Python: Setting up a staging environment

This documentation is part of the Advanced usages guide. You can view the complete guide here: Going further with your Python deployments.

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A staging environment is a best practice when used alongside development and production environments. It replicates the production environment so that you can test updates and changes before going live, reducing the risk of issues in production.

A staging environment must closely mirror the production environment.

However, it should use a cloned version of your production database or connected services rather than the live production database.

If your Python service depends on databases or other services, recreate them in a new <Project> - Staging stack.

Follow these steps to set up a staging environment with Stackhero:

1. On the Stackhero dashboard, rename your existing stack from <Project> to <Project> - Production. For example, if your project is called Chat Bot, the stack becomes Chat Bot - Production.
2. Create a new stack named <Project> - Staging. For the Chat Bot project, the stack becomes Chat Bot - Staging.
3. Start a Python service within the staging stack.
4. Retrieve the git remote command and follow the instructions in the Deploying to staging environment documentation.

This configuration ensures you have a fully functional staging environment for testing updates before production deployment.