Reducing AWS Costs With Graviton-Powered Kubernetes
A phased Graviton migration helped a US automotive platform reduce infrastructure costs while supporting flexible, multi-architecture Kubernetes workloads.
At a Glance
A Kubernetes and AWS optimization initiative enabled multi-architecture workloads, improved infrastructure flexibility, and reduced compute costs.
Industry
Automotive
Function
Cloud Engineering & DevOps
Solution
Graviton-Powered Kubernetes
Engagement
AWS Infrastructure Optimization
The Client
The client is a US-based used car dealership with a nationwide buyer network. Its platform simplifies the vehicle-selling process through price prediction, real-time bids, buyer coordination, logistics, and settlement management.
The Challenges
Moving Kubernetes Workloads to Graviton Without Disruption
The client wanted to adopt AWS Graviton while maintaining application availability, deployment flexibility, and compatibility with existing workloads.
Rising Compute Costs
Growing Kubernetes workloads increased infrastructure expenses, while most applications continued running on x86_64 nodes.
Migration Risk
Workloads needed to transition to Graviton nodes without affecting application availability or the user experience.
Legacy Architecture
Existing applications were built primarily for x86_64, limiting compatibility with alternative CPU architectures.
Limited Multi-Architecture Support
Container images and deployment workflows were not prepared to support both x86_64 and Graviton environments.
CI/CD Pipeline Gaps
Existing pipelines lacked the capabilities required to build and deploy multi-platform container images.
Cost and Performance Balance
The migration needed to reduce infrastructure costs without compromising application performance or reliability.
Modernize Kubernetes Infrastructure Without Disrupting Operations
Move workloads to more efficient cloud infrastructure while maintaining application performance, deployment flexibility, and service availability.
The Solution
Enabling Flexible Kubernetes Workloads With Graviton
Maruti Techlabs developed a phased migration strategy to introduce Graviton-powered Kubernetes nodes while supporting the client's existing x86_64 workloads.
Workloads were gradually moved to Graviton-powered Kubernetes nodes to reduce compute costs while minimizing disruption.
Workloads were gradually moved to Graviton-powered Kubernetes nodes to reduce compute costs while minimizing disruption.
The Journey
x86 to Graviton
Business Outcomes
Cost-Efficient Infrastructure With Faster Deployments
15% Lower Infrastructure Costs
Moving workloads to Graviton-powered nodes reduced overall infrastructure costs.
Zero-Downtime Migration
Applications transitioned to the new architecture without service interruptions.
Dual Architecture Support
Workloads could run on both x86_64 and Graviton architectures based on requirements.
Faster Deployments
Updated CI/CD pipelines improved the speed and reliability of multi-architecture deployments.
Greater Developer Flexibility
Teams could switch between architectures during testing and rollout.
Improved Infrastructure Efficiency
Graviton adoption provided a more cost-efficient foundation for growing Kubernetes workloads.
Conclusion
The Graviton migration delivered cost savings while improving infrastructure flexibility and deployment capabilities.
Tech Stack
Build a More Efficient Kubernetes Environment
Optimize cloud infrastructure with modern compute architectures and flexible deployment workflows built around your application requirements.
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Frequently Asked Questions
AWS introduced Graviton to reduce compute costs, improve infrastructure efficiency, and provide an alternative CPU architecture for Kubernetes workloads.
The team updated container images to support both x86_64 and Graviton architectures, allowing applications to run across both environments.
The team migrated workloads gradually using a phased approach, validating each workload before broader adoption.
The pipelines were updated to support multi-platform container image creation and deployments across different CPU architectures.
Yes. The solution maintained support for both x86_64 and Graviton, allowing developers to switch architectures when required.