same credentials across multiple stack components.If you don't already have an AWS Service Connector configured in your ZenML deployment, you can register one using the interactive CLI command. You have the option to configure an AWS Service Connector that can be used to access more than one S3 bucket or even more than one type of AWS resource:

zenml service-connector register --type aws -i

A non-interactive CLI example that leverages the AWS CLI configuration on your local machine to auto-configure an AWS Service Connector targeting a single S3 bucket is:

zenml service-connector register <CONNECTOR_NAME> --type aws --resource-type s3-bucket --resource-name <S3_BUCKET_NAME> --auto-configure

Example Command Output

$ zenml service-connector register s3-zenfiles --type aws --resource-type s3-bucket --resource-id s3://zenfiles --auto-configure

⠸ Registering service connector 's3-zenfiles'...

Successfully registered service connector `s3-zenfiles` with access to the following resources:

┏━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━┓

┃ RESOURCE TYPE │ RESOURCE NAMES ┃

┠───────────────┼────────────────┨

┃ 📦 s3-bucket  │ s3://zenfiles  ┃

┗━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━┛

Note: Please remember to grant the entity associated with your AWS credentials permissions to read and write to your S3 bucket as well as to list accessible S3 buckets. For a full list of permissions required to use an AWS Service Connector to access one or more S3 buckets, please refer to the AWS Service Connector S3 bucket resource type documentation or read the documentation available in the interactive CLI commands and dashboard. The AWS Service Connector supports many different authentication methods with different levels of security and convenience. You should pick the one that best fits your use case.

If you already have one or more AWS Service Connectors configured in your ZenML deployment, you can check which of them can be used to access the S3 bucket you want to use for your S3 Artifact Store by running e.g.: