**Note:** If we want to change the starting path for our secrets names from `openmetadata` to a different one, we have
to change the property `clusterName` in our `openmetadata.yaml`. Also, if you inform the `prefix` value, it will be
added before the `clusterName`, i.e., `/<prefix>/<clusterName>/<key>`.
You can inform the `tags` as well as a list of strings `[key1:value1,key2:value2,...]`. These tags will be added
to the resource created in AWS.
## CLI
After enabling the Secret Manager, we also have to make a slight change in our workflows YAML files. In the
`workflowConfig` we have to add the secret manager configuration:
```yaml
workflowConfig:
openMetadataServerConfig:
secretsManagerProvider: aws
secretsManagerLoader: env
hostPort: <OpenMetadatahostandport>
authProvider: <OpenMetadataauthprovider>
```
Then, in the environment running the CLI make sure to have an environment variable `AWS_DEFAULT_REGION` with the rest
of the required configurations from [AWS](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html#using-environment-variables).
## Airflow
If you enabled the Secret Manager and you are using your own Airflow to run the ingestions, make sure to configure
your YAML files as:
```yaml
workflowConfig:
openMetadataServerConfig:
secretsManagerProvider: aws
secretsManagerLoader: airflow
hostPort: <OpenMetadatahostandport>
authProvider: <OpenMetadataauthprovider>
```
and follow the same environment variables to set up the Airflow configuration: