Skip to main content
Version: 2.0
UNS Trigger Node interface

UNS trigger node

UNS Trigger Node

Overview

The UNS Trigger Node automatically initiates MaestroHub pipelines when data is published to matching Unified Namespace topics. Unlike the UNS connector nodes which publish, fetch, or search within an already-running pipeline, the UNS Trigger starts new pipeline executions in response to incoming data events — enabling fully event-driven automation on your UNS infrastructure.


Core Functionality

What It Does

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

1. Event-Driven Pipeline Execution Start pipelines automatically when data is published to matching UNS topics, without manual intervention or polling. Perfect for reacting to real-time production data, equipment state changes, and cross-system data flows.

2. Flexible Topic Matching with Wildcards Subscribe to specific topics or use MQTT-style wildcards (+ and #) to match multiple topics with a single pattern. Multiple topic patterns can be configured on a single trigger.

3. Data Payload Passthrough Incoming UNS data (topic, payload, and timestamp) is passed directly to the pipeline, making it available to all downstream nodes via the $trigger variable.


Topic Pattern Wildcards

UNS Trigger supports MQTT-style wildcard patterns for flexible topic matching.

WildcardBehaviorExampleMatches
+Matches exactly one levelmHv1.0/+/temperaturemHv1.0/site1/temperature, mHv1.0/site2/temperature
#Matches zero or more levels at the endmHv1.0/enterprise/#mHv1.0/enterprise/site1, mHv1.0/enterprise/site1/area1/temp
+/+Multi-level single wildcardsmHv1.0/+/+/pressureAny site and area combination under pressure
+ and # combinedSingle-level then multi-levelmHv1.0/+/packaging/#Any site, all topics under packaging
Wildcard Validation

The multi-level wildcard (#) must be at the end of the topic pattern. Patterns like mHv1.0/#/temperature are invalid and will fail validation.


Configuration Options

Basic Information

FieldTypeDescription
Node LabelString (Required)Display name for the node on the pipeline canvas
DescriptionString (Optional)Explains what this trigger initiates

Parameters

ParameterTypeDefaultRequiredConstraintsDescription
Topic Patternsstring[][]YesAt least oneUNS topic paths to subscribe to. Supports + and # wildcards.
Trigger Modeselect"always"Noalways / onChangealways: Trigger on every message. onChange: Only trigger when payload differs from last received value per topic.
EnabledbooleantrueNo--Enable/disable the trigger. When disabled, the trigger will not listen for UNS data events.

Change Detection Settings (Trigger Mode = onChange)

When Trigger Mode is set to onChange, additional settings control how payload deduplication works:

ParameterTypeDefaultConstraintsDescription
Max Tracked Topicsnumber10001–10,000Maximum number of distinct topics tracked for change detection. When exceeded, the least recently used topic is evicted.
State TTLselectNo expiry1h / 6h / 12h / 24h / 72h / 168hHow long to remember the last payload per topic. After expiry, the next message always fires. Enterprise edition only.
Change Detection Behavior
  • The first message after a pipeline restart always fires, regardless of trigger mode.
  • In Lite edition, change detection state is held in-memory and resets on restart.
  • In Enterprise edition, state is persisted via JetStream with configurable TTL.

Settings

Description

A free-text area for documenting the node's purpose and behavior. Notes entered here are saved with the pipeline and visible to all team members.

Execution Settings

SettingOptionsDefaultDescription
Timeout (seconds)numberPipeline defaultMaximum execution time for this node (1–600). Leave empty for pipeline default.
Retry on TimeoutPipeline Default / Enabled / DisabledPipeline DefaultWhether to retry the node if it times out.
Retry on FailPipeline Default / Enabled / DisabledPipeline DefaultWhether to retry on failure. When Enabled, shows Advanced Retry Configuration.
On ErrorPipeline Default / Stop Pipeline / Continue ExecutionPipeline DefaultBehavior when node fails after all retries.

Advanced Retry Configuration (visible when Retry on Fail = Enabled)

FieldTypeDefaultRangeDescription
Max Attemptsnumber31–10Maximum retry attempts.
Initial Delay (ms)number1000100–30,000Wait before first retry.
Max Delay (ms)number1200001,000–300,000Upper bound for backoff delay.
Multipliernumber2.01.0–5.0Exponential backoff multiplier.
Jitter Factornumber0.10–0.5Random jitter (+-percentage).

Validation Rules

The UNS Trigger Node enforces these validation requirements:

Parameter Validation

Topic Patterns

  • At least one topic pattern must be provided
  • Each topic pattern must be a non-empty string
  • Multi-level wildcard (#) must be at the end of the pattern (e.g., mHv1.0/enterprise/# is valid, mHv1.0/#/temperature is not)

Node Label

  • Must be provided and non-empty

Usage Examples

Real-Time Production Monitoring

Scenario: React to live production metrics published to the UNS.

Configuration:

  • Label: Production Metrics Monitor
  • Topics: mHv1.0/enterprise/plant-1/+/production/#
  • Trigger Mode: always
  • Enabled: true

Downstream Processing:

  • Parse payload to extract OEE metrics
  • Compare against target thresholds
  • Update dashboard via REST API
  • Send alerts if metrics fall below targets

Equipment State Change Detection

Scenario: Trigger workflows only when equipment state actually changes, ignoring duplicate readings.

Configuration:

  • Label: Equipment State Watcher
  • Topics: mHv1.0/+/+/equipment/+/state
  • Trigger Mode: onChange
  • Max Tracked Topics: 5000
  • Enabled: true

Downstream Processing:

  • Identify which equipment changed state
  • Log state transition to database
  • Notify maintenance team for fault states
  • Update digital twin model

Cross-Plant Data Aggregation

Scenario: Aggregate quality data from multiple plants for centralized analytics.

Configuration:

  • Label: Quality Data Aggregator
  • Topics: mHv1.0/enterprise/+/quality/#
  • Trigger Mode: always
  • Enabled: true

Downstream Processing:

  • Extract plant identifier from topic path
  • Normalize quality metrics across plants
  • Write aggregated data to InfluxDB
  • Generate cross-plant quality reports