Sold by: Axon Tech Labs
Deployed on AWS
Enterprise MLOps infrastructure on AWS. VPC-integrated, KMS-encrypted, compliance-ready. CloudFormation. Docker-based.
Overview
ML Provisioner Enterprise by Axon Tech Labs automates AWS MLOps pipeline infrastructure provisioning via CloudFormation - scaffolding SageMaker Model Registry, CodePipeline, CodeBuild, S3, EventBridge, KMS encryption, VPC endpoints, compliance monitoring, and IAM permission boundaries from a single YAML configuration file. Build compliant, VPC-integrated ML environments in minutes rather than weeks.
The Enterprise tier is designed for organizations with strict security, compliance, and network isolation requirements. It includes KMS Customer Managed Keys, four private VPC endpoints (SageMaker API, SageMaker Runtime, S3 Gateway, STS), a dedicated endpoint Security Group, CloudWatch compliance log group with metric filters and alarms, SNS security alerting, and IAM permission boundaries - all as a single CloudFormation stack.
Note: Enterprise tier requires a VPC before provisioning. VPC ID and subnet IDs can be supplied directly or resolved from AWS Systems Manager Parameter Store (recommended when using the Axon Tech Labs VPC Provisioner).
Key Capabilities
Enterprise-Grade Security and Compliance: KMS Customer Managed Keys, private VPC endpoints, CloudWatch compliance log group with metric filters, unauthorized API call and root account usage alarms, SNS security alerting, and IAM permission boundaries. No manual resource configuration required.
Continuous Compliance and Auditability: Built-in drift detection identifies unauthorized manual changes. Compliance logs and security alarms provide continuous monitoring. Every provisioner action generates an auditable log file.
Event-Driven Model Deployment: Automatically trigger the deploy pipeline when a model is approved in SageMaker Model Registry via EventBridge - no manual execution required.
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, source control, VPC integration mode, and alerts email
- 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
- Enterprise ML Infrastructure - SageMaker Model Registry, CodePipeline, CodeBuild, S3 artifacts bucket, EventBridge automation, KMS Customer Managed Key encryption, four private VPC endpoints (SageMaker API, SageMaker Runtime, S3 Gateway, STS), CloudWatch compliance log group with alarms, SNS security alerting, and IAM permission boundaries. 12 actions cover the full lifecycle from policy generation to stack teardown.
- Compliance and Auditability - Built-in drift detection identifies unauthorized manual changes to your deployed infrastructure. Compliance logs, metric filters, and CloudWatch alarms provide continuous security monitoring. Every provisioner action generates an auditable log file for team visibility.
- VPC-Isolated ML Pipelines - All ML traffic routed through private VPC endpoints - SageMaker, S3, and STS never traverse the public inter
Details
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Delivery method
Supported services
Delivery option
ML Provisioner Enterprise 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 Enterprise License | License for ML Provisioner Enterprise - Enterprise-grade MLOps pipeline infrastructure with VPC integration, KMS encryption, compliance monitoring, and permission boundaries. CloudFormation. Docker-based. | $2,499.00 |
Vendor refund policy
30-day money-back guarantee for monthly subscriptions. Pro-rated refunds for annual subscriptions cancelled within the first 30 days.
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) .
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Delivery details
ML Provisioner Enterprise 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/enterprise-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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