Sold by: Axon Tech Labs
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
- 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
- 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
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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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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 Starter License | License for ML Provisioner Starter - Foundation MLOps pipeline infrastructure for small teams and proof-of-concept projects. CloudFormation. Docker-based. | $499.00 |
Dimensions summary
This listing offers one pricing dimension: a license for ML Provisioner Starter, billed under a contract. You pay per unit of license. This is the foundation tier of the MLOps pipeline infrastructure, aimed at small teams and proof-of-concept projects. The license provisions core ML infrastructure through CloudFormation and runs in a Docker-based setup. Pricing scales with the number of license units you purchase. There are no separate usage-based charges or add-on dimensions in this listing; you buy the license and deploy the included infrastructure.
Top-of-mind questions for buyers
One license deploys the Starter tier resources as a single CloudFormation stack. This includes a SageMaker Model Registry, CodeCommit or S3 source control, CodeBuild, CodePipeline CI/CD pipelines, and the required IAM roles. It also writes deployment outputs to SSM Parameter Store for downstream use.
The Starter license does not include an S3 artifacts bucket, EventBridge automated deployment, or a CloudWatch dashboard. It also omits KMS encryption, compliance log groups, CloudWatch alarms, SNS alerting, VPC endpoints, and permission boundaries. Those capabilities belong to higher tiers, not this listing.
The license applies per AWS account, with no template sharing mechanism between accounts. Deploying in a second account requires a separate license. Your cost scales with the number of license units you purchase, since there are no separate usage-based charges in this listing.
docs.axontechlabs.com
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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
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
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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