Overview
Streams by UnifyApps provides powerful event streaming capabilities for real-time data processing and event-driven automation. This functionality enables you to publish, consume, and process events across your applications in a reliable and scalable way, facilitating seamless communication between different components of your system.
Use Cases
Real-time Event Processing: Stream events from multiple sources and trigger automated workflows based on these events. This enables immediate responses to business events, system changes, or user actions.
Scheduled Event Publishing: Schedule events to be published at specific times or with configured delays, allowing for time-based automation and orchestration of complex business processes.
Batch Processing: Collect events in batches for efficient processing, enabling optimized handling of high-volume data streams without overloading your systems.
Message Queueing and Guaranteed Delivery: Ensure reliable delivery of critical events with key-based processing guarantees, maintaining the order of related events and preventing data loss.
Actions
Polls for new events from stream
This action allows you to consume new events from a specified stream, triggering subsequent automation steps for each event or batch of events.
Input Fields:
Select Stream: Choose the stream to poll for new events
Repeat mode: Select how events should be processed
Batch items: Process multiple events in predefined batches
Consumer Group: Optionally specify a consumer group for distributed processing
Batch size: Define how many events to process in each batch (when using batch mode)
When to use:
For continuous monitoring of event streams
To trigger automated workflows based on incoming events
For processing new events as they arrive in the system
Publish event to stream
This action enables you to send events to a specified stream for real-time processing by consumers.
Input Fields:
Select Stream: Choose the target stream for publishing
Key: Optional identifier that guarantees events with the same key are processed in order
Event data: The payload to be published to the stream
When to use:
To trigger downstream processes in real-time
For broadcasting system changes to multiple consumers
To initiate event-driven workflows
Publish event to stream at
This action allows you to schedule events to be published at a specific time in the future.
Input Fields:
Select Stream: Choose the target stream for publishing
Key: Optional identifier that guarantees events with the same key are processed in order
Time to publish at: Specify the exact future date and time when the event should be published
Event data: The payload to be published to the stream
When to use:
For scheduling time-sensitive operations
To trigger workflows at specific times
For implementing time-based business logic
Publish event to stream with delay
This action publishes events to a stream after a specified delay period.
Input Fields:
Select Stream: Choose the target stream for publishing
Key: Optional identifier that guarantees events with the same key are processed in order
Time delayed for: Specify the delay duration
Unit: Select the time unit (seconds, minutes, hours, etc.)
Event data: The payload to be published to the stream
When to use:
To implement retry mechanisms with increasing delays
For processes that need to wait before proceeding
When orchestrating sequential workflows with timing requirements
Update DLQ status for stream
This action allows you to update the Dead Letter Queue (DLQ) status for an event in a stream, handling message processing failures and retries.
Input Fields:
Select Stream: Choose the stream containing the event
Event Id: Specify the ID of the event to update
Select DLQ Reason: Choose the reason for the status update
When to use:
To manage failed event processing
For implementing custom retry logic
When troubleshooting event processing issues
Output Examples
After executing a Streams action, you can track the status and results of the operation in the Output tab.
Common Output Fields:
Interrupted: Indicates if the process was interrupted
Resumed At: When an interrupted process was resumed
Success: Confirmation of successful completion
Implementation Steps
Add a Streams by UnifyApps action:
Start with a trigger or preceding action
Click the "
+" button to add a new actionSelect "
Streams by UnifyApps" from the app listChoose the specific action you need
Configure the action:
Select the target stream
Configure event keys, batch settings, or timing as needed
Define event data to be processed or published
Connect with downstream actions:
Use the output from Streams actions to trigger subsequent steps
Process event data in follow-up actions
Implement conditional logic based on streaming results
Monitor and handle exceptions:
Use DLQ management for error handling
Implement retry logic for failed events
Set up notifications for critical stream processing issues
