Implement GCZ Log Consumption Services and API with Pagination and Validation (Mock backend MVP)

Objective:

Implement log consumption functionality for the transformer service that allows querying logs by stream type, date range, and keyword, with pagination and validation capabilities.

Technical Requirements:

1. Log Streams: Introduce a dictionary for log streams that includes the following types:

   • transformer: Transformer application logs.
   • ingestion: Data ingestion process logs.
   • trajectory: Trajectory processing logs.
   • provider: Provider application logs.

2. Controller:

   • Create a LogsController to handle the /logs/{logStream} endpoint, supporting filtering by:
     • fromDate (optional, flexible format like yyyy-MM-dd or yyyy-MM-dd'T'HH:mm:ss.SSSSSS)
     • toDate (optional)
     • keyword (optional)
   • Implement pagination for the results, allowing for flexible page size and number.

3. Service and Repository:

   • LogsService: Create a service that processes the log retrieval logic.
   • LogsRepository: Implement a mock repository that returns pre-defined log data for testing, with support for filtering and pagination.

4. Validation:

   • Add validation for logStream to ensure only valid stream types are accepted.
   • Handle validation errors using a custom global exception handler (GlobalExceptionMapper), with detailed error messages when invalid data is provided.
   • Allow flexible datetime input formats (yyyy-MM-dd and yyyy-MM-dd'T'HH:mm:ss.SSSSSS).

5. Mock Data:

   • Provide mock log data with varied log streams, dates, and severities.
   • Ensure pagination works properly with larger datasets.

Acceptance Criteria:

• Logs can be retrieved by stream, date range, and keyword.
• The system properly handles validation errors for invalid log streams.
• Logs are returned in a paginated format.
• The /logs/streams endpoint returns all available log streams.
• Flexible date-time formats are supported.
• Unit tests are implemented to cover the functionality and validation.