Configure an external secrets backend on Astronomer Software

Apache Airflow variables and connections often contain sensitive information about your external systems that should be kept secret in a secure, centralized location that complies with your organization’s security requirements. While secret values of Airflow variables and connections are encrypted in the Airflow metadata database of every Deployment, Astronomer recommends integrating with a secrets backend tool.

Secrets backend tool integration benefits

Integrating a secrets backend tool with Astronomer Software allows you to:

Store Airflow variables and connections in a centralized location alongside secrets from other tools and systems used by your organization, including Kubernetes secrets, SSL certificates, and more.
Comply with internal security postures and policies that protect your organization.
Recover in the case of an incident.
Automatically pull Airflow variables and connections that are already stored in your secrets backend when you create a new Deployment instead of having to set them manually in the Airflow UI.

Astronomer Software integrates with the following secrets backend tools:

Hashicorp Vault
AWS Systems Manager Parameter Store
Google Cloud Secret Manager
Azure Key Vault

Secrets backend integrations are configured individually with each Astronomer Software Deployment.

If you enable a secrets backend on Astronomer Software, you can continue to define Airflow variables and connections either as environment variables or in the Airflow UI as needed. If you define variables and connections in the Airflow UI, they are stored as encrypted values in the Airflow metadata database.

Airflow checks for the value of an Airflow variable or connection in the following order:

Secrets backend
Environment variable
The Airflow UI

Setting Airflow connections with secrets requires knowledge of how to generate Airflow connection URIs. If you plan to store Airflow connections on your secrets backend, see the Apache Airflow documentation for guidance on how to generate a connection URI.

Setup

Hashicorp Vault
AWS Secrets Manager
AWS Parameter Store
Google Cloud Secret Manager
Azure Key Vault

In this section, you’ll learn how to use Hashicorp Vault as a secrets backend for both local development and on Astronomer Software. To do this, you will:

Create an AppRole in Vault which grants Astronomer minimal required permissions.
Write a test Airflow variable or connection as a secret to your Vault server.
Configure your Astro project to pull the secret from Vault.
Test the backend in a local environment.
Deploy your changes to Astronomer Software.

Prerequisites

A Deployment on Astronomer.
The Astro CLI.
A Hashicorp Vault server.
An Astro project initialized with astro dev init.
The Vault CLI.
Your Vault Server’s URL. If you’re using a local server, this should be http://127.0.0.1:8200/.

If you do not already have a Vault server deployed but would like to test this feature, Astronomer recommends that you either:

Sign up for a Vault trial on Hashicorp Cloud Platform (HCP) or
Deploy a local Vault server. See Starting the server in Hashicorp documentation.

Step 1: Create a Policy and AppRole in Vault

To use Vault as a secrets backend, Astronomer recommends configuring a Vault AppRole with a policy that grants only the minimum necessary permissions for Astronomer Software. To do this:

Create a Vault policy with the following permissions:

path "secret/data/variables/*" {
  capabilities = ["read", "list"]
}

path "secret/data/connections/*" {
  capabilities = ["read", "list"]
}

Create a Vault AppRole and attach the policy you just created to it.

Retrieve the role-id and secret-id for your AppRole by running the following commands:

vault read auth/approle/role/<your-approle>/role-id
vault write -f auth/approle/role/<your-approle>/secret-id

Save these values for Step 3.

Step 2: Write an Airflow variable or connection to Vault

To test whether your Vault server is set up properly, create a test Airflow variable or connection to store as a secret.To store an Airflow variable in Vault as a secret, run the following Vault CLI command with your own values:

vault kv put secret/variables/<your-variable-key> value=<your-variable-value>

To store a connection in Vault as a secret, run the following Vault CLI command with your own values:

vault kv put secret/connections/<your-connection-id> conn_uri=<connection-type>://<connection-login>:<connection-password>@<connection-host>:5432

To confirm that your secret was written to Vault successfully, run:

# For variables
$ vault kv get secret/variables/<your-variable-key>
# For connections
$ vault kv get secret/connections/<your-connection-id>

Step 3: Set up Vault locally

In your Astro project, add the Hashicorp Airflow provider to your project by adding the following to your requirements.txt file:

apache-airflow-providers-hashicorp

Then, add the following environment variables to your Dockerfile:

# Make sure to replace `<your-approle-id>` and `<your-approle-secret>` with your own values.
ENV AIRFLOW__SECRETS__BACKEND=airflow.providers.hashicorp.secrets.vault.VaultBackend
ENV AIRFLOW__SECRETS__BACKEND_KWARGS={"connections_path": "connections", "variables_path": "variables", "config_path": null, "url": "http://host.docker.internal:8200", "auth_type": "approle", "role_id":"<your-approle-id>", "secret_id":"<your-approle-secret>"}

This tells Airflow to look for variable and connection information at the secret/variables/* and secret/connections/* paths in your Vault server. In the next step, you’ll test this configuration in a local Airflow environment.

If you want to deploy your project to a hosted Git repository before deploying to Astronomer Software, be sure to save <your-approle-id> and <your-approle-secret> securely. Astronomer recommends adding them to your project’s .env file and specifying this file in .gitignore.When you deploy to Astronomer Software in Step 4, you can set these values as secrets in the Software UI.

By default, Airflow uses "kv_engine_version": 2, but this secret was written using v1. You can change this to accommodate how you write and read your secrets.

For more information on the Airflow provider for Hashicorp Vault and how to further customize your integration, see the Apache Airflow documentation.

Step 4: Run an example DAG to test Vault locally

To test Vault, write a simple DAG which calls your test secret and add this DAG to your project’s dags directory. For example, you can use the following DAG to print the value of a variable to your task logs:

from airflow import DAG
from airflow.hooks.base import BaseHook
from airflow.models import Variable
from airflow.operators.python import PythonOperator
from datetime import datetime

def print_var():
    my_var = Variable.get("<your-variable-key>")
    print(f'My variable is: {my_var}')

with DAG('example_secrets_dags', start_date=datetime(2022, 1, 1), schedule=None) as dag:

  test_task = PythonOperator(
      task_id='test-task',
      python_callable=print_var,
)

Once you’ve added this DAG to your project:

Run astro dev restart to push your changes to your local Airflow environment.
In the Airflow UI (http://localhost:8080/admin/), trigger your new DAG.
Click on test-task > View Logs. If you ran the example DAG above, you should see the contents of your secret in the task logs:
{logging_mixin.py:109} INFO - My variable is: my-test-variable

Once you confirm that the setup was successful, you can delete this example DAG.

Step 5: Deploy on Astronomer Software

Once you’ve confirmed that the integration with Vault works locally, you can complete a similar set up with a Deployment on Astronomer Software.

In the Software UI, add the same environment variables found in your Dockerfile to your Deployment environment variables. Specify AIRFLOW__SECRETS__BACKEND_KWARGS as secret to ensure that your Vault credentials are stored securely.
In your Astro project, delete the environment variables from your Dockerfile.
Deploy your changes to Astronomer Software.

Now, any Airflow variable or connection that you write to your Vault server can be successfully accessed and pulled by any DAG in your Deployment on Astronomer Software.

Prerequisites

A Deployment.
The Astro CLI.
An Astro project initialized with astro dev init.
Access to AWS Secrets Manager.
A valid AWS Access Key ID and Secret Access Key.

Step 1: Write an Airflow variable or connection to AWS Secrets Manager

To start, add an Airflow variable or connection as a secret to Secrets Manager for testing. For instructions, see the AWS documentation on how to do so using the AWS Secrets Manager Console, CLI or SDK.Variables and connections should live at /airflow/variables and /airflow/connections, respectively. For example, if you’re setting a secret variable with the key my_secret, it should exist at /airflow/connections/my_secret.

Step 2: Set up AWS Secrets Manager locally

To test AWS Secrets Manager locally, configure it as a secrets backend in your Astro project.First, install the Airflow provider for Amazon by adding the following to your project’s requirements.txt file:

apache-airflow-providers-amazon

Then, add the following environment variables to your project’s Dockerfile:

# Make sure to replace `<your-aws-key>` and `<your-aws-secret-key>` with your own values.
ENV AWS_ACCESS_KEY_ID="<your-aws-key>"
ENV AWS_SECRET_ACCESS_KEY="<your-aws-secret-key>"
ENV AWS_DEFAULT_REGION="<your-aws-region>"
ENV AIRFLOW__SECRETS__BACKEND=airflow.providers.amazon.aws.secrets.secrets_manager.SecretsManagerBackend
ENV AIRFLOW__SECRETS__BACKEND_KWARGS={"connections_prefix": "airflow/connections", "variables_prefix": "airflow/variables"}

In the next step, you’ll test that this configuration is valid locally.

If you want to deploy your project to a hosted Git repository before deploying to Astronomer Software, be sure to save <your-aws-key> and <your-aws-secret-key> in a secure manner. When you deploy to Astronomer Software, use the Software UI to set these values as secrets.

If you’d like to reference an AWS profile, you can also add the profile param to ENV AIRFLOW__SECRETS__BACKEND_KWARGS.To further customize the integration between Airflow and AWS Secrets Manager, reference Airflow documentation with the full list of available kwargs.

Step 3: Run an example DAG to test AWS Secrets Manager locally

To test Secrets Manager, write a simple DAG which calls your secret and add this DAG to your Astro project’s dags directory.For example, you can use the following DAG to print the value of an Airflow variable to your task logs:

from datetime import datetime

from airflow import DAG
from airflow.models import Variable
from airflow.operators.python import PythonOperator

def print_var():
    my_var = Variable.get("<your-variable-key>")
    print(f'My variable is: {my_var}')

with DAG('example_secrets_dags', start_date=datetime(2022, 1, 1), schedule=None) as dag:

  test_task = PythonOperator(
      task_id='test-task',
      python_callable=print_var,
)

To test your changes:

Run astro dev restart to push your changes to your local Airflow environment.
In the Airflow UI (http://localhost:8080/admin/), trigger your new DAG.
Click on test-task > View Logs. If you ran the example DAG above, you should see the contents of your secret in the task logs:
{logging_mixin.py:109} INFO - My variable is: my-test-variable

Step 4: Deploy to Astronomer Software

Once you’ve confirmed that the integration with AWS Secrets Manager works locally, you can complete a similar set-up with a Deployment on Astronomer Software.

In the Software UI, add the same environment variables found in your Dockerfile to your Deployment environment variables. Specify both AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY as secret ensure that your credentials are stored securely.
In your Astro project, delete the environment variables from your Dockerfile.
Deploy your changes to Astronomer Software.

Now, any Airflow variable or connection that you write to AWS Secrets Manager can be automatically pulled by any DAG in your Deployment on Astronomer Software.

In this section, you’ll learn how to use AWS Systems Manager (SSM) Parameter Store as a secrets backend on Astronomer Software.

Prerequisites

A Deployment.
The Astro CLI.
An Astro project initialized with astro dev init.
Access to AWS SSM Parameter Store.
A valid AWS Access Key ID and Secret Access Key.

Step 1: Write an Airflow variable or connection to AWS Parameter Store

To start, add an Airflow variable or connection as a secret to Parameter Store for testing. For instructions, see the AWS documentation on how to do so using the AWS Systems Manager Console, the AWS CLI, or Tools for Windows PowerShell.Variables and connections should live at /airflow/variables and /airflow/connections, respectively. For example, if you’re setting a secret variable with the key my_secret, it should exist at /airflow/connections/my_secret.

Step 2: Set up AWS Parameter Store locally

To test AWS Parameter Store locally, configure it as a secrets backend in your Astro project.First, install the Airflow provider for Amazon by adding the following to your project’s requirements.txt file:

apache-airflow-providers-amazon

Then, add the following environment variables to your project’s Dockerfile:

# Make sure to replace `<your-aws-key>` and `<your-aws-secret-key>` with your own values.
ENV AWS_ACCESS_KEY_ID="<your-aws-key>"
ENV AWS_SECRET_ACCESS_KEY="<your-aws-secret-key>"
ENV AWS_DEFAULT_REGION="<your-aws-region>"
ENV AIRFLOW__SECRETS__BACKEND=airflow.providers.amazon.aws.secrets.systems_manager.SystemsManagerParameterStoreBackend
ENV AIRFLOW__SECRETS__BACKEND_KWARGS={"connections_prefix": "/airflow/connections", "variables_prefix": "/airflow/variables"}

In the next step, you’ll test that this configuration is valid locally.

If you’d like to reference an AWS profile, you can also add the profile param to ENV AIRFLOW__SECRETS__BACKEND_KWARGS.To further customize the integration between Airflow and AWS SSM Parameter Store, reference Airflow documentation with the full list of available kwargs.

Step 3: Run an example DAG to test AWS Parameter Store locally

To test Parameter Store, write a simple DAG which calls your secret and add this DAG to your Astro project’s dags directory.For example, you can use the following DAG to print the value of an Airflow variable to your task logs:

from datetime import datetime

from airflow import DAG
from airflow.models import Variable
from airflow.operators.python import PythonOperator

def print_var():
    my_var = Variable.get("<your-variable-key>")
    print(f'My variable is: {my_var}')

with DAG('example_secrets_dags', start_date=datetime(2022, 1, 1), schedule=None) as dag:

  test_task = PythonOperator(
      task_id='test-task',
      python_callable=print_var,
)

You can do the same for any Airflow connection.To test your changes:

Run astro dev restart to push your changes to your local Airflow environment.
In the Airflow UI (http://localhost:8080/admin/), trigger your new DAG.
Click on test-task > View Logs. If you ran the example DAG above, you should see the contents of your secret in the task logs:
{logging_mixin.py:109} INFO - My variable is: my-test-variable

Step 4: Deploy to Astronomer Software

Once you’ve confirmed that the integration with AWS SSM Parameter Store works locally, you can complete a similar set up with a Deployment on Astronomer Software.

In the Software UI, add the same environment variables found in your Dockerfile to your Deployment environment variables. Specify both AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY as secret ensure that your credentials are stored securely.
In your Astro project, delete the environment variables from your Dockerfile.
Deploy your changes to Astronomer Software.

Now, any Airflow variable or connection that you write to AWS SSM Parameter Store can be automatically pulled by any DAG in your Deployment on Astronomer Software.

In this section, you’ll learn how to use Google Cloud Secret Manager as a secrets backend on Astronomer Software.

Prerequisites

A Deployment.
The Astro CLI.
An Astro project initialized with astro dev init.
Cloud SDK.
A Google Cloud environment with Secret Manager configured.
A service account with the Secret Manager Secret Accessor role on Google Cloud.
A JSON service account key for the service account.

Step 1: Write an Airflow variable or connection to Google Cloud Secret Manager

To start, add an Airflow variable or connection as a secret to Google Cloud Secret Manager. You can do so in the Cloud Console or the gcloud CLI.Secrets must be formatted such that:

Airflow variables are set as airflow-variables-<variable-key>.
Airflow connections are set as airflow-connections-<connection-id>.

For example, to add an Airflow variable with a key my-secret-variable, you would run the following gcloud CLI command:

gcloud secrets create airflow-variables-<my-secret-variable> \
    --replication-policy="automatic"

For more information on creating secrets in Google Cloud Secret Manager, see the Google Cloud documentation.

Step 2: Set up Secret Manager locally

To test Google Secret Manager locally, configure it as a secrets backend in your Astro project.First, install the Airflow provider for Google by adding the following to your project’s requirements.txt file:

apache-airflow-providers-google

Then, add the following environment variables to your project’s Dockerfile:

ENV AIRFLOW__SECRETS__BACKEND=airflow.providers.google.cloud.secrets.secret_manager.CloudSecretManagerBackend
ENV AIRFLOW__SECRETS__BACKEND_KWARGS={"connections_prefix": "airflow-connections", "variables_prefix": "airflow-variables", "gcp_keyfile_dict": <your-key-file>}

Make sure to paste your entire JSON service account key in place of <your-key-file>. In the next step, you’ll test that this configuration is valid locally.

If you want to deploy your project to a hosted Git repository before deploying to Astronomer, be sure to save <your-key-file> securely. Astronomer recommends adding it to your project’s .env file and specifying this file in .gitignore. When you deploy to Astronomer, you should set these values as secrets in the Software UI.

Step 3: Run an example DAG to test Secret Manager locally

To test Secret Manager, create a secret containing either an Airflow variable or connection for testing.Once you create a test secret, write a simple DAG which calls the secret and add this DAG to your project’s dags directory. For example, you can use the following DAG to print the value of a variable to your task logs:

from datetime import datetime

from airflow import DAG
from airflow.models import Variable
from airflow.operators.python import PythonOperator

def print_var():
    my_var = Variable.get("<your-variable-key>")
    print(f'My variable is: {my_var}')

with DAG('example_secrets_dags', start_date=datetime(2022, 1, 1), schedule=None) as dag:

  test_task = PythonOperator(

      task_id='test-task',
      python_callable=print_var,
)

To test your changes:

Run astro dev stop followed by astro dev start to push your changes to your local Airflow environment.
In the Airflow UI (http://localhost:8080/admin/), trigger your new DAG.
Click on test-task > View Logs. If you ran the example DAG above, you should see the contents of your secret in the task logs:
{logging_mixin.py:109} INFO - My variable is: my-test-variable

Once you confirm that the setup was successful, you can delete this DAG.

Step 4: Deploy to Astronomer Software

Once you’ve confirmed that the integration with Google Cloud Secret Manager works locally, you can complete a similar set up with a Deployment on Astronomer Software.

In the Software UI, add the same environment variables found in your Dockerfile to your Deployment environment variables. Specify both AIRFLOW__SECRETS__BACKEND and AIRFLOW__SECRETS__BACKEND_KWARGS as Secret to ensure that your credentials are stored securely.
In your Astro project, delete the environment variables from your Dockerfile.
Deploy your changes to Astronomer Software.

You now should be able to see your secret information being pulled from Secret Manager on Astronomer. From here, you can store any Airflow variables or connections as secrets on Secret Manager and use them in your project.

In this section, you’ll learn how to use Azure Key Vault as a secrets backend on Astronomer Software.

Prerequisites

A Deployment.
The Astro CLI.
An Astro project initialized with astro dev init.
An existing Azure Key Vault linked to a resource group.
Your Key Vault URL. To find this, go to your Key Vault overview page > Vault URI.

If you do not already have Key Vault configured, see the Microsoft Azure documentation.

Step 1: Register Astronomer as an app on Azure

Follow the Microsoft Azure documentation to register a new application for Astronomer.At a minimum, you need to add a secret that Astronomer can use to authenticate to Key Vault.Note the value of the application’s client ID and secret for Step 3.

Step 2: Create an access policy

Follow the Microsoft documentation to create a new access policy for the application that you just registered. The settings you need to configure for your policy are:

Configure from template: Select Key, Secret, & Certificate Management.
Select principal: Select the name of the application that you registered in Step 1.

Step 3: Set up Key Vault locally

In your Astro project, add the following line to your requirements.txt file:

apache-airflow-providers-microsoft-azure

In your Dockerfile, add the following environment variables with your own values:

ENV AZURE_CLIENT_ID="<your-client-id>" # Found on App Registration page > 'Application (Client) ID'
ENV AZURE_TENANT_ID="<your-tenant-id>" # Found on App Registration page > 'Directory (tenant) ID'
ENV AZURE_CLIENT_SECRET="<your-client-secret>" # Found on App Registration Page > Certificates and Secrets > Client Secrets > 'Value'
ENV AIRFLOW__SECRETS__BACKEND=airflow.providers.microsoft.azure.secrets.key_vault.AzureKeyVaultBackend
ENV AIRFLOW__SECRETS__BACKEND_KWARGS={"connections_prefix": "airflow-connections", "variables_prefix": "airflow-variables", "vault_url": "<your-vault-url>"}

This tells Airflow to look for variable information at the airflow-variables-* path in Azure Key Vault and connection information at the airflow-connections-* path. In the next step, you’ll run an example DAG to test this configuration locally.

By default, this setup requires that you prefix any secret names in Key Vault with airflow-connections or airflow-variables. If you don’t want to use prefixes in your Key Vault secret names, set the values for sep, "connections_prefix", and "variables_prefix" to "" within AIRFLOW__SECRETS__BACKEND_KWARGS.

If you want to deploy your project to a hosted Git repository before deploying to Astronomer, be sure to save <your-client-id>, <your-tenant-id>, and <your-client-secret> in a secure manner. When you deploy to Astronomer, you should set these values as secrets with the Software UI.

Step 4: Test Key Vault locally

To test your Key Vault setup on Astronomer locally, create a new secret in Key Vault containing either a variable or a connection.Once you create a test secret, write a simple DAG which calls the secret and add this DAG to your project’s dags directory. For example, you can use the following DAG to print the value of a variable to your task logs:

from datetime import datetime

from airflow import DAG
from airflow.models import Variable
from airflow.operators.python import PythonOperator

def print_var():
    my_var = Variable.get("<your-variable-key>")
    print(f'My variable is: {my_var}')

with DAG('example_secrets_dags', start_date=datetime(2022, 1, 1), schedule=None) as dag:

  test_task = PythonOperator(
      task_id='test-task',
      python_callable=print_var,
)

To test your changes:

Run astro dev stop followed by astro dev start to push your changes to your local Airflow environment.
In the Airflow UI (http://localhost:8080/admin/), trigger your new DAG.
Click on test-task > View Logs. If you ran the example DAG above, you should see the contents of your secret in the task logs:
{logging_mixin.py:109} INFO - My variable is: my-test-variable

Once you confirm that the setup was successful, you can delete this DAG.

Step 5: Push changes to Astronomer

Once you’ve confirmed that your secrets are being imported correctly to your local environment, you’re ready to configure the same feature in a Deployment on Astronomer Software.

In the Software UI, add the same environment variables found in your Dockerfile to your Deployment environment variables. Specify the AZURE_CLIENT_ID, AZURE_TENANT_ID, and AZURE_CLIENT_SECRET variables as Secret to ensure that your credentials are stored securely.
In your Astro project, delete the environment variables from your Dockerfile.
Deploy your changes to Astronomer Software.

From here, you can store any Airflow variables or connections as secrets on Key Vault and use them in your project.

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Reference

Configure an external secrets backend on Astronomer Software

Secrets backend tool integration benefits

Setup

Prerequisites

Step 1: Create a Policy and AppRole in Vault

Step 2: Write an Airflow variable or connection to Vault

Step 3: Set up Vault locally

Step 4: Run an example DAG to test Vault locally

Step 5: Deploy on Astronomer Software

Prerequisites

Step 1: Write an Airflow variable or connection to AWS Secrets Manager

Step 2: Set up AWS Secrets Manager locally

Step 3: Run an example DAG to test AWS Secrets Manager locally

Step 4: Deploy to Astronomer Software

Prerequisites

Step 1: Write an Airflow variable or connection to AWS Parameter Store

Step 2: Set up AWS Parameter Store locally

Step 3: Run an example DAG to test AWS Parameter Store locally

Step 4: Deploy to Astronomer Software

Prerequisites

Step 1: Write an Airflow variable or connection to Google Cloud Secret Manager

Step 2: Set up Secret Manager locally

Step 3: Run an example DAG to test Secret Manager locally

Step 4: Deploy to Astronomer Software

Prerequisites

Step 1: Register Astronomer as an app on Azure

Step 2: Create an access policy

Step 3: Set up Key Vault locally

Step 4: Test Key Vault locally

Step 5: Push changes to Astronomer

​Secrets backend tool integration benefits

​Setup

​Prerequisites

​Step 1: Create a Policy and AppRole in Vault

​Step 2: Write an Airflow variable or connection to Vault

​Step 3: Set up Vault locally

​Step 4: Run an example DAG to test Vault locally

​Step 5: Deploy on Astronomer Software

​Prerequisites

​Step 1: Write an Airflow variable or connection to AWS Secrets Manager

​Step 2: Set up AWS Secrets Manager locally

​Step 3: Run an example DAG to test AWS Secrets Manager locally

​Step 4: Deploy to Astronomer Software

​Prerequisites

​Step 1: Write an Airflow variable or connection to AWS Parameter Store

​Step 2: Set up AWS Parameter Store locally

​Step 3: Run an example DAG to test AWS Parameter Store locally

​Step 4: Deploy to Astronomer Software

​Prerequisites

​Step 1: Write an Airflow variable or connection to Google Cloud Secret Manager

​Step 2: Set up Secret Manager locally

​Step 3: Run an example DAG to test Secret Manager locally

​Step 4: Deploy to Astronomer Software

​Prerequisites

​Step 1: Register Astronomer as an app on Azure

​Step 2: Create an access policy

​Step 3: Set up Key Vault locally

​Step 4: Test Key Vault locally

​Step 5: Push changes to Astronomer

Secrets backend tool integration benefits

Setup

Prerequisites

Step 1: Create a Policy and AppRole in Vault

Step 2: Write an Airflow variable or connection to Vault

Step 3: Set up Vault locally

Step 4: Run an example DAG to test Vault locally

Step 5: Deploy on Astronomer Software

Prerequisites

Step 1: Write an Airflow variable or connection to AWS Secrets Manager

Step 2: Set up AWS Secrets Manager locally

Step 3: Run an example DAG to test AWS Secrets Manager locally

Step 4: Deploy to Astronomer Software

Prerequisites

Step 1: Write an Airflow variable or connection to AWS Parameter Store

Step 2: Set up AWS Parameter Store locally

Step 3: Run an example DAG to test AWS Parameter Store locally

Step 4: Deploy to Astronomer Software

Prerequisites

Step 1: Write an Airflow variable or connection to Google Cloud Secret Manager

Step 2: Set up Secret Manager locally

Step 3: Run an example DAG to test Secret Manager locally

Step 4: Deploy to Astronomer Software

Prerequisites

Step 1: Register Astronomer as an app on Azure

Step 2: Create an access policy

Step 3: Set up Key Vault locally

Step 4: Test Key Vault locally

Step 5: Push changes to Astronomer