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AWS Secrets Manager /deployment/secrets-manager/supported-implementations/aws-secrets-manager

AWS Secrets Manager

Setup

The setup steps covers the use of the managed version of the AWS Secrets Manager as secrets manager but for the non-managed follow only the steps related to the Airflow server and CLI.

1. Permissions needed

These are the permissions required in the IAM policy to enable the AWS Secrets Manager in OpenMetadata.

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "secretsmanager:GetSecretValue",
                "secretsmanager:PutSecretValue",
                "secretsmanager:CreateSecret",
                "secretsmanager:UpdateSecret"
            ],
            "Resource": "*"
        }
    ]
}

2. Update configuration

We have to set up the secret manager provider we want to use, that in our case is aws, and the credentials for our AWS account.

The changes to be done in openmetadata.yaml file of the OpenMetadata server are:

...
secretsManagerConfiguration:
    secretsManager: managed-aws # or env var SECRET_MANAGER. For non-managed use 'aws'.
    parameters:
      region: <aws region> # or env var OM_SM_REGION
      accessKeyId: <aws access key id> # or env var OM_SM_ACCESS_KEY_ID
      secretAccessKey: <aws secret access key> # or env var OM_SM_ACCESS_KEY

pipelineServiceClientConfiguration:
  # ...
  # Secrets Manager Loader: specify to the Ingestion Framework how to load the SM credentials from its env
  # Supported: noop, airflow, env
  secretsManagerLoader: ${PIPELINE_SERVICE_CLIENT_SECRETS_MANAGER_LOADER:-"noop"}
...

And these are the changes required in airflow.cfg of our Airflow instance:

...
[openmetadata_secrets_manager]
aws_region = <aws region>
aws_access_key_id = <aws access key id>
aws_secret_access_key = <aws secret access key>
...

As an alternative to editing the airflow.cfg file, we can also set the following environment variables:

AIRFLOW__OPENMETADATA_SECRETS_MANAGER__AWS_REGION= <aws region>
AIRFLOW__OPENMETADATA_SECRETS_MANAGER__AWS_ACCESS_KEY_ID= <aws access key id>
AIRFLOW__OPENMETADATA_SECRETS_MANAGER__AWS_SECRET_ACCESS_KEY= <aws secret access key>

If no parameters are provided for the AWS account, or only <aws region>, it will use the default credentials. The default credential will look for credentials in:

  1. Environment variables - AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY.
  2. Shared credential file - ~/.aws/credentials
  3. AWS config file - ~/.aws/config
  4. Assume Role provider
  5. Instance metadata service on an Amazon EC2 instance that has an IAM role configured

More info in AWS SDK for Java and Boto3 Docs

3. Restart both servers

After updating the configuration files, we are ready to restart both services. When the OM server starts, it will automatically detect that a Secrets Manager has been configured and will migrate all our sensitive data and remove it from our DB.

If everything goes as planned, all the data would be displayed using the secrets names which starts with /openmetadata/... in your AWS Secrets Manager console. The following image shows what it should look like:

{% image src="/images/v1.1.0/deployment/secrets-manager/supported-implementations/aws-secrets-manager/secrets-manager-console.png" alt="secrets-manager-console" /%}

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

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:

workflowConfig:
  openMetadataServerConfig:
    secretsManagerProvider: aws
    secretsManagerLoader: env
    hostPort: <OpenMetadata host and port>
    authProvider: <OpenMetadata auth provider>

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.

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:

workflowConfig:
  openMetadataServerConfig:
    secretsManagerProvider: aws
    secretsManagerLoader: airflow
    hostPort: <OpenMetadata host and port>
    authProvider: <OpenMetadata auth provider>

and follow the same environment variables to set up the Airflow configuration:

AIRFLOW__OPENMETADATA_SECRETS_MANAGER__AWS_REGION= <aws region>
AIRFLOW__OPENMETADATA_SECRETS_MANAGER__AWS_ACCESS_KEY_ID= <aws access key id>
AIRFLOW__OPENMETADATA_SECRETS_MANAGER__AWS_SECRET_ACCESS_KEY= <aws secret access key>