Are production, QA, testing, and development environments created when Databricks is going to be used for a solution?
It's recommended to create separate environments for production, QA, testing, and development when using Databricks for a solution. However, not everyone does it, and the exact implementation might vary depending on factors like team size, the complexity of the solution, and budget constraints.
Benefits of separate environments:
- Isolation: Each environment serves its own purpose, preventing accidental changes from impacting production or vice versa.
- Testing and validation: QA and testing environments allow thorough testing of features and bug fixes before deployment to production.
- Development flexibility: Developers can experiment and iterate in the development environment without affecting other stages.
- Resource allocation: You can optimize resource allocation for each environment based on its specific needs, maximizing cost efficiency.
Alternative approaches:
- Shared environments: For smaller teams or simple solutions, a single environment might be sufficient, especially during development. However, this introduces more risk and requires stricter control mechanisms.
- Feature flags: Feature flags allow you to toggle features on and off in different environments, providing some level of isolation while still using a single codebase.
How to implement separate environments in Databricks:
- Workspaces: The most common approach is to create separate Databricks workspaces for each environment. This offers complete isolation and control over resources, configurations, and access.
- Clusters: Within a single workspace, you can create dedicated clusters for each environment. While this offers some isolation, it's not as robust as separate workspaces.
- Git branches and notebooks: You can manage different environments within the same workspace by using separate Git branches for each environment and deploying code with notebooks or libraries.
Ultimately, the decision of whether to create separate environments depends on your specific needs and context. Consider the benefits of isolation, testing, and resource optimization when making your choice.