Refactor metrics and imports across multiple files
- Removed unused import of CORE_LABELS in metrics.py.
- Updated import statements in api.py for consistency.
- Cleaned up import order in worker.py for better readability.
- Added missing newline at the end of metrics.py.
- Adjusted formatting in core_scouter.py to ensure proper syntax.
- Removed redundant 'on_conflict' and 'unique_columns' keys from test cases in test_core_scouter.py for clarity.
Refactor PIWebAPIClient and Update Configuration Imports
- Removed outdated PostgreSQL, Redis, MongoDB, and API configuration functions from connectors_config.py.
- Deleted the pi_web_api_client.py file as part of the refactor.
- Updated imports in worker.py and api.py to use the new repository structure.
- Cleaned up scenarios.md by removing obsolete scenarios related to unique constraint violations.
- Commented out the specific version of the sientia-dataops-library in requirements.txt for flexibility.
Refactor imports and enhance timestamp handling in API and test files
- Removed redundant import statements in api.py and prepare_worker.py for cleaner code.
- Updated timestamp format in test cases to include timezone information for consistency.
- Adjusted test configurations to align with new API structure for improved accuracy in data handling.
SIENTIAPDE-1445 Add PI Web API configuration to .env.example and enhance worker setup
- Introduced new environment variables for PI Web API configuration in .env.example.
- Updated prepare_worker.py to utilize a camelCase to kebab-case conversion function for queue naming.
- Enhanced logging in prepare_worker to provide better insights during worker preparation.
- Adjusted execution counts in tests.ipynb for improved notebook state management.
Enhance Activities and API Integration
- Updated Activities class to include API operations for external data ingestion.
- Added API configuration builder to connectors_config.py for environment variable management.
- Integrated API configuration into worker setup.
- Expanded unit tests to cover new API functionality and configuration handling.
- Updated requirements.txt to include pycurl and prometheus-client for enhanced metrics support.
Refactor prepare_worker.py to improve type annotations and code clarity. Update import statements and enhance formatting for better readability. Adjust comments in worker.py for consistency.
SIENTIAPDE-1441: Refactor worker configuration in worker.py to utilize a new prepare_worker function for cleaner setup. Update environment variable names in values.yaml for consistency and clarity, adjusting memory requests and enhancing health check commands for improved application monitoring.
SIENTIAPDE-1442: Enhance Temporal worker configuration by adding environment variables for concurrency limits and poller behavior settings in values.yaml and worker.py for optimized performance.
Refactor initialization of Activities, Gates, and MongoDB classes for improved readability by using multi-line argument formatting. Update related tests to match the new initialization style.
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.
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.
Update requirements and core scouter workflow: comment out old dataops library dependency, change default namespace in worker.py, and enhance timestamp handling in core_scouter.py with DATETIME_FORMAT.
Refactor logging in worker.py to use custom_info and custom_error methods, enhancing log metadata with pod and workflow details for improved observability.
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.
Enable SDK metrics service in values.yaml and update worker.py to initialize SDK metrics server with Prometheus configuration, enhancing observability of the application.
Update replica count in values.yaml, add application status metrics in metrics.py, and implement Prometheus server in worker.py for enhanced observability.
Update sonar-project.properties to exclude worker.py from coverage, enhance error handling in worker.py, and add new tests for error scenarios in test_redis.py and test_mongo.py.
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.
Integrate Druid activity into the Activities class, adding support for Druid configuration and initialization. Update worker and connectors configuration to accommodate Druid, enhancing data processing capabilities.
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.
