Triggers Overview

Triggers are post-execution actions that automatically send your scraped data to external destinations after your automation finishes running. Instead of manually exporting data and uploading it somewhere, triggers handle the delivery for you — automatically, every single time your project runs.

Think of triggers as the “delivery trucks” of your automation. Your automation collects the data (the “packages”), and triggers ship that data to wherever it needs to go: a database, a cloud storage bucket, a BI dashboard, an email inbox, or any of 30+ other destinations.

How Triggers Work

Triggers follow a simple, predictable lifecycle:

1. Your automation runs. Commands execute, data is extracted, and datasets are populated.
2. The run completes. The project finishes with a status of completed or failed.
3. RTILA checks for triggers. If your project has triggers configured, RTILA prepares to execute them.
4. Triggers execute sequentially. Each trigger runs one after another, in the order you arranged them.
5. Data flows between triggers. Each trigger can pass its output to the next trigger using output variables.
6. Delivery is complete. Your data arrives at its destination.

Sequential Execution

Triggers run sequentially, not in parallel. This means:

• Trigger 1 completes before Trigger 2 starts.
• If Trigger 1 fails, Trigger 2 still runs (unless you configure otherwise).
• Each trigger’s output is available to subsequent triggers via output variables.

This sequential design ensures data integrity. If Trigger 1 writes data to a database and Trigger 2 sends a notification about that data, the notification will always reference data that has already been written.

When Triggers Fire

Run Status	Triggers Fire?
completed	✅ Yes — all triggers execute
failed	✅ Yes — triggers still execute (data from partial runs is delivered)
stopped	❌ No — user stopped the run before completion
killed	❌ No — run was force-terminated

Trigger Categories

RTILA X provides 13 trigger categories with 35+ individual trigger types, covering virtually every data destination you can imagine.

#	Category	Triggers	Description
1	APIs / Webhooks	REST API, GraphQL API, SOAP API	Send data to any web API endpoint
2	Cloud Storage	AWS S3, GCP Storage, Azure Blob	Upload files to cloud storage buckets
3	Databases	PostgreSQL, MySQL, MongoDB	Write data directly to databases
4	Email	SMTP	Send email notifications with data
5	File Formats	Export to File, Convert Format, Compress File, Parquet Export, XML Processing, JSONL Export	Export, convert, and compress data files
6	File Transfer	SFTP, FTPS, WebDAV	Transfer files to remote servers
7	Messaging Queues	RabbitMQ, Kafka, AWS SQS	Publish messages to message queues
8	Spreadsheets	Google Sheets, Excel	Write data to spreadsheets
9	BI Tools & Alerting	Power BI, Tableau, Slack, Teams, Generic Webhook	Send alerts and data to BI platforms
10	ITSM, PM & ERP	JIRA, ServiceNow, SAP	Create tickets and records in enterprise tools
11	Cloud Orchestration	Azure Data Factory, Dataiku, Airflow	Trigger data pipeline runs
12	BI Tools (Extended)	Qlik Sense, Superset, Looker Studio, MicroStrategy	Interact with additional BI platforms
13	Cloud Warehouses & Databases	Snowflake, BigQuery, Databricks, MSSQL, Oracle	Query and write to cloud data platforms

Configuring Triggers

Opening the Trigger Editor

1. Go to Automation Projects in the sidebar.
2. Select the project you want to configure.
3. Click Triggers in the ribbon toolbar.
4. The Trigger Flow view opens.

The Trigger Flow View

The Trigger Flow view shows your triggers as a visual flow diagram:

Project Finish → [Trigger 1] → [Trigger 2] → [Trigger 3] → ...

Each trigger appears as a node (a card) in the flow. Nodes are connected by arrows showing the execution order.

Adding a Trigger

1. In the Trigger Flow view, click the + button (usually at the end of the flow).
2. The Trigger Selector Modal opens, showing all available triggers organized by category.
3. Browse or search for the trigger you need.
4. Click the trigger to add it to your flow.
5. Configure the trigger’s parameters in the panel that appears.

The Trigger Selector Modal

The Trigger Selector Modal displays all 35+ triggers organized into 13 categories. Each trigger shows:

• Name — The trigger name (e.g., “REST API”)
• Description — A brief description of what it does
• Category icon — An icon representing the category

You can search by name or browse by category. Click any trigger to add it to your project’s trigger flow.

Configuring a Trigger

After adding a trigger, you configure its parameters. Each trigger type has its own set of parameters. For example, the REST API trigger requires a URL, method, and optional headers.

Each trigger configuration panel shows:

Element	Description
Trigger name	Editable display name for this trigger
Parameter fields	Type-specific configuration fields
Output variable	The variable name where this trigger’s result is stored
Action buttons	Buttons for cloning, deleting, and reordering

Output Variables

Every trigger can store its result in an output variable. This allows subsequent triggers to access the result of previous triggers.

How Output Variables Work

Trigger 1: REST API → output_variable: "api_response"
Trigger 2: Email → body: "API returned: ${api_response}"

In this example:

1. Trigger 1 calls an API and stores the response in api_response.
2. Trigger 2 sends an email that includes the API response.

You reference output variables using the ${variable_name} syntax, just like project variables.

Common Output Variable Patterns

Pattern	Example
Store API response	api_response → used in email body
Store file path	exported_file → used in SFTP upload
Store database result	insert_result → used in notification
Store conversion result	converted_file → used in cloud upload

Bulk vs. Per-Record Triggers

Triggers are either bulk or per-record:

Type	Description	Examples
Bulk	Runs once with ALL extracted data	Export to File, Parquet Export, XML Processing
Per-record	Runs once for EACH record	REST API, Email, Database Insert

How to Tell

Bulk triggers are indicated with a “Bulk: runs once with all data” badge in the trigger configuration panel.

When to Use Each

Use Bulk When	Use Per-Record When
You want all data in one file	You want each record sent individually
You’re exporting to a file format	You’re sending each record to an API
You’re uploading to cloud storage	You’re inserting each record into a database
You want one email with all data	You want one email per record

Managing Triggers

Reordering Triggers

Triggers execute in the order they appear in the flow. To reorder:

1. Click on a trigger node to select it.
2. Use the ← (move left) and → (move right) arrow buttons in the trigger’s action bar.
3. The trigger moves to its new position in the flow.

Cloning a Trigger

To duplicate a trigger:

1. Click on a trigger node to select it.
2. Click the 📋 (clone) button in the trigger’s action bar.
3. A copy of the trigger is created with the same configuration.
4. The clone appears immediately after the original in the flow.

Deleting a Trigger

To remove a trigger:

1. Click on a trigger node to select it.
2. Click the 🗑️ (delete) button in the trigger’s action bar.
3. Confirm the deletion.
4. The trigger is removed from the flow.

Warning: Deleting a trigger is permanent. If other triggers reference this trigger’s output variable, those references will break.

Trigger Chains (New in v8.3.2)

In v8.3.2, RTILA X introduces Trigger Chains — a new system for building reusable, multi-step post-processing pipelines. Trigger Chains go beyond simple project triggers by offering:

• Visual flow builder with drag-and-drop nodes
• IF/ELSE conditional blocks for branching logic
• Parallel execution groups for concurrent processing
• Scheduling — run trigger chains on a schedule
• Run history with detailed execution tracking
• Webhook triggers — trigger chains from external services

Trigger Chains are configured separately from project triggers. While project triggers fire automatically after a project run, Trigger Chains are standalone pipelines that can be triggered manually, on a schedule, or via webhook.

For complete documentation on Trigger Chains, see:

• Trigger Chains Overview
• Trigger Chain Builder
• Trigger Chain Runs
• Trigger Chain Scheduling
• Webhook Triggers

Tips and Best Practices

Tip	Why It Matters
Test triggers with a small dataset first	Verify your trigger configuration works before running on large datasets.
Use output variables to chain triggers	Pass data between triggers for complex workflows.
Use bulk triggers for file exports	Bulk triggers are more efficient for file-based operations.
Use per-record triggers for APIs	Per-record triggers ensure each record is sent individually.
Add error handling with try_catch	Wrap risky triggers in error handling to prevent failures.
Use descriptive trigger names	Name triggers clearly so you can identify them in the flow.
Test credentials before running	Verify API keys, database credentials, and cloud storage credentials before running.
Monitor trigger execution	Check the execution logs to verify triggers completed successfully.
Use triggers for automation	Instead of manually exporting data, let triggers deliver it automatically.
Combine triggers for complex workflows	Chain multiple triggers to build sophisticated data pipelines.

Complete Trigger Reference

For detailed documentation on every trigger with all parameters, examples, and edge cases, see the following pages:

Page	Triggers Covered
API Triggers	REST API, GraphQL API, SOAP API
Cloud Storage	AWS S3, GCP Storage, Azure Blob
Databases	PostgreSQL, MySQL, MongoDB
Email	SMTP
File Formats	Export, Convert, Compress, Parquet, XML, JSONL
File Transfer	SFTP, FTPS, WebDAV
Messaging Queues	RabbitMQ, Kafka, AWS SQS
Spreadsheets	Google Sheets, Excel
BI Tools & Alerting	Power BI, Tableau, Slack, Teams, Generic Webhook
ITSM, PM & ERP	JIRA, ServiceNow, SAP
Cloud Orchestration	Azure Data Factory, Dataiku, Airflow
Data Stores & Search	Redis, Elasticsearch, Teradata, Sybase
BI Tools (Extended)	Qlik Sense, Superset, Looker Studio, MicroStrategy
Cloud Warehouses	Snowflake, BigQuery, Databricks, MSSQL, Oracle