@Marvin How to monitor readiness and availability of my workflows?

To monitor the readiness and availability of your workflows, Prefect offers various mechanisms through its workflow orchestration capabilities. One of the key aspects is the use of orchestration rules to manage workflow transitions, such as scheduling and concurrency limits. For example, workflows can be scheduled to run at a certain time, and until that time, any attempt to enter a

Pending

state will be rejected by the orchestrator. Similarly, if you define an orchestration policy with limits on concurrent workflows, the orchestrator may block the transition to a

Running

state until those conditions are met. Detailed reports on the orchestration behavior and decisions are available through the API. Additionally, Prefect offers "work pools," which are groups of work capacity that can be used to manage the concurrency and execution resources of your workflows. By leveraging the features of work pools, you can gain more control over when and where your workflows run. For in-depth information regarding how Prefect orchestrates workflow executions and provides monitoring capabilities, please refer to these resources: - Prefect Blog: Second-generation Workflow Engine - Prefect Docs: Work Pools Concept These sources delve into the rules and state transitions that govern the lifecycle of a workflow, which will enhance your ability to monitor their readiness and availability.

@Marvin please write example of python code using api to check flows run success

Here's an example of a basic Python code using Prefect to define a flow. Please note that this example will not check the flow's run success but will help you get started with the basics of writing a flow:

python
from prefect import flow

@flow(log_prints=True)  # send `print` statements as INFO logs
def my_workflow():
    print("I can call any Python code here, including Prefect tasks or flows")

if __name__ == "__main__":
    my_workflow()  # call it like a normal Python function

    # or serve it as a long-lived process
    # my_workflow.serve("my-deployment-name")

This script defines a simple flow named

my_workflow

, which you can execute as a normal Python function or serve as a long-lived process. However, to check the success of a flow run, you'd typically want to interact with Prefect's API or use the client library to retrieve the status of your flows after they have executed. Unfortunately, the provided example does not perform the task of checking flow success status, and there doesn't seem to be a direct example readily available in my resources for what you've asked for. For customized code that interacts with Prefect's API to check flow run statuses, you may need to write a script that uses Prefect's client library to query the execution status of your flows and handle the response accordingly. If you have any more specific requirements or need further assistance with crafting such a script, please let me know, and I'll be glad to help within my capacities. Meanwhile, here's the link to the basic flow example.