Sold by: Aokumo Inc.Â
Optimize your AI/ML workloads on Amazon EKS with specialized AWS infrastructure configurations, resource management, and workflow automation to improve model training speed by 60% and reduce infrastructure costs by 40%.
Overview
Aokumo's AI/ML Workload Optimization for Amazon EKS helps organizations maximize the performance and cost efficiency of their machine learning operations on AWS. Our solution addresses the unique challenges of running AI/ML workloads in containerized environments on AWS, including EC2 instance selection, Amazon SageMaker integration, GPU utilization, and ML workflow orchestration.
Our AWS-certified experts analyze your current AI/ML infrastructure and workloads to identify opportunities for optimization within your AWS environment. We implement specialized configurations for compute-intensive tasks using Amazon EC2 P4d/P3 instances, design efficient EKS node groups for various ML workload types, and optimize resource allocation to maximize GPU utilization and minimize AWS costs.
The implementation includes Amazon EKS-based Kubeflow deployment, ML pipeline automation with AWS Step Functions, distributed training configurations with Amazon SageMaker, and model serving optimization using AWS Inferentia. Our approach has helped organizations improve model training speed by 60%, reduce AWS infrastructure costs by 40%, and create a more streamlined ML experience that takes full advantage of AWS's purpose-built ML infrastructure.
Highlights
- Specialized Amazon EKS configuration for AI/ML workloads with optimized EC2 instance selection, GPU sharing mechanisms on AWS Nitro instances, and EKS node group design to improve training speed by 60% and reduce infrastructure costs by 40%.
- End-to-end ML platform implementation on Amazon EKS using Kubeflow and AWS services (SageMaker, Step Functions, S3) with automated pipelines for model training, validation, and deployment to streamline the entire ML lifecycle.
- Performance tuning for distributed AI/ML workloads, including Amazon EC2 GPU instance optimization, AWS Enhanced Networking configuration, and efficient data access patterns with Amazon FSx for Lustre to accelerate training and inference.
Details
Sold by
Categories
Delivery method
Deployed on AWS
Unlock automation with AI agent solutions
Fast-track AI initiatives with agents, tools, and solutions from AWS Partners.
Pricing
Custom pricing options
Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Resources
Vendor resources
Support
Vendor support
Email: sales@aokumo.ioÂ
Service delivery by ML platform specialists with deep Kubernetes expertise. Implementation typically spans 4-6 weeks depending on complexity. Includes assessment workshop, architecture design, implementation, performance tuning, and knowledge transfer. Post-implementation support and optimization guidance included.