SIENTIAPDE-1250: Implement experiment tracking activity with status updates, error handling, and model registration. This includes a unified update method, error message truncation, and integration into the main activities orchestrator. (236+, 2-)

README.md

@@ -149,13 +149,20 @@ The Model Manager system uses a Temporal-based workflow architecture with clear
 
 #### **Activities (`model_manager/activities/`)**
 - **Activities**: Main activity orchestrator combining all functionality through multiple inheritance
+- **ExperimentTracking**: ML experiment lifecycle tracking and database operations (extends Postgres)
+  - Unified `update_experiment_run()` method for all experiment status updates
+  - Support for three update types: STATUS, STATUS_WITH_ERROR, MODEL_SAVED
+  - Automatic error message truncation (1024 chars)
+  - Connection pooling and retry logic via Postgres base class
 - **Gates**: Data quality validation and filtering mechanisms
 - **MLFlow**: Model transformation and prediction operations
+- **MinIO**: Object storage operations for file management
 - **Key Features**:
   - Multiple inheritance pattern for unified activity interface
   - Configurable filter policies and validation rules
   - MLFlow model serving integration with configurable flavors
   - Comprehensive error handling and notification integration
+  - Experiment tracking with automatic status management
 
 #### **Data Services (`model_manager/utils/`)**
 - **Connectors Config**: Environment variable-based configuration management