This documentation section provides a detailed guide on how the benhall/flask-demo
project manages and stores sensitive information in a production environment. This includes best practices, code examples, and explanations for expert developers.
Storing Production Secrets
In any application, especially web applications, managing secrets such as API keys, database connection strings, and other sensitive configuration is crucial. Here is a step-by-step guide on how to securely handle secrets in a production setting.
1. Environment Variables
One of the most common practices for managing secrets is utilizing environment variables. This method keeps sensitive information out of your codebase.
Example:
You would set environment variables in your production environment, for example:
export DATABASE_URL='postgres://user:password@localhost/dbname'
export SECRET_KEY='your_secret_key'
In your app.py
, you can access these variables using Python’s os
module:
import os
DATABASE_URL = os.getenv('DATABASE_URL')
SECRET_KEY = os.getenv('SECRET_KEY')
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = DATABASE_URL
app.secret_key = SECRET_KEY
2. Configuration Files
If you prefer to keep secrets in a file, avoid hardcoding them directly in your source code. Instead, use a configuration file that is not tracked by version control. For example, create a config.py
file and include it in your .gitignore
.
Example:
# config.py
import os
class Config:
SECRET_KEY = os.getenv('SECRET_KEY', 'default_secret_key')
DATABASE_URL = os.getenv('DATABASE_URL', 'sqlite:///:memory:')
Then, you would load this configuration in your app.py
:
from config import Config
app.config.from_object(Config)
3. Using Makefile for Environment Setup
The Makefile
can be utilized for setting up the environment during deployment. Ensure sensitive operations are encapsulated to avoid exposing them in logs or on the console.
Example:
In your Makefile
, create a target for running the application:
run:
@echo "Starting application..."
FLASK_APP=app.py flask run
When running this, you can set up your environment before starting:
make run
4. Secrets Management Solutions
For larger applications or teams, consider using a dedicated secrets management tool such as AWS Secrets Manager, HashiCorp Vault, or Azure Key Vault.
Integrate the library corresponding to the secret management tool you choose and fetch the secrets in your application after authentication. For instance:
import boto3
from botocore.exceptions import ClientError
def get_secret():
secret_name = "my_database_password"
session = boto3.session.Session()
client = session.client(
service_name='secretsmanager',
region_name='us-east-1'
)
try:
get_secret_value_response = client.get_secret_value(SecretId=secret_name)
except ClientError as e:
# Handle errors
pass
return get_secret_value_response['SecretString']
This would allow you to retrieve secrets dynamically without hardcoding them in your configuration files.
Final Notes
Always ensure that any sensitive information stored in your application is encrypted both at rest and in transit. Regularly audit access and use secrets management tools that provide auditing capabilities.
By following these steps, one can better secure sensitive information in a production environment in benhall/flask-demo
.
Sources: The information was consolidated from the project code and common practices for Python web applications, aligning with the structure and requirements of benhall/flask-demo
.