sientia-dataops-opc-ingestor/README.md

Sientia DataOps OPC Ingestor

A high-performance, scalable OPC UA data ingestion system designed for industrial data collection and real-time streaming. The OPC Ingestor provides enterprise-grade data acquisition from OPC UA servers with automatic load balancing, fault tolerance, and comprehensive monitoring.

Features

Core Functionality

• OPC UA Integration: Native support for OPC UA servers with secure and unsecured connections
• Automatic Load Balancing: Slot-based architecture for horizontal scaling across multiple instances
• Persistent Storage: MongoDB integration for historical data persistence
• Health Monitoring: Comprehensive Prometheus metrics and health checks
• Fault Tolerance: Automatic failover, reconnection, and error recovery

Advanced Capabilities

• Certificate-based Security: Support for X.509 certificates and private keys
• Dynamic Tag Management: Runtime configuration updates without service interruption
• Resource Coordination: Redis-based slot leasing and instance coordination
• Notification System: Integrated alerting and notification management
• Performance Optimization: Configurable polling intervals and data collection frequencies

Architecture

The OPC Ingestor uses a modular, manager-based architecture designed for scalability and fault tolerance:

┌────────────────────────────────────────────
│   Main App      │    │  IngestorManager │    │   OPC Manager   │
│                 │◄──►│                  │◄──►│                 │
│ - Signal Hand.  │    │ - Slot Mgmt      │    │ - Connections   │
│ - Metrics       │    │ - Load Balancing │    │ - Subscriptions │
│ - Lifecycle     │    │ - Coordination   │    │ - Data Handler  │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                                │
                                ▼
                       ┌──────────────────┐    ┌─────────────────┐
                       │  ResourceManager │    │  DataManager    │
                       │                  │    │                 │
                       │ - Redis Coord.   │    │ - MongoDB Store │
                       │ - Slot Leasing   │    │ - Data Pipeline │
                       │ - Heartbeats     │    │                 │
                       └──────────────────┘    └─────────────────┘

Key Components

• Ingestor: Main application orchestrator managing the overall lifecycle
• IngestorManager: Coordinates slot allocation, OPC server management, and load balancing
• OPC Manager: Handles individual OPC UA server connections and tag subscriptions
• Data Manager: Manages data persistence (MongoDB)
• Resource Manager: Coordinates resource allocation and instance coordination via Redis

🚪 OPC Gateway (SIENTIAPDE-1972)

Alongside the passive ingestion pipeline above, this service also runs an OPC Gateway for on-demand and command-driven interactions with OPC UA servers:

• NATS write consumer: consumes write commands from opc.write (see NATS_WRITE_SUBJECT) and executes them against the target OPC server (ingestor/adapters/nats_consumer.py, ingestor/engines/write.py).
• On-demand gRPC ReadTag: a gRPC server (ingestor/adapters/grpc_server.py, ingestor/proto/opc_gateway.proto) for synchronous, single-tag reads.
• Scheduled active reads: a polling read engine (ingestor/engines/active_read.py) for tags that need periodic reads outside the subscription pipeline; orchestrator-side wiring lands in SIENTIAPDE-1974.
• Certificate management: client certs for secure OPC connections are fetched from MinIO + a Mongo platform_certificates collection (ingestor/connection/certs.py) rather than shipped in the image.

See docs/deploy-notes.md for the deployment-facing details (env vars, health probe, NetworkPolicy, cert cache) and the # OPC Gateway block in .env.example for the full list of new environment variables.

📋 Prerequisites

• Python 3.11+
• Redis server
• MongoDB server
• OPC UA servers for data collection

Note: External dependencies (Redis, MongoDB) must be available either through:

• Port forwarding from a Kubernetes cluster
• External Docker Compose setup
• Cloud-managed services
• Local installations

️ Installation

Local Development Setup

1. Clone the repository

   git clone <repository-url>
   cd sientia-dataops-opc-ingestor
   

2. Create virtual environment

   python3.11 -m venv venv
   source ./venv/bin/activate
   

3. Install dependencies

   pip install -r requirements.txt
   

4. Create environment configuration file

   cp .env.example .env
   # Edit .env with your connection details
   

5. Configure external dependencies

   You'll need to set up port forwarding or connections to external services. For example:

   # Port forwarding from Kubernetes cluster
   kubectl port-forward svc/redis-master 6379:6379
   kubectl port-forward svc/mongodb 27017:27017
   
   # Or connect to external Docker Compose
   # Ensure services are accessible on localhost with appropriate ports
   

6. Register the OPC UA client certificate (only if connecting to a secured OPC UA server)

   See OPC Client Certificate below.

Usage

Running the Ingestor

Use the provided script to run the application locally:

# Make script executable (first time only)
chmod +x run_local.sh

# Run the application
./run_local.sh

The script will:

• Activate the virtual environment
• Load environment variables from .env
• Start the ingestor application

Running Tests and Coverage

Use the provided script to run tests with coverage:

# Make script executable (first time only)
chmod +x run_coverage.sh

# Run tests with coverage
./run_coverage.sh

The script will:

• Activate the virtual environment
• Run pytest with coverage reporting
• Generate HTML coverage report
• Open the coverage report in your browser

Manual Test Execution

You can also run tests manually:

# Activate virtual environment
source ./venv/bin/activate

# Run all tests
pytest

# Run with coverage
pytest --cov=ingestor --cov-report=html

Populating Redis with OPC Configuration

1. Activate virtual environment

   source ./venv/bin/activate
   

2. Run the Redis feeder

   python simulator/redis-feeder.py
   

The feeder creates sample OPC tag configurations in Redis that the ingestor can discover and manage.

🔐 OPC Client Certificate

OPC UA servers that require secure connections validate the gateway with a single, shared platform X.509 client certificate. Every OPC connection — subscription reads, NATS writes and gRPC reads — uses it with Basic256Sha256 (SIENTIAPDE-1974).

The certificate is never read from the repository or the image. On connect, the CertProvider (ingestor/connection/certs.py):

1. reads the single document of the Mongo collection platform_certificates: {"client_cert": {"minio_object_name": "..."}, "private_key": {"minio_object_name": "..."}};
2. downloads both objects from the MinIO bucket CERT_BUCKET (default streamlit-connectors) into CERT_CACHE_DIR (default /tmp/opc-certs).

Requirements for a server to accept the connection:

• the server's slot config has use_security: true (a slot v1 server with a cert_path is treated the same way; the path itself is ignored);
• the certificate's SAN URI equals the server's server_uri in the slot — it is sent as the client application_uri (KEPServer rejects a mismatch with BadCertificateUriInvalid);
• the server exposes a Basic256Sha256 endpoint and trusts the certificate (e.g. KEPServer: OPC UA Configuration Manager → Trusted Clients → Trust, then restart its runtime).

MinIO is only contacted when a certificate is first needed, so a MinIO outage only affects secured servers, which are retried on the next main-loop iteration.

🧪 Testing

Unit Tests

# Install pytest
pip install pytest

# Run tests
pytest

# Run with coverage
pip install pytest-cov
pytest --cov=ingestor

# Generate HTML coverage report
pytest --cov=ingestor --cov-report=html

Functional Tests

# Run functional tests
pytest tests/functional/

📊 Monitoring and Metrics

The OPC Ingestor exposes comprehensive Prometheus metrics for monitoring:

Application Metrics

• app_up: Application health status
• app_main_loop_total: Main loop execution count
• app_main_loop_duration_seconds: Loop execution time
• app_errors_total: Error count

OPC Server Metrics

• opc_connection_status: Server connection status
• opc_tags_subscribed_current: Number of subscribed tags
• opc_cycles_without_data: Data reception health
• opc_subscriptions_created_total: Subscription count

Resource Management Metrics

• ingestor_slots_managed_current: Slots managed by this instance
• ingestor_active_total: Total active ingestor instances
• redis_connection_status: Redis connection health

Data Processing Metrics

• ingestor_tag_written_count: Data write operations
• redis_operations_total: Redis operation count

OPC Gateway Metrics

• opc_write_total: Active write attempts (NATS-driven), by result
• opc_write_latency_seconds: Active write latency
• opc_active_read_total: Scheduled/on-demand read attempts, by result
• opc_error_by_type_total: OPC errors by type (connection, conversion, session, ...)

⚙️ Configuration

Environment Variables

Variable	Description	Default	Required
REDIS_HOST	Redis server hostname	localhost	Yes
REDIS_PORT	Redis server port	6379	Yes
REDIS_USERNAME	Redis username	None	No
REDIS_PASSWORD	Redis password	None	No
LEASE_TTL	Slot lease time-to-live (seconds)	10	No
HEARTBEAT_TTL	Heartbeat time-to-live (seconds)	20	No
HOSTNAME	Pod identifier	localhost	No
POLL_INTERVAL	Main loop polling interval (seconds)	5	No
MONGODB_URL	MongoDB server address	localhost:27017	Yes
MONGODB_DATABASE	MongoDB database name	sientia	No
MONGODB_USERNAME	MongoDB username	sientia	No
MONGODB_PASSWORD	MongoDB password	sientia	No
HTTP_METRICS_PORT	Prometheus metrics port	9090	No

See the # OPC Gateway block in .env.example (NATS_URL, GRPC_ENABLED, CERT_BUCKET, WRITE_TIMESTAMP, ...) and docs/deploy-notes.md for the gateway-specific environment variables.

OPC Server Configuration

OPC servers are configured by the Orchestrator through Redis, one key per slot (slot:opc_tags:<n>). The gateway reads the slot v2 structure (contract C1): one entry per address, with one names item per collection / tag name / model, so the same address can feed several models under different names. For secured connections set use_security: true (the certificate comes from MinIO, see OPC Client Certificate):

{
  "slot:opc_tags:1": {
    "server1": {
      "name": "server1",
      "server_id": "1",
      "url": "opc.tcp://localhost:4841",
      "server_uri": "urn:sientia:opc-ingestor",
      "use_security": true,
      "subscription_period_ms": 7500,
      "tags": {
        "ns=2;i=2": {
          "frequency": "15000",
          "active_read": {"enabled": false},
          "names": [
            {"collection": "raw_scouter-opcua-orchestrated-pipeline", "tag_name": "Counter", "model_name": "m1", "model_id": "1"},
            {"collection": "raw_scouter-basic-sum-model", "tag_name": "Contador", "model_name": "m2", "model_id": "2"}
          ]
        }
      }
    }
  }
}

The legacy slot v1 (each tag with tag_name + topics, the server with cert_path) is still accepted and converted on read (ingestor/io/slots.py): one names item per topic, and use_security is true when cert_path is set (the path itself is ignored). This lets the gateway and the Orchestrator be deployed in any order. Documents written from a v1 slot have no model_id, exactly as before.

🔧 Development

Project Structure

sientia-dataops-opc-ingestor/
├── ingestor/                 # Main application code
│   ├── managers/            # Component managers
│   │   ├── data_manager.py # Data persistence and export
│   │   ├── ingestor_manager.py # Main coordination
│   │   ├── resource_manager.py # Resource coordination
│   │   └── server_reader.py # OPC UA server reads (SubscriptionEngine + pool)
│   ├── app.py              # Main application entry point
│   ├── ingestor.py         # Core ingestor logic
│   └── metrics.py          # Prometheus metrics definitions
├── simulator/               # OPC simulation and testing tools
├── scripts/                 # Ops scripts (e.g. e2e seed)
├── tests/                   # Test suite
└── requirements.txt         # Python dependencies

Adding New Features

1. Follow the manager pattern for new components
2. Add comprehensive docstrings for all public methods
3. Include Prometheus metrics for monitoring
4. Add unit tests for new functionality
5. Update this README with new features and configuration

🐛 Troubleshooting

Common Issues

1. OPC Connection Failures

   • Verify server URLs and network connectivity
   • Check certificate paths and security settings
   • Review server logs for authentication issues

2. Redis Connection Issues

   • Verify Redis server is running and accessible
   • Check authentication credentials
   • Ensure proper network configuration

3. Performance Issues

   • Monitor Prometheus metrics for bottlenecks
   • Adjust polling intervals and lease TTLs
   • Review OPC server performance and network latency

Debug Mode

Enable debug logging by setting the log level in your environment:

export LOG_LEVEL=DEBUG

Performance Tuning

Key Parameters

• POLL_INTERVAL: Main loop frequency (lower = more responsive, higher = less CPU)
• LEASE_TTL: Slot lease duration (lower = faster failover, higher = more stable)
• HEARTBEAT_TTL: Instance health check frequency
• Tag frequency: OPC tag collection rate (Hz)

Scaling Considerations

• Horizontal Scaling: Deploy multiple ingestor instances for high availability
• Load Distribution: Use Redis-based slot allocation for automatic load balancing
• Resource Limits: Monitor CPU, memory, and network usage
• Database Performance: Optimize MongoDB indexes

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes with comprehensive testing
4. Update documentation and docstrings
5. Submit a pull request

Code Quality Standards

• Follow PEP 8 style guidelines
• Include comprehensive docstrings for all public methods
• Maintain test coverage above 80%
• Use type hints where appropriate
• Follow the established architectural patterns

🆘 Support

For support and questions:

• Check the troubleshooting section above
• Review the metrics and logs for error patterns
• Open an issue in the project repository
• Contact the development team

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Note: This OPC Ingestor is designed for production use in industrial environments. Ensure proper security configuration and network isolation for production deployments.