Let me help explain this error. "Pod never started" typically occurs when running Prefect with Kubernetes infrastructure and indicates that the Kubernetes pod failed to start within the expected timeframe. There are several common causes: 1. Resource Constraints: - Not enough CPU or memory available in the cluster - No nodes available that match the pod's requirements - Node pool capacity limits reached 2. Configuration Issues: - Missing or incorrect service account permissions - Invalid Kubernetes configuration - Container image pull errors - Node affinity/taint issues 3. Network/Infrastructure Issues: - Docker registry access problems - Network connectivity issues - Container image pull rate limits To troubleshoot this: 1. Check the Kubernetes events for the pod:

bash
kubectl describe pod <pod-name>
kubectl describe job <job-name>

2. Verify your infrastructure configuration: - Ensure your Kubernetes cluster has sufficient resources - Check that service accounts and RBAC permissions are correctly configured - Verify container registry access and credentials 3. Adjust the

pod_watch_timeout_seconds

parameter if needed (though this should be a last resort - fixing the root cause is better) If you're seeing this error frequently, you might want to: - Monitor your cluster's resource utilization - Set up proper resource requests and limits - Implement auto-scaling if you're dealing with varying workloads - Ensure your container images are accessible to your Kubernetes cluster Would you like me to help investigate any specific aspect of this error in your environment? It would be helpful to know: - Are you using a managed Kubernetes service (like EKS, GKE, AKS) or self-hosted? - Can you share the relevant Kubernetes configuration or deployment logs?

Based on the behavior you're describing and recent issue reports, I can explain what's happening: This is actually a known behavior when using Kubernetes infrastructure with concurrency limits. Here's what's occurring: 1. When you have many flows trying to run simultaneously with a concurrency limit of 6: - Only 6 flows can run at once - Additional flows attempt to start but can't get scheduled due to the concurrency limit - These pods fail to start within the default timeout period - Prefect marks these as "CRASHED" 2. The automatic restart behavior you're seeing is expected because: - When previously running flows complete, they free up concurrency slots - Kubernetes will automatically attempt to reschedule the "failed" pods - Once resources are available (concurrency slots free up), these pods can start successfully - The flow runs transition from "CRASHED" to "RUNNING" To better manage this situation, you have several options: 1. Queue Instead of Crash: Use work queues with a concurrency limit instead of infrastructure-level concurrency. This will queue flows rather than crash them:

python
from prefect.blocks.system import Queue

@flow(name="my-flow")
def my_flow():
    ...

if __name__ == "__main__":
    my_flow.serve(name="my-deployment", work_queue="my-queue")

2. Adjust Timeouts: If you want to keep your current setup, you can increase the

pod_watch_timeout_seconds

in your Kubernetes job configuration to give pods more time to start. 3. Implement Backoff: Add retry policies to your flows to handle infrastructure-related failures more gracefully:

python
from prefect import flow
from datetime import timedelta

@flow(retries=3, retry_delay_seconds=60)
def my_flow():
    ...

The most robust solution would be option 1 (using work queues), as it provides better control over flow execution and avoids the crash/restart cycle you're currently experiencing. Would you like me to provide more details about implementing any of these solutions?