Update project configuration and dependencies
- Added .mypy_cache and .cursor to .gitignore.
- Changed asyncio_default_fixture_loop_scope and asyncio_default_test_loop_scope to "session" in pyproject.toml.
- Updated e2e testing dependencies in requirements-dev.txt, replacing fakeredis and mongomock with pytest-httpserver.
- Updated requirements.txt to use sientia_do instead of a specific git commit.
- Modified sonar-project.properties to remove a file from coverage exclusions.
- Enhanced E2E test fixtures in e2e/conftest.py for better container management.
- Cleaned up e2e test files related to CoreScouter and PIWebAPIScouter workflows.
Enhance Redis activity by formatting set and get operations for improved readability and consistency. Update tests to include metadata in assertions for better verification of Redis interactions.
Refactor notification methods in Gates, MongoDB, and Redis classes to use asynchronous send_notification_async. Update related tests to ensure proper async handling and verification of notifications.
Update environment configuration and refactor activities to include metrics controller. Remove Kafka settings and adjust Redis and MongoDB initialization. Update tests to reflect changes in initialization and metrics tracking.
Refactor MongoDB, Redis, and Gates classes to extend SientiaMonitoring instead of BaseActivity. Update requirements to point to local dataops library path. Implement repository pattern for MongoDB and Redis operations, enhancing code organization and maintainability.
Implement tag value registration in Gates activity and update related tests. Enhanced the write_metrics method to process and register tag values, improving metrics tracking. Adjusted tests to validate new functionality.
Update Redis and CoreScouter to incorporate 'fill_missing_tags' parameter in data processing. Adjusted related tests to ensure proper handling of missing tags, enhancing overall functionality and consistency across workflows.
SIENTIAPDE-1318: Add support for filling missing tags in Redis data processing. Enhanced the Redis class to include a new parameter for handling missing tags, ensuring that absent tags are filled with None in the data package.
Update .gitignore and refactor metrics.py, activities.py, and gates.py for improved clarity and consistency. Added coverage.xml and cache directories to .gitignore. Standardized string formatting and parameter handling in metrics and activities classes, enhancing code readability. Removed the deprecated faker.py file and adjusted related tests accordingly.
Remove deprecated files and configurations, including .env, Dockerfile, docker-compose.yml, and client-schedule.py. Update README.md to reflect new architecture and features, enhancing clarity on system capabilities and workflows. Adjust values.yaml for image tag and replica count, and improve code documentation across various modules for better maintainability.
Enhance timestamp handling in Redis and CoreScouter workflows by updating to DATETIME_FORMAT_MS_WITH_TZ. Modify tests to reflect new timestamp format, ensuring consistency across data structures and improving overall datetime management.
Refactor Redis activity to utilize the new 'now' function for timestamp generation, ensuring consistency with updated datetime handling. This change replaces the direct use of 'datetime.now()' with 'now()' from the temporal constants.
Update sientia-dataops-library version to 1.4.3 and refactor timestamp handling in MongoDB and Redis activities to use DATETIME_FORMAT constants for improved consistency. Enhance unit tests to reflect these changes.
Enhance logging in Gates, MongoDB, and Redis activities by replacing debug statements with info level logs, improving observability of data processing steps. Update worker configuration to adjust concurrency settings and enable autoscaling for task polling.
Update dependencies and improve observability by changing logger imports. Bump sientia-dataops-library version to 1.4.1 and update image tag to 0.4.2 in values.yaml.
Update image tag to 0.4.0 in values.yaml, modify GITHUB_BRANCH for SIENTIAPDE-1169, and enhance Redis activity to handle model tags for improved data retention.
Update requirements for sientia-dataops-library to version 1.3.7, add ServiceMonitor configuration for Prometheus in values.yaml, and refactor pod_id usage in Gates and Redis activities for improved consistency in metric tracking.
Implement store_data_package method in Redis activity for debug data storage. Update CoreScouter workflow to conditionally call store_data_package based on debug flag. Enhance tests for store_data_package functionality and error handling.
Enhance Gates and Redis activities by adding metadata parameter to apply_aggregation and notification methods. Refactor notification handling to use send_notification for improved consistency. Update tests to reflect changes in notification method calls and ensure proper functionality with new metadata integration.
Refactor Activities class to remove Kafka and Druid dependencies, simplifying initialization. Update values.yaml to set replica count to 1 for reduced resource usage. Adjust Redis activity to set TTL to None for better data retention. Remove unused Kafka and Druid activity files and their associated tests, streamlining the codebase.
Update sientia-dataops-library version to 1.2.0 in requirements.txt; refactor logging in activities to use a unified Logger instance and include metadata in log messages across various activities.
Update environment configuration and refactor activity imports
- Changed Kafka, Redis, and Temporal host configurations to use localhost.
- Updated the version reference for the sientia-dataops-library in requirements.txt.
- Refactored import paths for activities to align with new module structure.
- Removed unused base.py and postgres.py files.
- Updated logger and policies imports to reflect new module locations.
- Adjusted values.yaml for branch and log level settings.
Implement workflows for fake data generation, scouter processing, and core scouter operations
- Added `FakeData` workflow to generate random data and send it to a Kafka topic.
- Implemented `Scouter` workflow to load data from Kafka and trigger the core scouter workflow.
- Created `CoreScouter` workflow to process data through quality gates, aggregation, and export to PostgreSQL.
- Developed comprehensive unit tests for activities and workflows, ensuring proper functionality and error handling.
- Enhanced Redis and Postgres activities with robust testing for data handling and error notifications.
- Introduced quality filters for data validation and implemented tests to verify their functionality.
