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SIENTIAPDE-1243: Rename project from 'laborious' to 'model-manager' across codebase and configuration. This includes updating project names in environment variables, Makefiles, README, metrics, and Helm chart values.

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Bruno Domingues
2025-10-01 14:41:24 -03:00
parent aba4a3f1a5
commit bc4d98f78d
11 changed files with 45 additions and 45 deletions
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README.md
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@@ -21,7 +21,7 @@ A comprehensive AI model management platform for the complete machine learning l
## Architecture
The Laborious system uses a Temporal-based workflow architecture with clear separation of concerns and robust error handling. The architecture is designed for high availability, scalability, and operational excellence in production ML environments.
The Model Manager system uses a Temporal-based workflow architecture with clear separation of concerns and robust error handling. The architecture is designed for high availability, scalability, and operational excellence in production ML environments.
### Architecture Principles
@@ -428,7 +428,7 @@ flowchart LR
## 📦 How to Run
### Running the Laborious Application
### Running the Model Manager Application
Use the provided script to run the application locally:
@@ -443,7 +443,7 @@ chmod +x run_local.sh
The script will:
- Activate the virtual environment
- Load environment variables from `.env`
- Start the laborious worker application
- Start the model-manager worker application
### Running Tests and Coverage
@@ -495,7 +495,7 @@ if [ -f .env ]; then
export $(cat .env | grep -v '^#' | xargs)
fi
# Start the laborious worker
# Start the model-manager worker
python -m model_manager.worker.worker
```
@@ -525,25 +525,25 @@ pytest tests/workflow/test_predictions_batch.py
## 📊 Monitoring and Metrics
The Laborious system exposes comprehensive Prometheus metrics for operational visibility and performance monitoring:
The Model Manager system exposes comprehensive Prometheus metrics for operational visibility and performance monitoring:
### Application Health Metrics
- `app_up`: Application health status (1=healthy, 0=unhealthy)
- Labels: `pod_id`
### Prediction Operation Metrics
- `laborious_predictions_written_count`: Counter for successful prediction exports
- `model_manager_predictions_written_count`: Counter for successful prediction exports
- Labels: `pod_id`, `model_name`, `pipeline_name`
- `laborious_prediction_confidence_monitor`: Gauge for current prediction confidence levels
- `model_manager_prediction_confidence_monitor`: Gauge for current prediction confidence levels
- Labels: `pod_id`, `model_name`, `pipeline_name`
- `laborious_prediction_response_time_monitor`: Histogram for prediction response times
- `model_manager_prediction_response_time_monitor`: Histogram for prediction response times
- Labels: `pod_id`, `model_name`, `pipeline_name`
- Buckets: [0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 2.0, 5.0, 10.0]
### OPC Export Metrics
- `laborious_prediction_opc_writing_count`: Counter for OPC server write operations
- `model_manager_prediction_opc_writing_count`: Counter for OPC server write operations
- Labels: `pod_id`, `model_name`, `pipeline_name`, `opc_server_id`
- `laborious_prediction_opc_writing_response_time_monitor`: Histogram for OPC write response times
- `model_manager_prediction_opc_writing_response_time_monitor`: Histogram for OPC write response times
- Labels: `pod_id`, `model_name`, `pipeline_name`, `opc_server_id`
- Buckets: [0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 2.0, 5.0, 10.0]
@@ -559,7 +559,7 @@ The Laborious system exposes comprehensive Prometheus metrics for operational vi
| Variable | Description | Default | Required |
|----------|-------------|---------|----------|
| `TEMPORAL_HOST` | Temporal server address | `localhost:7233` | Yes |
| `TEMPORAL_NAMESPACE` | Temporal namespace | `laborious` | No |
| `TEMPORAL_NAMESPACE` | Temporal namespace | `model-manager` | No |
| `POSTGRES_HOST` | PostgreSQL hostname | `localhost` | Yes |
| `POSTGRES_PORT` | PostgreSQL port | `5432` | Yes |
| `POSTGRES_USER` | PostgreSQL username | `sientia` | Yes |
@@ -585,7 +585,7 @@ The Laborious system exposes comprehensive Prometheus metrics for operational vi
| `MONGODB_DATABASE_NAME` | MongoDB database name | `sientia` | Yes |
| `MONGODB_TTL_INDEX_HOURS` | MongoDB TTL index hours | `1` | No |
| `LOG_LEVEL` | Application log level | `INFO` | No |
| `PROJECT_NAME` | Project name for metrics | `laborious` | No |
| `PROJECT_NAME` | Project name for metrics | `model-manager` | No |
| `HTTP_METRICS_PORT` | Prometheus metrics port | `9090` | No |
| `HTTP_SDK_METRICS_PORT` | Temporal SDK metrics port | `9091` | No |
| `POD_ID` | Kubernetes pod identifier | `None` | No |
@@ -838,4 +838,4 @@ For support and questions:
---
**Note**: The Laborious system is designed for production use in industrial ML environments. Ensure proper security configuration and network isolation for production deployments.
**Note**: The Model Manager system is designed for production use in industrial ML environments. Ensure proper security configuration and network isolation for production deployments.