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    ML Provisioner Professional - Automated MLOps Infrastructure on AWS

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    Deployed on AWS
    Professional MLOps infrastructure on AWS. Event-driven, monitoring-ready, S3-backed. CloudFormation. Docker-based.

    Overview

    ML Provisioner Professional by Axon Tech Labs automates AWS MLOps pipeline infrastructure provisioning via CloudFormation - scaffolding SageMaker Model Registry, CodePipeline, CodeBuild, S3 artifacts bucket, EventBridge event-driven automation, CloudWatch monitoring dashboard, and IAM managed policies from a single YAML configuration file. Build production-grade ML environments in minutes rather than weeks.

    The Professional tier is designed for growing ML teams that need production-ready pipeline infrastructure with enhanced monitoring and event-driven automation. It includes an S3 artifacts bucket, an EventBridge rule that triggers the deploy pipeline when a model is approved in the SageMaker Model Registry, a CloudWatch dashboard for pipeline visibility, and IAM managed policies - all as a single CloudFormation stack.

    Deploy across multiple AWS accounts, environments, and regions with consistent results. Every step produces auditable artifacts for team visibility. For VPC isolation, KMS encryption, and compliance monitoring, see ML Provisioner Enterprise.

    Key Capabilities

    Event-Driven Model Deployment: Automatically trigger the deploy pipeline when a model is approved in SageMaker Model Registry via EventBridge - no manual execution required.

    Production Monitoring: A CloudWatch dashboard provides real-time visibility into pipeline execution status, build metrics, and deployment health.

    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.

    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

    • Production ML Infrastructure - SageMaker Model Registry, CodePipeline, CodeBuild, S3 artifacts bucket, EventBridge event-driven pipeline automation, CloudWatch monitoring dashboard, and IAM managed policies. 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 infrastruct
    • Event-Driven Model Deployment - Automatically trigger the deploy pipeline when a model is approved in the SageMaker Model Registry. The EventBridge rule routes the approval event directly to CodePipeline - no manual intervention required. Docker-based execution fits any CI/CD system.

    Details

    Delivery method

    Supported services

    Delivery option
    ML Provisioner Professional Container Image

    Latest version

    Operating system
    Linux

    Deployed on AWS
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    Pricing

    ML Provisioner Professional - Automated MLOps Infrastructure on AWS

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    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 Professional License
    License for ML Provisioner Professional - Production-ready MLOps pipeline infrastructure with event-driven automation, CloudWatch monitoring, and S3 artifacts. CloudFormation. Docker-based.
    $999.00

    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

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    Delivery details

    ML Provisioner Professional 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/professional-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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