FlowX.AI Scheduler
The Scheduler is part of the core extensions of the FlowX.AI platform. It can be easily added to your custom FlowX deployment to enhance the core platform capabilities with functionality specific to scheduling messages.
The service offers the possibility to schedule a message that you only need to process after a configured time period.
It can be quickly deployed on the chosen infrastructure and then connected to the FLOWX.AI Engine through Kafka events.
Using the scheduler
After deploying the scheduler service in your infrastructure, you can start using it to schedule messages that you need to process at a later time.
One such example would be to use the scheduler service to expire processes that were started but haven’t been finished.
First you need to check the configured kafka topics match the ones configured in the engine deployment.
For example the engine topics KAFKA_TOPIC_PROCESS_SCHEDULE_OUT_SET
and KAFKA_TOPIC_PROCESS_SCHEDULE_OUT_STOP
must be the same with the ones configured in the scheduler at KAFKA_TOPIC_SCHEDULE_IN_SET
and KAFKA_TOPIC_SCHEDULE_IN_STOP
environment variables.
When a process is scheduled to expire, the engine sends the following message to the scheduler service (on the topic KAFKA_TOPIC_SCHEDULE_IN_SET
):
The scheduled time should be defined as java.time.Instant
.
At the scheduled time, the payload will be sent back to the response topic defined in the message, like so:
If you don’t need the scheduled message anymore, you can discard it by sending the following message (on the topic KAFKA_TOPIC_SCHEDULE_IN_STOP
)
These fields, applicationName
and applicationId
are used to uniquely identify a scheduled message.
Scheduler setup
Steps needed in order to deploy and set up the service
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