Netflix DevOps Engineer Interview Questions

As Netflix manages a plethora of microservices, a central configuration manager is vital for managing dynamic configurations across deployments. Your task is to design a class that can handle storing, updating, and retrieving configurations for various services.
- def get_config(service_name: str) -> Dict[str, str]: Retrieves configuration for a given service.
- def set_config(service_name: str, config: Dict[str, str]) -> None: Updates the configuration for a given service.
- def list_services() -> List[str]: Returns a list of all services currently managed by the configuration manager.Example 1:
Input: set_config('video_service', {'quality': '1080p', 'bitrate': '4500kbps'})
Output: None
Explanation: Updates the configuration for the video_service.Example 2:
Input: get_config('video_service')
Output: {'quality': '1080p', 'bitrate': '4500kbps'}
Explanation: Retrieves the updated configuration for the video_service.Constraints:
- The number of services managed does not exceed 1000.
- Configuration items per service are limited to 100.

Netflix relies on seamless Continuous Integration and Continuous Deployment to ensure rapid iterations of their streaming services. You need to implement a pipeline that automatically tests and deploys code changes efficiently.
Design a pipeline that includes automated testing, security scanning, and different deployment stages.
- def run_tests(commit: str) -> None: Runs unit tests for the given commit.
- def deploy_to_staging(commit: str) -> bool: Deploys the given commit to the staging environment.
- def promote_to_production(commit: str) -> bool: Promotes a successfully tested commit to production.Example 1:
Input: run_tests('abc123')
Output: None
Explanation: Runs all tests for the specified commit.Example 2:
Input: promote_to_production('abc123')
Output: True
Explanation: Successfully promotes the commit to production if all tests passed.Constraints:
- The commit string will be a valid git SHA.
- Only valid commits that passed tests can be promoted.

As Netflix deploys thousands of microservices, optimizing Docker image builds is essential to reduce deployment times. You are tasked with refactoring a Dockerfile to enhance its efficiency.
You need to rewrite the Dockerfile applying best practices in caching and layers to minimize build time while ensuring the image is as small as possible.Example 1:
Input: Dockerfile with multiple RUN statements and unnecessary packages.
Output: Optimized Dockerfile with fewer layers and reduced size.
Explanation: Consolidates RUN statements and removes unnecessary dependencies.Constraints:
- Current Dockerfile size is greater than 200MB.
- Must maintain application functionality and compatibility.

In Netflix's infrastructure, managing multiple Terraform states efficiently is crucial due to the vast number of services and environments. Proper state management ensures that the infrastructure is maintained consistently without manual errors.
You are required to implement a script that automates the backup, cleanup, and restoration of Terraform states across different environments.
- def backup_states(states: List[str]) -> None: Backs up the provided Terraform states.
- def clean_old_states(states: List[str], retention_days: int) -> None: Cleans up states older than the specified retention period.
- def restore_state(state: str) -> bool: Restores a Terraform state from the backup.Example 1:
Input: backup_states(['dev', 'prod'])
Output: None
Explanation: Backs up the specified states.Example 2:
Input: clean_old_states(['dev', 'prod'], 30)
Output: None
Explanation: Cleans up states older than 30 days.Constraints:
- 1 <= states.length <= 100
- 1 <= retention_days <= 365