively: Monitor CPU utilization, memory consumption, and application-specific metrics. Set up alarms for any performance degradation during the migration process. Create dashboards that compare x86 and ARM performance side-by-side during the transition.
Implement comprehensive testing: Beyond functional testing, conduct performance and load testing to ensure applications perform optimally on the new architecture. Use synthetic transaction monitoring to catch subtle performance changes that might not appear in basic health checks.
Cost optimization strategies
Right-size instances: Graviton instances often provide better performance at lower costs, but you may be able to downsize instance types while maintaining performance. Use this opportunity to optimize your instance sizing across your entire fleet.
Monitor cost impact: Track your AWS costs closely during migration using tools like the AWS Cost Optimization Hub. Document savings achieved and use this data to inform future migration decisions for remaining workloads.
Optimize beyond compute: The migration presents an opportunity to review and optimize other AWS services. Consider consolidating data transfer, optimizing storage classes, and reviewing reserved instance commitments.
Real-world migration outcomes
Organizations working with Hykell’s specialized Graviton migration services consistently achieve significant results. Beyond the logistics company mentioned earlier, a fintech client processing real-time financial data achieved 35% cost savings and 20% better memory throughput by migrating from R5 to R7g instances.
These post-migration OTT platform performance improvements demonstrate that careful planning and execution can deliver both cost and performance benefits simultaneously. The key success factor across all these cases was the methodical approach—starting with non-critical workloads, building expertise, and then applying lessons learned to production systems.
One particularly interesting case involved a media company processing thousands of video encoding jobs daily. After migrating to Graviton4 instances, they saw the dramatic 73% performance improvement over their previous Graviton2 setup, while simultaneously reducing costs by 35%.
Addressing common migration concerns
“Will my Python applications work on Graviton?” Yes, Python applications typically run seamlessly on Graviton instances. The Python runtime and most popular packages support ARM64 architecture without modification. However, always test your specific dependency stack, as some native extensions or specialized libraries may require ARM64 versions.
“Can Linux run on Graviton?” Absolutely. Amazon Linux 2, Ubuntu, CentOS, and other major distributions fully support ARM64 architecture and are optimized for Graviton processors. In fact, many distributions perform better on ARM due to architectural optimizations.
“Is the migration worth the effort?” For most workloads, the 30-40% cost savings and performance improvements justify the migration effort. Start with low-risk applications to gain experience before tackling more complex workloads. The learning curve is typically gentle, and the benefits compound over time.
“What about our legacy applications?” Legacy applications present the biggest challenge, but solutions exist. You can maintain x86 instances for truly incompatible workloads while migrating everything else. Often, this hybrid approach still delivers significant overall savings.
Planning your migration timeline
A typical Graviton migration follows this timeline:
Weeks 1-2: Workload assessment and compatibility analysis using the AWS transition guide
Weeks 3-4: Infrastructure preparation and testing environment setup
Weeks 5-8: Application testing and optimization
Weeks 9-12: Gradual production migration with monitoring
Large enterprises may extend this timeline, while smaller organizations with simpler architectures often complete migrations more quickly. The timeline heavily depends on the complexity of your dependency graph and the number of custom applications requiring testing.
Consider building buffer time for unexpected compatibility issues—while most applications migrate smoothly, discovering a critical dependency that lacks ARM64 support can add weeks to your timeline if not planned for.
Ready to reduce your AWS costs by up to 40% through strategic Graviton migration? The combination of careful planning, systematic testing, and gradual rollout ensures successful transitions with minimal business disruption. Whether you’re managing compute-heavy workloads or memory-intensive applications, Graviton instances offer compelling advantages that justify the migration investment.
Start with your least critical workloads to build confidence and expertise, then expand to production systems as your team becomes comfortable with the ARM architecture. With proper execution, your organization can join the growing number of companies achieving significant cost savings while improving application performance through AWS Graviton adoption. Contact Hykell to explore how automated optimization tools can accelerate your migration timeline and maximize your cost savings potential.