Sold by: Global Mobility Services
Deployed on AWS
AWS Free Tier
Deploy MLflow on AWS in Minutes. A secure, scalable MLOps platform built for data teams in biotech, finance, and AI startups. Automate infrastructure, centralize model tracking, and speed up ML delivery.
Overview
Get production-ready MLOps in just a few clicks.
This solution deploys MLflow on AWS with secure, autoscaling infrastructure - ideal for teams who need to manage machine learning models across dev, staging, and production environments without the overhead.
Built with AWS CloudFormation, it provisions EC2, RDS, and S3 with best practices for encryption, VPC isolation, and IAM policies.
Who is it for?
ML engineers at biotech or finance companies managing multiple model versions
Data scientists in regulated industries (HIPAA, SOC 2)
Startups scaling their AI teams without a dedicated MLOps function
What is included:
CloudFormation templates to deploy the full stack
Secure multi-tier VPC setup
Auto-scaling compute and storage
SSL, IAM roles, and logging
MLflow UI for experiment tracking
Need help getting started? Book a free walkthrough or get white-glove deployment support here: cloud@gmobility.com
Start deploying faster, tracking smarter, and scaling confidently with the MLflow MLOps Platform.
Highlights
- Deploy MLflow in Minutes: Instantly spin up secure, scalable ML environments on AWS using automated CloudFormation templates - no manual setup required.
- Enterprise-Grade Architecture: Includes multi-AZ high availability, IAM roles, SSL encryption, and a 3-tier VPC setup to meet compliance and uptime requirements.
- Let Your Data Scientists Focus: Eliminate DevOps overhead so teams can accelerate model development, tracking, and deployment with MLflow and AWS-native services.
Details
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Delivery method
Delivery option
Scalable MLOps: A Secure & Automated Platform
Latest version
Operating system
Debian 8/27/2024
Deployed on AWS
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Features and programs
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/month |
|---|---|---|
GMS MLOPS | Admin of GMS MLOPS AMI | $50.00 |
Dimensions summary
This listing offers one pricing dimension under a contract model. You pay for administrative access to the GMS MLOPS Amazon Machine Image (AMI), billed by the Units measure. There are no tiers, instance sizes, or usage add-ons to choose from. Pricing does not scale across multiple options. You commit to the single AMI-based deployment covered by the contract term shown in the pricing table.
Top-of-mind questions for buyers
One unit covers administrative access to the GMS MLOPS Amazon Machine Image (AMI). It grants admin rights to the deployed image under the contract. You are not billed per user, per node, or per model. The unit reflects the single AMI-based deployment you commit to.
The image supports data engineering for ML pipelines, including data ingestion, preprocessing, and model integration with scalable data pipelines. It also covers model deployment and monitoring, with built-in logging. These functions run within the single AMI-based deployment you administer under the contract.
No. The contract bills for administrative access to the single AMI, not for models run, data processed, or workload volume. There are no tiers or usage add-ons to trigger a cost change. Note that underlying AWS compute and storage from running the instance are billed separately by AWS.
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Vendor refund policy
no refund but contact for help
Legal
Vendor terms and conditions
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Content disclaimer
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Delivery details
Scalable MLOps: A Secure & Automated Platform
This AWS-based MLOps platform provides a scalable and automated foundation for managing machine learning operations. It includes EC2 instances for compute, VPC for secure networking, S3 for storage, RDS for backend and IAM for access control. The platform is designed to streamline deployment and operation of ML workloads using infrastructure-as-code principles via CloudFormation.
CloudFormation Template (CFT)
AWS CloudFormation templates are JSON or YAML-formatted text files that simplify provisioning and management on AWS. The templates describe the service or application architecture you want to deploy, and AWS CloudFormation uses those templates to provision and configure the required services (such as Amazon EC2 instances or Amazon RDS DB instances). The deployed application and associated resources are called a "stack."
Version release notes
Initial release of MLflow MLOps Platform with automated infrastructure setup, S3-based artifact storage, RDS PostgreSQL backend, and SSL-secured access via ACM integration.
Additional details
Usage instructions
- Launch the CloudFormation stack in your AWS Console.
- Configure parameters like IAM role, VPC, subnets, and domain name.
- After stack creation, access the MLflow tracking server using your domain name (e.g., https://mlops.example.com ).
- Log in with the provided credentials and start tracking your ML experiments.
Resources
Vendor resources
Support
Vendor support
- Basic: Email support (9 AM to 5 PM, Mon to Fri, 24 hr response), setup guidance, access to knowledge base, bug fixes, notifications for minor updates.
- Premium: 24/7 priority support (2 hr response), dedicated account manager, SLAs (99.9% uptime), custom configurations, proactive monitoring, updates. Please email cloud@gmobility.com for any questions and support for this product.
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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