Sold by: Axon Tech Labs
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
- Configure: Define your infrastructure in a YAML file - tier and source control
- Execute: Run the Docker container with your config and credentials mounted
- Review: Generate templates, IAM policies, and review reports before deploying
- 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
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Delivery method
Supported services
Delivery option
ML Provisioner Professional Container Image
Latest version
Operating system
Linux
Deployed on AWS
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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 |
|---|---|---|
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 |
Dimensions summary
This listing offers one pricing option: a license for ML Provisioner Professional, billed by unit under a contract. You pay per license unit, so your cost scales with the number of units you commit to. The license covers production-ready MLOps pipeline infrastructure that deploys through CloudFormation and runs from a Docker-based image. It includes event-driven automation, CloudWatch monitoring, and an S3 artifacts bucket. There are no separate usage add-ons or size-based tiers within this listing; you select the number of license units you need.
Top-of-mind questions for buyers
The license is granted per AWS account. One unit covers ML Provisioner Professional deployments within a single account. There is no template-sharing mechanism across accounts, so each account you deploy into needs its own license unit.
It deploys a SageMaker Model Registry, source control repository, CodeBuild, and CodePipeline for CI/CD. It also creates an S3 artifacts bucket, an EventBridge rule for automated deployment, a CloudWatch dashboard, and managed IAM policies. Everything deploys as a single CloudFormation stack from a Docker-based image.
No. This listing bills by license unit under a contract, not by usage. Deploying more pipelines, running automated deployments, or storing more artifacts does not change the license cost. Note that the AWS resources provisioned, such as SageMaker and S3, carry their own separate AWS charges.
docs.axontechlabs.com
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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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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
Resources
Vendor resources
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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