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Enhance your MLOps workflow by integrating Azure Container Registry with ZenML. This integration allows you to efficiently store, manage, and deploy container images for your ML components, leveraging the scalability and reliability of Azure's cloud-based container registry service.
Features with ZenML
- Seamless integration of Azure Container Registry within ZenML pipelines
- Effortless storage and management of container images for ML components
- Scalable and reliable container registry backed by Azure's cloud infrastructure
- Integrate with other Azure-based stack components for end-to-end MLOps
- Secure access and authentication using Azure credentials or service connectors
Main Features
- Fully-managed, private container registry for storing Docker and OCI images
- High availability and geo-replication for global deployments
- Integrated security features like role-based access control and network restrictions
- Support for artifact signing and image vulnerability scanning
- Comprehensive APIs and tooling for automation and CI/CD integration
How to use ZenML with Azure Container Registry
# 1. Install the ZenML `azure` integration
# zenml integration install azure
# 2. Register an Azure container registry using its URI
# zenml container-registry register <NAME> --flavor=azure --uri="<YOUR URI>"
# 3. Update your stack with your new container registry
# zenml stack update -c <NAME>
from zenml import pipeline, step
@step
def hello_world() -> str:
return "Hello World!"
@pipeline
def my_pipeline():
_ = hello_world()
if __name__ == "__main__":
my_pipeline()
