@Marvin I have a prefect flow that has a sensor that listens to an sqs queue for a specific message then processes data. I want to have multiple instances of this flow running for load balancing purposes. How can I prevent each flow’s listener from processing the same message, resulting in running the pipeline 3 times if there are 3 instances of the flow running

To handle multiple instances of a flow running for load-balancing purposes and ensure each instance does not process the same message from an SQS queue, you can utilize concurrency limits within Prefect. Here are the steps you can follow: 1. Concurrency Limits: Set a concurrency limit to ensure that only one task or flow instance processes a given message at a time. 2. Work Pools: Utilize work pools to define and manage concurrent work, maintain priority, and prevent overlap in processing. Here's a brief explanation of how you can set this up: 1. Define Concurrency Limit:

python
    from prefect import concurrency, flow, task
    
    @task
    def process_message(message):
        # Your processing logic here
        pass
    
    @flow
    def my_flow():
        with concurrency("sqs_message_processing", occupy=1):
            message = get_message_from_queue()
            process_message(message)
    
    if __name__ == "__main__":
        my_flow()

2. Work Pools and Concurrency: Ensure you have set up work pools in Prefect Cloud or Server, which can help you manage concurrent execution of tasks and prioritize them. For more detailed steps, you can refer to the Prefect Guide on Global Concurrency Limits and the Work Pools Documentation. By configuring concurrency limits and work pools, you can prevent the same SQS message from being processed multiple times by different instances of your flow.