App Parameters

Expose configurable parameters to users without building a full web UI. Define a form using env-template.yml and IronFlock renders it automatically.

When to Use Parameters

Use parameters for simple configuration that users need to adjust per device or per group:

• Sensor recording intervals
• Data endpoint URLs
• Alert thresholds
• Feature toggles
• API keys and credentials

For more complex configuration (robot training, camera AI setup, hardware configuration), build a custom Edge User Interface instead.

Defining Parameters

Create an env-template.yml file in the .ironflock/ directory:

RECORDING_INTERVAL:
    label: "Recording Interval (seconds)"
    defaultValue: 5
    type: numeric
    optional: true
 
ALERT_THRESHOLD:
    label: "Temperature Alert Threshold (°C)"
    defaultValue: 80
    type: numeric
    optional: true
 
API_ENDPOINT:
    label: "Data API Endpoint"
    defaultValue: "https://api.example.com/data"
    type: text
    optional: true
 
ENABLE_DEMO:
    label: "Enable Demo Data"
    defaultValue: true
    type: boolean
    optional: true
 
DATA_FORMAT:
    label: "Output Format"
    defaultValue: "json"
    type: select
    options:
        - json
        - csv
        - xml
    optional: true
 
SECRET_KEY:
    label: "API Secret Key"
    defaultValue: ""
    type: text
    secret: true
    optional: true

Parameter Types

How Parameters Reach Your App

Parameters are injected as Linux environment variables in your container:

import os
 
interval = int(os.environ.get("RECORDING_INTERVAL", 5))
threshold = float(os.environ.get("ALERT_THRESHOLD", 80))

const interval = parseInt(process.env.RECORDING_INTERVAL || "5");
const threshold = parseFloat(process.env.ALERT_THRESHOLD || "80");

Large Parameters

Parameters exceeding 20 KB are not set as environment variables due to system limitations. Instead, all parameters (including large ones) are always available as files:

/data/env/PARAMETER_NAME.txt

Development Mode

The defaultValue specified in env-template.yml is used when running the app in development mode. This provides a consistent development experience without requiring manual parameter configuration.

Mass Parametrization

When parameters are set at the device group level, they apply to all devices in the group simultaneously. This is ideal for:

• Setting a common S3 bucket across all data collection devices
• Updating AI model parameters project-wide
• Changing sensor configurations for an entire production line

Parameters can be set even when devices are offline — they are applied when the device reconnects.