he ZenML Stack components to an external resource.If you are looking for a quick, assisted tour, we recommend using the interactive CLI mode to configure Service Connectors, especially if this is your first time doing it:

zenml service-connector register -i

zenml service-connector register -i

Example Command Output

Please enter a name for the service connector: gcp-interactive

Please enter a description for the service connector []: Interactive GCP connector example

╔══════════════════════════════════════════════════════════════════════════════╗

║                      Available service connector types                       ║

╚══════════════════════════════════════════════════════════════════════════════╝

🌀 Kubernetes Service Connector (connector type: kubernetes)

Authentication methods:

🔒 password

🔒 token

Resource types:

🌀 kubernetes-cluster

Supports auto-configuration: True

Available locally: True

Available remotely: True

This ZenML Kubernetes service connector facilitates authenticating and

connecting to a Kubernetes cluster.

The connector can be used to access to any generic Kubernetes cluster by

providing pre-authenticated Kubernetes python clients to Stack Components that

are linked to it and also allows configuring the local Kubernetes CLI (i.e.

kubectl).

The Kubernetes Service Connector is part of the Kubernetes ZenML integration.

You can either install the entire integration or use a pypi extra to install it

independently of the integration:

pip install "zenml[connectors-kubernetes]" installs only prerequisites for the

Kubernetes Service Connector Type

zenml integration install kubernetes installs the entire Kubernetes ZenML

integration

A local Kubernetes CLI (i.e. kubectl ) and setting up local kubectl

configuration contexts is not required to access Kubernetes clusters in your

Stack Components through the Kubernetes Service Connector.

🐳 Docker Service Connector (connector type: docker)

Authentication methods:

🔒 password

Resource types:

🐳 docker-registry