Picture this: You’re building an app that uses global configuration values (public and private keys, environment execution configurations, database credentials, domain names, and URLs), and you need to update them frequently. The first solution you’ll come up with is to manage your global values using ENV files. Still, soon enough, you’ll realize that this approach can be a burden and is unscalable, especially in a distributed architectural system.
Suppose you found a solution that serves as a universal secrets manager and allows you to synchronize environment variables at scale efficiently. Would this help you solve your problem better than ENV files? The answer is YES, and the best solution for your issue is Doppler.
This tutorial will teach you how to integrate Doppler into your apps and store your secrets with it. In this article, you will build and deploy a demo app with Python (Flask) and Heroku, then manage its secrets and environment variables using Doppler.
What is Doppler?
Doppler is a universal secrets manager that allows you to efficiently synchronize environment variables across devices, environments, and team members. It will enable you to store, share, and access secrets from a centralized source with support for collaboration, access controls, versioning, secrets documentation, and many more.
Benefits of using Doppler
Doppler provides many unique features and functionalities that make it more than just a storage for secrets. Here are some of them:
- Doppler simplifies the synchronization of secrets and app configuration across devices, environments, and team members.
- Doppler allows your teams to collaborate and organize secrets across multiple projects and environments.
- Doppler helps developers automate the process of updating secrets in their apps across several locations.
- Doppler lets you deploy everywhere, be it Docker, serverless environments, or anywhere you work.
- Doppler boosts your team's productivity by removing the burden of keeping ENV files in sync.
- Doppler supports secrets versioning, meaning you can easily track changes in real-time and roll back broken changes.
- Doppler also lets you create documentation and notes for secrets values, so you know their usage.
Getting started with Doppler
To continue with this tutorial, you need an account with Doppler. Create one on the Doppler website using your email address, Google account, or Secure SSO if you don't have one.
Step 1: Create a Doppler Project
Projects
are used in Doppler to universally organize and manage your secrets from local development to production.
Click on the Create Project
button in the Doppler dashboard, as shown in the image below:
Step 2: Store your secrets in Doppler
To store secrets in Doppler, select the Project
you want to configure from your dashboard. Click on the Project
you created earlier:
Then, choose the environment execution mode (development, staging, production) to configure your secrets. Select the dev
config:
Next, configure the Project
config and store secrets in it. Click on the Add First Secret
button to add secrets manually or the Import Secrets
button to fetch them from an ENV, JSON or YAML file.
Don't forget to press the
Save
button after adding/updating your secrets in Doppler.
Step 3: Install the Doppler CLI
The Doppler CLI is a lightweight binary that allows you to access your secrets in any environment (local, development, CI/CD, staging, production). Follow this guide to install it on your machine.
Step 4: Authenticate the Doppler CLI
To connect the Doppler CLI to your account and access the secrets of your Projects
, you need to be authenticated on it using an access token. Doppler CLI provides a doppler login
command to authenticate yourself via your browser (for local development).
In the terminal, type the following:
doppler login
You only need to do this once per workplace. If you have multiple workplaces, you can scope each login to a separate directory.
Step 5: Set up a Doppler Project
After installing and authenticating the Doppler CLI, you need to configure it with a Project
in your development environment to fetch its secrets. Doppler CLI provides a doppler setup
command to configure your app with a Project
.
Change the current directory to your app directory, then type the following in the terminal:
cd ./your/project/directory
doppler setup
Now, select the Project
and config
you want to configure your app to use:
You can also use a
doppler.yaml
file to pre-configure the DopplerProject
andconfig
for your app. Follow this guide to learn how.Doppler allows you to set up secrets for multiple projects on a single machine simultaneously by scoping them to specific directories.
Step 6: Inject Doppler into running processes
After setting up the Project
and config
of your secrets for your app, you can inject your secrets as environment variables into running processes using doppler run
. Let’s see an example where we access our secrets from the Python shell.
In your terminal, type the following:
doppler run -- python3
import os
print(os.getenv("DB_URL"))
print(os.getenv("PAYMENT_KEY"))
Here, you launched a process (python3
) and injected your secrets (that we created earlier) into it using doppler run
. Then, you fetched the secrets from environment variables using os.getenv()
.
You can learn more ways to inject Doppler into running processes from this guide.
Setting up the Python app
Now that you have successfully injected your secrets into a running process using Doppler, let's start building a Python (Flask) web app that uses the secrets you stored in Doppler.
Step 1: Install the Flask web framework
You need to install Flask on your machine. In the terminal, type the following:
pip install Flask
Step 2: Create the Flask app
Create a file named app.py
in the same directory you set up Doppler and save the following code in it:
from flask import *
app = Flask(__name__)
@app.route("/")
def home():
return "Hello World!"
if __name__ == "__main__":
app.run(debug=True)
Step 3: Start the app with Doppler
Start the app using doppler run
to inject the secrets into the Flask server. In the terminal, type the following:
doppler run -- python3 app.py
When you open the http://127.0.0.1:5000
URL in your browser, you will get a response like this:
Integrating Doppler with Python and Flask
Let's fetch the secrets from Doppler and use them in the Python (Flask) web app. Since Doppler injects secrets as environment variables, you can easily retrieve them using the built-in os.getenv()
function provided by Python like you would when using ENV files.
Step 1: Update the Flask app
Update the app.py
you created earlier with the code below:
import os
from flask import *
app = Flask(__name__)
@app.route("/")
def home():
response = f"""
<h1>Doppler Secrets</h1>
<h3>DB_URL: {os.getenv('DB_URL')}</h3>
<h3>API_HOST: {os.getenv('API_HOST')}</h3>
<h3>PAYMENT_KEY: {os.getenv('PAYMENT_KEY')}</h3>
<h3>ADMIN_USERNAME: {os.getenv('ADMIN_USERNAME')}</h3>
"""
return response
if __name__ == "__main__":
app.run(debug=True)
Step 2: Start the app with Doppler
Start the app using doppler run
and open the http://127.0.0.1:5000
URL in your browser to confirm Doppler injected your secrets correctly.
doppler run -- python3 app.py
Step 3: Update the secrets in Doppler
Change the secrets from your Doppler dashboard to see how easy, efficient, and scalable the synchronization of your environment variables has become.
Deploying the Flask app
Doppler provides integrations for many cloud providers, including Heroku, AWS, Digital Ocean, Azure, Docker, GCP, and many more to keep your secrets synchronized wherever you develop and deploy.
Doppler also simplifies the whole cloud provider integration process, only requiring you to set things up with a couple of clicks. Let's see how to integrate Doppler with Heroku.
Step 1: Create an app in Heroku
Login to your Heroku dashboard and create a new app to deploy your Python (Flask) app.
Step 2: Integrate Doppler with Heroku
Head over to the INTEGRATIONS
tab in the stg
(staging) config setup of your Doppler Project
.
Don't forget to configure your secrets in the
stg
config of yourProject
.
Next, click on the Add Integration
button and select Heroku from the list of cloud providers.
Then, authorize Doppler to have access to your Heroku account.
Finally, complete the integration process by setting the following:
- Heroku Project Type: Either a Heroku
App
orPipeline
. - App: The name of the Heroku app that you created earlier (
doppler-demo
). - Config to sync: The config that Doppler should inject into your app (
stg
). - Import Options: Whether to import previously configured environment variables in Heroku to Doppler.
Click on the Set Up Integration
button after providing all the necessary information.
You have successfully integrated Doppler with Heroku. Whenever you make changes (adding/updating) to your Project
secrets, Doppler will automatically synchronize them with your Heroku app's Config Vars
.
Step 3: Deploy your app to Heroku
Deploy your app to Heroku as you would typically do.
Conclusion
By integrating Doppler with Python (Flask) and Heroku, you built and deployed a web app with efficient and scalable secrets management using minimal effort. You saw how to store, share, and access secrets using Doppler and integrate your Project
with a cloud provider.
You can also learn more about Doppler from the official documentation. If you have any questions, contact me on Twitter: @LordGhostX
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