Version: 2.0-dev

OPC UA trigger node

OPC UA Trigger Node

Overview

The OPC UA Trigger Node automatically initiates MaestroHub pipelines when monitored OPC UA node values change. Unlike the OPC UA Read connector node which reads values within an already-running pipeline, the OPC UA Trigger starts new pipeline executions in response to value changes—enabling fully event-driven automation without polling.

Core Functionality

What It Does

OPC UA Trigger enables real-time, event-driven pipeline execution by:

1. Event-Driven Pipeline Execution Start pipelines automatically when OPC UA node values change, without manual intervention or polling. Perfect for equipment monitoring, alarm processing, and real-time production data flows.

2. Automatic Subscription Management Subscriptions and monitored items are created and cleaned up automatically—no manual OPC UA subscription management required.

3. Value Change Passthrough Incoming value change notifications are passed directly to the pipeline, making them available to all downstream nodes via the $input variable.

How OPC UA Monitoring Works

OPC UA monitoring is fundamentally different from read operations:

Aspect	Read Operation	Monitor (Subscription)
Model	Request-response (pull)	Event-driven (push)
Execution	One-time value retrieval	Continuous streaming
Lifecycle	Stateless	Stateful subscription
Use Case	On-demand data access	Real-time change detection

When you configure an OPC UA Trigger:

MaestroHub creates a Subscription on the OPC UA server
Monitored Items are registered for each configured node
The server samples nodes at the configured sampling interval
Value changes are queued and published at the publishing interval
Each notification triggers a new pipeline execution

This push-based model is optimized for low-latency, continuous telemetry in industrial environments.

Reconnection Handling

MaestroHub automatically handles connection disruptions to ensure reliable monitoring.

Automatic Recovery

When an OPC UA connection is lost and restored:

Connection Lost: The system detects the disconnection automatically
Connection Restored: Subscriptions and monitored items are automatically recreated
Transparent Recovery: Pipelines continue to receive value changes once the connection is restored—no manual intervention required

What This Means for Your Workflows

Scenario	Behavior
Brief network interruption	Automatic resubscription after reconnection
OPC UA server restart	Subscriptions automatically restored when server comes back online
Session timeout	New session established with all monitors restored
MaestroHub restart	All triggers for enabled pipelines are restored on startup

Queue Size and Data Loss

To minimize data loss during brief outages, configure your Monitor function with appropriate Queue Size settings. Larger queues buffer more notifications but use more server memory.

Configuration Options

Basic Information

Field	Type	Description
Node Label	String (Required)	Display name for the node on the pipeline canvas
Description	String (Optional)	Explains what this trigger initiates

Parameters

Parameter	Type	Required	Default	Description
Connection	Connection ID	Yes	-	The OPC UA connection profile to use for subscribing
Function	Function ID	Yes	-	The OPC UA Monitor function that defines nodes and subscription settings
Enabled	Boolean	No	`true`	When disabled, the subscription is not created even if the pipeline is enabled

Function Requirement

The selected function must be an OPC UA Monitor function type. Read, Write, and Browse functions cannot be used with OPC UA Trigger nodes.

Settings

Basic Settings

Setting	Options	Default	Recommendation
Retry on Fail	true / false	false	Keep disabled for triggers—retries don't apply to event-driven nodes
Error Handling	Stop Pipeline / Continue	Stop Pipeline	Use "Stop Pipeline" to halt on critical failures

Documentation Settings

Setting	Type	Default	Purpose
Notes	Text	Empty	Document the trigger's purpose, expected data formats, or operational context
Display Note in Pipeline	Boolean	false	Show notes on the pipeline canvas for quick reference

Output Data Structure

When an OPC UA node value change triggers pipeline execution, the following data is available to downstream nodes via the $input variable.

Output Format

{
  "type": "opcua_trigger",
  "connectionId": "bf29be94-fc0a-4dc4-8e5c-092f1b74eb4b",
  "functionId": "aef374c3-aa2b-454e-aabc-5657faac5950",
  "enabled": true,
  "node_id": "trigger.opcua-1",
  "message": "OPC UA trigger provides configuration for event-based triggering",
  "payload": {
    "value": 23.5,
    "nodeId": "ns=2;i=123",
    "namespaceIndex": 2,
    "identifier": "i=123",
    "sourceTimestamp": "2024-01-15T10:30:00.000Z",
    "serverTimestamp": "2024-01-15T10:30:00.001Z",
    "statusCode": "Good"
  }
}

Accessing Value Change Data

In downstream nodes, use the $input variable to access the trigger output:

Field	Expression	Description
Node Value	`$input.payload.value`	The current value of the monitored node
Node ID	`$input.payload.nodeId`	Full OPC UA node identifier (e.g., `ns=2;i=123`)
Namespace Index	`$input.payload.namespaceIndex`	Namespace index of the monitored node
Identifier	`$input.payload.identifier`	Node identifier string (e.g., `i=123`, `s=Temperature`)
Source Timestamp	`$input.payload.sourceTimestamp`	When the value was sampled at the source
Server Timestamp	`$input.payload.serverTimestamp`	When the OPC UA server processed the notification
Status Code	`$input.payload.statusCode`	OPC UA status code indicating data quality
Connection ID	`$input.connectionId`	The OPC UA connection profile used
Function ID	`$input.functionId`	The Monitor function that received the notification
Trigger Type	`$input.type`	Always `opcua_trigger`

Working with Values

Access the monitored value directly with $input.payload.value. The value type matches the OPC UA node's data type (number, string, boolean, etc.).

Validation Rules

The OPC UA Trigger Node enforces these validation requirements:

Parameter Validation

Connection ID

Must be provided and non-empty
Must reference a valid OPC UA connection profile
Error: "connectionId is required"

Function ID

Must be provided and non-empty
Must reference a valid OPC UA Monitor function
Function must belong to the specified connection
Error: "functionId is required"

Enabled Flag

Must be a boolean if provided
Error: "enabled must be a boolean"

Settings Validation

On Error

Must be one of: stopPipeline, continueExecution, retryNode
Error: "onError must be a valid error handling option"

Usage Examples

Real-Time Temperature Monitoring

Scenario: Process temperature readings from industrial equipment and trigger alerts when thresholds are exceeded.

Configuration:

Label: Equipment Temperature Monitor
Connection: Factory OPC UA Server
Function: Monitor function subscribing to temperature nodes with 100ms publishing interval
Enabled: true

Downstream Processing:

Extract temperature from $input.payload.value
Compare against threshold limits
Send alert if threshold exceeded
Store reading in time-series database

Production Counter Tracking

Scenario: Track production counts in real-time for OEE calculations.

Configuration:

Label: Production Counter Tracker
Connection: PLC OPC UA Server
Function: Monitor function for counter nodes with queue size of 50 to capture all increments
Enabled: true

Downstream Processing:

Extract counter value and timestamp
Calculate production rate from consecutive values
Update production dashboard
Store in historian for shift reports

Alarm Condition Processing

Scenario: React immediately when equipment alarms activate.

Configuration:

Label: Equipment Alarm Handler
Connection: SCADA OPC UA Server
Function: Monitor function for alarm nodes with sampling interval of 0 (fastest)
Enabled: true

Downstream Processing:

Check alarm state from $input.payload.value
Look up alarm details from alarm database
Send notification to operators
Log alarm event with timestamps for compliance

Multi-Node Quality Monitoring

Scenario: Monitor multiple quality parameters from a single production line.

Configuration:

Label: Quality Parameter Monitor
Connection: Quality System OPC UA Server
Function: Monitor function with nodes for temperature, pressure, flow rate, and vibration
Enabled: true

Downstream Processing:

Identify which node changed from $input.payload.identifier
Route to appropriate quality check logic
Update quality dashboard
Trigger corrective action if out of spec

Best Practices

Subscription Configuration

Configure your Monitor function with appropriate Publishing Interval for your use case (100–1000ms typical)
Set Sampling Interval equal to or faster than publishing interval for critical nodes
Use Queue Size > 1 for nodes where every change must be captured

Designing for Reliability

Practice	Rationale
Use appropriate Queue Size	Larger queues buffer notifications during network hiccups
Set Discard Oldest = true	Ensures you always see the most recent value
Keep monitored node count reasonable	Each node adds server-side sampling overhead
Group related nodes in one function	Reduces subscription overhead while maintaining logical grouping

Error Handling Strategies

For Critical Workflows:

Set On Error to stopPipeline
Monitor pipeline execution failures
Implement alerting for stopped pipelines

For Best-Effort Processing:

Set On Error to continueExecution
Log failed executions for later analysis
Ensure downstream nodes handle partial failures gracefully

Performance Considerations

Scenario	Recommendation
High-frequency changes	Increase publishing interval to batch notifications; use larger queue sizes
Many monitored nodes	Split across multiple Monitor functions; consider sampling intervals
Critical real-time data	Use sampling interval of 0; minimize publishing interval
Resource-constrained OPC UA servers	Reduce number of monitored items; increase sampling intervals

Enable vs. Disable

Use the trigger's Enabled parameter to temporarily pause monitoring without changing pipeline state
Disable triggers during maintenance windows to prevent processing
Document the reason for disabled triggers in the node's Notes field

Overview​

Core Functionality​

What It Does​

How OPC UA Monitoring Works​

Reconnection Handling​

Automatic Recovery​

What This Means for Your Workflows​

Configuration Options​

Basic Information​

Parameters​

Settings​

Output Data Structure​

Output Format​

Accessing Value Change Data​

Validation Rules​

Parameter Validation​

Settings Validation​

Usage Examples​

Real-Time Temperature Monitoring​

Production Counter Tracking​

Alarm Condition Processing​

Multi-Node Quality Monitoring​

Best Practices​

Subscription Configuration​

Designing for Reliability​

Error Handling Strategies​

Performance Considerations​

Enable vs. Disable​

Overview

Core Functionality

What It Does

How OPC UA Monitoring Works

Reconnection Handling

Automatic Recovery

What This Means for Your Workflows

Configuration Options

Basic Information

Parameters

Settings

Output Data Structure

Output Format

Accessing Value Change Data

Validation Rules

Parameter Validation

Settings Validation

Usage Examples

Real-Time Temperature Monitoring

Production Counter Tracking

Alarm Condition Processing

Multi-Node Quality Monitoring

Best Practices

Subscription Configuration

Designing for Reliability

Error Handling Strategies

Performance Considerations

Enable vs. Disable