Realtime Trigger
Available on: >= 0.17.0
React to events as they happen with millisecond latency.
Triggers in Kestra can listen to external events and start a workflow execution when the event occurs. Most of these triggers poll external systems for new events at regular intervals e.g. every second. This works well for data processing use cases. However, business-critical workflows often require reacting to events as they happen with millisecond latency and this is where Realtime Triggers come into play.
What are Realtime Triggers
Realtime triggers listen to events in real time and start a workflow execution as soon as:
- a new message is published to a Kafka topic
- a new message is published to a Pulsar topic
- a new message is published to an AMQP queue
- a new message is published to an MQTT queue
- a new message is published to an AWS SQS queue
- a new message is published to Google Pub/Sub
- a new message is published to Azure Event Hubs
- a new message is published to a NATS subject
- a new item is added to a Redis list
- a new row is added, modified or deleted in Postgres, MySQL, or SQL Server.
How Realtime Triggers Work
As soon as you add a Realtime Trigger to your workflow, Kestra starts an always-on thread that listens to the external system for new events. When a new event occurs, Kestra starts a workflow execution to process the event.
Use Cases
Using Realtime Triggers, you can orchestrate business-critical processes and microservices in real time. This covers scenarios such as:
- fraud and anomaly detection,
- order processing,
- realtime predictions or recommendations,
- reacting to stock price changes,
- shipping and delivery notifications,
- ...and many more use cases that require reacting to events as they happen.
In addition, Realtime Triggers can be used for data orchestration, especially for Change Data Capture use cases. The Debezium Postgres RealtimeTrigger plugin can listen to changes in a database table and start a workflow execution as soon as a new row is inserted, updated, or deleted.
When to use Triggers vs. Realtime Triggers
The table below compares Triggers with Realtime Triggers to help you choose the right trigger type for your use case:
| Criteria | Trigger | Realtime Trigger |
|---|---|---|
| Implementation | Micro-batch | Realtime |
| Event Processing | Batch-process all events received until the poll interval has elapsed | Process each event immediately as it happens |
| Latency | Second(s) or minute(s) | Millisecond(s) |
| Execution Model | Each execution processes one or many events | Each execution processes exactly one event |
| Data Handling | Store all received events in a file | Store each event in a raw format |
| Output format | URI of a file in internal storage | Raw data of the event payload and related metadata |
| Application | Data applications processing data in batch | Business-critical operations reacting to events in real time |
| Use cases | Data orchestration for analytics and building data products | Process and microservice orchestration (real time updates, anomaly detection, order processing) |
How to Use Realtime Triggers
To use Realtime Triggers, simply choose the RealtimeTrigger as a trigger type of your desired service. Here, we use the RealtimeTrigger to listen to new messages in an AWS SQS queue:
id: sqs
namespace: company.team
tasks:
- id: log
type: io.kestra.plugin.core.log.Log
message: "{{ trigger }}"
triggers:
- id: realtime_trigger
type: io.kestra.plugin.aws.sqs.RealtimeTrigger
region: eu-north-1
accessKeyId: "{{ secret('AWS_ACCESS_KEY_ID')}}"
secretKeyId: "{{ secret('AWS_SECRET_ACCESS_KEY') }}"
queueUrl: https://sqs.eu-north-1.amazonaws.com/123456789/MyQueue
Comparison with Realtime Data Processing Engines
It's important to note that Kestra's Realtime Triggers are not intended to be used as a replacement for real-time data processing engines such as Apache Flink, Apache Beam or Google Dataflow.
Those data processing engines excel at stateful streaming applications and complex SQL transformations over real-time data streams.
In contrast, Kestra's Realtime Triggers are stateless, meaning they trigger one workflow execution per event. They are designed primarily to react to events in real time to orchestrate business-critical processes.
Was this page helpful?