For teams whose Amazon EC2, container or Lambda bill keeps rising: we check which workloads can run on Arm-based AWS Graviton, move them with minimal code changes and benchmark before and after, so the gain is measured, not assumed.
AWS Partner, Advanced Tier Services
AWS Graviton migration services move applications from x86-based compute to AWS Graviton, the Arm-based processors AWS designs for better price performance. HabileLabs, an AWS Advanced Tier Services Partner with the AWS Service Delivery validation for AWS Graviton, checks which Amazon EC2, Amazon ECS and AWS Lambda workloads are compatible, ports them with minimal code changes and benchmarks cost and performance before and after, for education, non-profit and enterprise teams.
Teams usually look at Graviton when one of these shows up in their bill or their roadmap:
Most of these come down to knowing which workloads will run well on Graviton and proving it with numbers from your own systems, and that is where we start.
What our Graviton clients gain, and the mechanism behind each.
Graviton instances with right-sized Auto Scaling replace x86 capacity sized for peaks. Prashant Foundation cut compute spend by up to 30–35%.
CI/CD pipelines that build for Arm make releases routine. Bhoj University cut release time 70% and held 99.9% uptime through admission and exam peaks.
Pre- and post-migration benchmarks of latency, throughput and cost show what changed for each workload, instead of relying on published averages.
Compatibility checks find the libraries and container images that need an Arm build before anything moves, so code changes stay minimal.
AWS designs Graviton processors to reduce energy consumption, so moving compute to them supports your sustainability goals.
Performance monitoring and cost tracking after the move keep the saving from drifting as workloads and traffic change.
From the first compatibility check to tracking cost after the move.
Performance profiling, dependency analysis and Arm compatibility checks across EC2, containers and Lambda, ranking workloads by fit and effort.
Graviton instance families chosen per workload, a migration roadmap and a performance validation plan agreed before work starts.
Workloads moved from x86-based EC2 instances to Graviton with AWS tools and custom automation scripts, keeping code changes minimal.
Arm builds added to your pipelines with AWS CodeBuild and CI/CD, plus Auto Scaling and custom monitoring dashboards for the new instances.
Latency, throughput and cost measured before and after migration, so each change is backed by numbers from your own workloads.
Continuous performance monitoring, cost tracking and support across Amazon EC2, Amazon ECS, Amazon EKS, AWS Lambda and Amazon RDS.
Four stages. Each workload is benchmarked before and after, so you see the result in numbers.
We profile your workloads, check dependencies and Arm compatibility, and pick the ones that stand to gain most from Graviton.
We choose Graviton instance families, set the migration roadmap and agree how performance will be validated.
We port workloads with AWS CodeBuild and automated CI/CD pipelines, then tune Auto Scaling and monitoring dashboards.
We compare pre- and post-migration benchmarks for performance and cost, then keep tracking both over time.
Client results on AWS
AWS Graviton is a family of Arm-based processors designed by AWS. It powers Graviton-based instance types on Amazon EC2 and can be used with Amazon ECS, Amazon EKS, AWS Lambda and Amazon RDS.
They cover a readiness assessment of your workloads, instance selection and a migration roadmap, porting from x86 to Arm, CI/CD changes for Arm builds, and benchmarks of performance and cost before and after. Ongoing monitoring and cost tracking keep the gains in place.
It depends on the workload. AWS's own figure is up to 40% better price performance than comparable x86-based instances, but your result depends on how your code runs on Arm. Prashant Foundation cut compute spend by up to 30–35% with Graviton and Auto Scaling, and we benchmark your workloads before you commit.
Often not. Code in interpreted or managed languages such as Python, Node.js and Java usually runs on Arm as it is, while compiled code and native libraries need an Arm build. Our compatibility checks find those before migration, so code changes stay minimal.
Workloads built on open-source stacks, containers, web and application servers, and Lambda functions are usually the easiest to move. Software that ships only x86 binaries, or depends on x86-specific libraries, needs more work or stays on x86. The readiness assessment sorts your workloads into these groups.
It depends on how many workloads you have and how much of your build pipeline needs Arm support. The assessment gives you a roadmap with the order and timing of each workload before any work starts.
Yes. Migrations usually run in stages, keeping x86 instances for software that cannot move yet. Mixed clusters and multi-architecture container images let both run in the same environment while benchmarks confirm each move.
AWS designs Graviton processors to reduce energy consumption, so moving compute to Graviton supports sustainability goals. The workloads keep running on the same AWS services, such as Amazon EC2, Amazon ECS and AWS Lambda.
Tell us what runs on Amazon EC2, containers or Lambda today. An AWS-certified architect will come back with the workloads that fit, the risks and a rough plan, whether or not we work together.
