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    ML Provisioner Starter - Automated MLOps Infrastructure on AWS

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    Deployed on AWS
    Starter MLOps infrastructure on AWS. Model Registry, CodePipeline, CodeBuild, CodeCommit. CloudFormation. Docker-based.

    Overview

    ML Provisioner Starter by Axon Tech Labs automates AWS MLOps pipeline infrastructure provisioning via CloudFormation - scaffolding SageMaker Model Registry, CodePipeline, CodeBuild, CodeCommit or S3 source control, and IAM roles from a single YAML configuration file. Build consistent ML pipeline environments in minutes rather than weeks.

    The Starter tier is designed for small teams and proof-of-concept projects. It includes a SageMaker Model Package Group, two CodeCommit repositories (model-build and model-deploy) or S3 as the pipeline source, CodeBuild projects for build and deploy stages, CodePipeline pipelines, and scoped IAM roles - all as a single CloudFormation stack.

    When your team grows or compliance requirements increase, upgrade to Professional for event-driven automation and monitoring, or Enterprise for VPC isolation, KMS encryption, and compliance controls - using the same tool, same workflow, and same config structure.

    Key Capabilities

    Safe Deployment Pipeline: Multi-stage validation with YAML schema checks, CloudFormation structural validation, and isolated test-deploy namespaces with random suffixes.

    Pre-Deployment Visibility: Generate CloudFormation Change Sets and HTML review reports for team sign-off before any changes touch live environments.

    Streamlined Lifecycle Orchestration: Manage the entire ML pipeline stack through a single interface - from generating CloudFormation templates to executing full resource tear-downs.

    12 Actions

    • validate-config - Validate YAML config against tier schema
    • list-products - List available tier templates
    • show-product - Display resources and SSM outputs for active tier
    • create-policy - Generate least-privilege IAM deployer policy
    • create-prov-template - Generate CloudFormation provisioning template
    • validate-prov-template - Validate template structure and references
    • create-review-report - Generate pre-deployment HTML review report
    • show-changes - Preview infrastructure changes via CloudFormation ChangeSet
    • check-drift - Detect drift on deployed stack resources
    • test-deploy - Deploy to isolated namespace with random suffix
    • deploy-product - Provision ML pipeline infrastructure stack
    • delete-product - Tear down stack and all associated resources

    How It Works

    1. Configure: Define your infrastructure in a YAML file - tier and source control
    2. Execute: Run the Docker container with your config and credentials mounted
    3. Review: Generate templates, IAM policies, and review reports before deploying
    4. Deploy: Provision to AWS via CloudFormation

    Highlights

    • Foundation ML Infrastructure - SageMaker Model Registry, CodePipeline, CodeBuild, CodeCommit repositories (model-build and model-deploy) or S3 source control, and scoped IAM roles. Everything a small team needs to start shipping ML models to production. 12 actions cover the full lifecycle from policy generation to stack teardown.
    • Visibility and Auditability - Generate pre-deployment HTML review reports for team sign-off. Preview infrastructure changes via CloudFormation Change Sets before touching live environments. Built-in drift detection identifies unauthorized manual changes.
    • Safe Deployment Pipeline - Multi-stage validation workflow with YAML schema checks, CloudFormation template validation, and isolated test deployments with random suffixes. Upgrade to Professional or Enterprise at any time using the same tool, same workflow, and same config structure.

    Details

    Delivery method

    Supported services

    Delivery option
    New delivery option 1ML Provisioner Starter Container Image

    Latest version

    Operating system
    Linux

    Deployed on AWS
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    Features and programs

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    Financing for AWS Marketplace purchases

    Pricing

    ML Provisioner Starter - Automated MLOps Infrastructure on AWS

     Info
    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.

    1-month contract (1)

     Info
    Dimension
    Description
    Cost/month
    ML Provisioner Starter License
    License for ML Provisioner Starter - Foundation MLOps pipeline infrastructure for small teams and proof-of-concept projects. CloudFormation. Docker-based.
    $499.00

    Vendor refund policy

    30-day money-back guarantee for monthly subscriptions. Pro-rated refunds for annual subscriptions cancelled within the first 30 days.

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    Legal

    Vendor terms and conditions

    Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .

    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.

    Usage information

     Info

    Delivery details

    New delivery option 1ML Provisioner Starter Container Image

    Supported services: Learn more 
    • Amazon ECS
    • Amazon EKS
    • Amazon ECS Anywhere
    • Amazon EKS Anywhere
    Container image

    Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.

    Version release notes

    Bug fix: resolved AttributeError when deploying with source_control: s3 configuration (s3_prefix attribute was missing from ALLOWED_ML_KEYS in config loader).

    Additional details

    Usage instructions

    Run the container to see all available actions and options:

    docker run --rm
    -v ~/.aws:/home/mluser/.aws:ro
    709825985650.dkr.ecr.us-east-1.amazonaws.com/axon-tech-labs/starter-ml-provisioner:1.0.0 --help

    Full documentation: https://docs.axontechlabs.com/ml/index.html 

    Support

    Vendor support

    Axon Tech Labs provides comprehensive support for ML Provisioner customers through email and documentation.

    Email Support

    • Address:
    • Response Time: Within 24 hours (business days)
    • Hours: Monday-Friday, 9 AM - 5 PM Pacific Time

    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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