AWS Graviton processors are transforming cloud economics. Powered by Arm architecture, they’re engineered to deliver:
- 💰 Lower costs – Graviton instances are 20-40% cheaper than x86-based equivalents, thanks to AWS’s custom silicon optimised for price-performance.
- ⚡ Better efficiency – Graviton excels in compute-intensive, memory-bound, and containerised workloads. With native support in services like Amazon ECS, Lambda, and RDS, it’s an obvious choice for many scenarios.
However, Graviton isn’t a universal fit. Here's why:
- 🤔 Software compatibility – Not all workloads are Arm-ready. Legacy applications or proprietary software built for x86 may require refactoring, re-compilation, or might not support Graviton at all.
- 🛠Workload-specific tuning – While many frameworks and languages (e.g., Python, Java, Node.js) support Graviton, unlocking its full potential often requires optimising your stack.
The path to Graviton adoption:
- Start small: Identify workloads where Graviton’s strengths align with your needs, such as stateless services, CI/CD pipelines, or batch processing jobs.
- Use AWS tools: AWS provides resources like the Graviton Challenge and the Porting Advisor for Graviton to analyse dependencies and identify changes needed for a smooth migration.
- Benchmark workloads: Run tests on Graviton instances (e.g., C7g, M7g, R7g). Use tools like AWS Compute Optimizer to assess performance improvements and cost savings.
- Iterate gradually: Adopt in phases, starting with non-critical services. Use blue/green deployments or canary releases to validate performance, scalability, and reliability.
By embracing Graviton, you can achieve significant cost savings while enhancing efficiency—without compromising scalability or security.
👉 Are you exploring Graviton for your workloads? Contact us below👇 for a no-obligations chat to help you get on your way.
