Sold by: Outerbounds
Deployed on AWS
Give your data scientists superpowers, approved by your engineers.
Overview
Design and develop all data science and ML/AI applications easily with open-source Metaflow. Execute and deploy them on scalable, enterprise-grade infrastructure powered by Outerbounds.
Highlights
- Managed High Availability: Outerbounds encapsulates years of experience and hard-earned lessons in managing demanding, business-critical ML and data workloads.
- Efficient Compute: At the core of Outerbounds is a scalable, cost-optimized, fully managed Kubernetes cluster that is specifically tuned for data-intensive batch workloads, including demanding GPU needs of modern AI.
- Secure & SOC2 Compliant: Security is in our DNA, not at the perimeter. No data or code ever leaves your account.
Details
Sold by
Delivery method
Deployed on AWS
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Outerbounds Platform | Platform access, onboarding and standard support | $60,000.00 |
Vendor refund policy
All fees are non-cancellable and non-refundable except as required by law
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
24 x 7 on-call support provided. support@outerbounds.co
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Workflow Orchestration Framework
Open-source Metaflow framework for designing and developing data science and ML/AI applications
Managed Kubernetes Infrastructure
Scalable, cost-optimized, fully managed Kubernetes cluster specifically tuned for data-intensive batch workloads and GPU-accelerated computing
High Availability Management
Enterprise-grade infrastructure with managed high availability for business-critical ML and data workloads
Data Isolation and Compliance
SOC2 compliant security architecture ensuring no data or code leaves the customer's account
GPU Compute Support
Native support for demanding GPU requirements of modern AI and machine learning workloads
GPU Container Provisioning
Spin up GPU-enabled containers in as little as one second with custom infrastructure for rapid iteration and scaling.
Autoscaling Capability
Automatically scale resources from zero to hundreds of GPUs and back down based on workload demands without manual infrastructure management.
Infrastructure as Code Deployment
Deploy Python functions to the cloud using infrastructure-as-code to define custom container images and hardware requirements.
Serverless Compute Architecture
Serverless compute platform that abstracts infrastructure management for ML inference, fine-tuning, and batch data processing workloads.
Pay-Per-Use Resource Billing
Resource-based billing model that charges only for the actual compute time consumed during workload execution.
Automated Deployment and Scaling
Full automation and auto-scaling capabilities for moving AI projects from proof-of-concept to production environments
Model Fine-tuning Capabilities
Support for responsible model customization using RAG (Retrieval-Augmented Generation) and RAFT techniques to improve model accuracy and performance
GPU Resource Optimization
Dynamic GPU resource provisioning with scaling capabilities to optimize resource utilization across different deployment environments
Governance and Monitoring
Built-in governance frameworks, guardrails and monitoring systems for managing ML and GenAI applications in production
Multi-environment Deployment
Support for deploying workloads across multiple environments including AWS GovCloud, on-premises and hybrid infrastructure configurations
Standard contract
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