Payload Shapes

This article assumes you've completed the Getting Started guide and understand the data modeling concepts.

Payload shapes define the structure and validation rules for message payloads. While built-in shapes handle most time-series data, custom shapes enable relational data modeling for complex business records.

Overview

In the component chain, payload shapes provide the foundation:

Payload Shapes → Data Models → Data Contracts → Data Flows
       ↑
  Value types defined here

UI Capabilities

Payload shapes have no UI component:

Feature	Available	Notes
View shapes	❌	Configuration file only
Create shapes	❌	Edit config.yaml directly
Edit shapes	❌	Modify config.yaml
Built-in shapes	✅	Always available, no configuration needed

Configuration location: Select your instance under Instances in the menu, press ..., then Config File. Find payload shapes under the payloadShapes: section

Built-in Shapes

UMH provides three built-in shapes that handle 90% of industrial data:

timeseries-number

For numeric sensor data and measurements.

Structure:

{
  "timestamp_ms": 1733904005123,
  "value": 42.5
}

Use cases: Temperature, pressure, speed, counts, any numeric measurement

timeseries-string

For text-based status and identifiers.

Structure:

{
  "timestamp_ms": 1733904005123,
  "value": "running"
}

Use cases: Machine states, batch IDs, product codes, operator names

timeseries-boolean

For on/off process values.

Structure:

{
  "timestamp_ms": 1733904005123,
  "value": true
}

Use cases: Machine running, alarm active, valve open/closed, any true/false state

When to Use Custom Shapes

Custom shapes are specifically for relational data - business records with multiple related fields that must stay together.

Time-series vs Relational:

Data Type	Shape	Example
Single values over time	Built-in timeseries-*	Temperature readings
Complex business records	Custom shape	Work orders, quality inspections

Learn more: Payload Formats

Configuration

Access configuration via: Instances → Select instance → ... → Config File

Defining Custom Shapes

payloadShapes:
  work-order:    # Shape name (referenced in models)
    description: "Work order record"
    fields:
      orderId:
        _type: string
      productId:
        _type: string
      quantity:
        _type: number
      status:
        _type: string    # created/in-progress/completed
      operatorId:
        _type: string
      timestamp:
        _type: string    # ISO 8601 format

Key points:

• Field types are string, number, boolean (see Data Model Type Definitions)
• All fields are required
• Shape names must be unique

Using Custom Shapes in Models

Reference custom shapes in your data models to create CRUD-like endpoints:

dataModels:
  - name: work-order
    version:
      v1:
        structure:
          create:
            _payloadshape: work-order    # Custom shape for new orders
          update:
            _payloadshape: work-order    # Same shape for updates
          delete:
            _payloadshape: work-order    # Or simplified delete shape

This creates topics like:

• enterprise.site._work_order_v1.create - New work orders
• enterprise.site._work_order_v1.update - Update existing orders
• enterprise.site._work_order_v1.delete - Delete orders

Processing Relational Data

Example: Processing Work Orders

// In nodered_js processor for work order creation
msg.meta.data_contract = "_work_order_v1";
msg.meta.tag_name = "create";  // Maps to the 'create' endpoint

// Build work order record
msg.payload = {
  orderId: "WO-" + Date.now(),
  productId: msg.product,
  quantity: msg.qty,
  status: "created",
  operatorId: msg.operator,
  timestamp: new Date().toISOString()
};

return msg;

This creates a message at enterprise.site._work_order_v1.create with the complete work order data.

Relationship to Other Components

Payload shapes are referenced by data models, which are then enforced by data contracts.

Next Steps

• Define structure: Data Models - Create hierarchies using shapes
• Enforce validation: Data Contracts - Make shapes mandatory
• Build pipelines: Data Flows - Process data with bridges