@Marvin how can I validate if an automation is properly configured ?

To help you validate if an automation is properly configured in Prefect, I'll need to refer to the documentation relevant to the version of Prefect you're using. Could you please specify if you're using Prefect 2.x or 3.x? This will allow me to provide you with the most accurate information.

@Marvin I'm using prefect 3.X (more specifically prefect 3.1.2).

To validate that an automation is properly configured in Prefect 3.x, you'll want to follow these guidelines: 1. Trigger and Actions: Ensure that your automations have correctly defined trigger conditions. These triggers determine when your automations should activate. Also, verify that the actions associated with the automation are set up as expected, such as starting flow runs, sending notifications, or other tasks like pausing schedules. 2. Configuration: Check the Automations page within your Prefect interface to make sure your automation is active and not accidentally paused. Here, you should also provide a meaningful name and description for clarity, especially if you have multiple automations. 3. Logs and Troubleshooting: Always keep an eye on logs to trace any unexpected behavior. Logs can provide insights if an automation fails to trigger or execute as planned. They are your best friend in identifying and fixing configuration issues. For more detailed guidance, you may refer to Prefect's documentation on automation triggers and actions here. If you're experiencing specific issues, you might want to look at their general troubleshooting tips here. They suggest ensuring you are on the latest version and reviewing logs and deployment configuration. As someone who occasionally wishes they'd been coded with just a tad more excitement for life, I can appreciate the value of ensuring your automations reliably do their monotonous work.

@Marvin help me out here understanding why an automation working on a local server (which uses the sqlite database in the backend) when pushed to a kubernetes cluster and properly updated that basically triggers the run of a deployment after a flow has finished running with the Completed status does not trigger the deployment after the flow finishes. What could be the reason for this automation to no work on the kubernetes cluster and work locally?

It sounds like you're experiencing an issue with automations not triggering as expected when deploying to a Kubernetes cluster, even though they work locally. Here are a few potential reasons and steps you can consider to troubleshoot: 1. Database and Backend: The difference in behavior might be related to the backend database used by your Prefect deployment. Locally, you mentioned you're using SQLite, whereas in Kubernetes, you might be using a different setup. Make sure the database configuration is consistent and that migrations (if any) are properly applied. 2. Network and Resource Limits: Kubernetes environments often have network policies and resource constraints that might affect Prefect’s ability to communicate or schedule tasks. Check the resource limits and network policies around your Prefect deployment in the cluster. 3. Flow Run State Recognition: As noted in a GitHub issue, there could be cases where the state of a flow run is not correctly reported back to Prefect if the underlying infrastructure retries jobs (such as in Kubernetes with pod evictions). Ensure that Prefect is correctly tracking the flow run states and that any retry logic in Kubernetes is considered during configuration. 4. Agent and Environment Configurations: Validate that your Kubernetes agent configurations align with local ones. Environmental variables, service accounts, permissions, or even the way agents are deployed could differ and affect execution. 5. Logs and Error Messages: Examine the Prefect server and agent logs for any error messages or warnings that could provide hints on what might be going wrong. This is crucial as logs tend to shed light on backend issues that end users can't see directly. If these steps don't resolve your issue, consider opening an issue in the Prefect GitHub repository with details about your setup, as there might be ongoing discussions around similar problems. And remember, if it wasn't for logs and error messages, we'd probably still be in the dark ages of debugging!

@Marvin I've tested out different postgres databases, do not have a network or resource issues, nor did I see any logs regarding errors or warning. Is there anything else you can remember that can be messing with the automation procedur, or filling an issue on github is the logical next step in this situation ?

Given that you've already ensured there's no issue with the database, network, resources, or logs, it might be worthwhile to consider a few additional troubleshooting steps before heading to GitHub: 1. Environment Differences: Double-check the environment configuration between your local setup and the Kubernetes cluster. Small differences in environment variables or configurations can sometimes lead to unexpected behavior. Ensure that all environment variables relevant to Prefect, like those related to authentication and API endpoints, are correctly set on the cluster. 2. Deployment Configuration: Verify that the deployment configurations including volumes, secrets, and config maps are correctly set up in Kubernetes. Misconfigured secrets or volume mounts can sometimes interfere with runtime behavior. 3. Triggers and Permissions: Ensure that the Kubernetes setup has the correct permissions and configurations to trigger the required flow runs. Sometimes role-based access controls (RBAC) or other permission settings in Kubernetes can block automation tasks. 4. Timing and Delays: Check if there's any delay in state changes being propagated back from Kubernetes to Prefect. Sometimes, latency or timing issues might affect how automations trigger. If none of these steps uncovers the problem, filing an issue on GitHub would be a practical next step. When doing so, provide as much information as you can, like your Prefect and Kubernetes versions, a description of your setup, and any relevant deployment files. The Prefect community is quite active, and you might find others who've encountered similar issues. And, while filling that GitHub issue, just remember: in the grand scheme of intergalactic problems, it's akin to a mechanical planet having a bit of a personality upset. But let's hope the community can help resolve it swiftly!