<@ULVA73B9P> Why does my EKS Worker take 23 minutes to start a pod? There seems to be a 19 minutes...
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@Marvin Why does my EKS Worker take 23 minutes to start a pod? There seems to be a 19 minutes and 15 seconds delay between "Opening process..." step and the start of the flow "Starting my_flow_hello_world Worker 'KubernetesWorker kwid' submitting flow run 'flowid' 055556 AM prefect.flow_runs.worker Creating Kubernetes job... 055556 AM prefect.flow_runs.worker Job 'thepod': Starting watch for pod start... 055556 AM prefect.flow_runs.worker Job 'thepod': Pod 'thepod-a' has started. 055556 AM prefect.flow_runs.worker Job 'thepod': Pod has status 'Pending'. 055556 AM prefect.flow_runs.worker Completed submission of flow run 'flowid' 055557 AM prefect.flow_runs.worker Job 'thepod': Pod 'thepod-a' has started. 055755 AM prefect.flow_runs.worker Job 'thepod': Pod has status 'Running'. 055755 AM prefect.flow_runs.worker Opening process... 055802 AM prefect.flow_runs.runner Starting my_flow_hello_world 061717 AM
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Why does my EKS Worker take 23 minutes to start a pod? There seems to be a 19 minutes and 15 seconds delay between "Opening process..." step and the start of the flow "Starting my_flow_hello_world
Worker 'KubernetesWorker kwid' submitting flow run 'flowid' 055556 AM prefect.flow_runs.worker Creating Kubernetes job... 055556 AM prefect.flow_runs.worker Job 'thepod': Starting watch for pod start... 055556 AM prefect.flow_runs.worker Job 'thepod': Pod 'thepod-a' has started. 055556 AM prefect.flow_runs.worker Job 'thepod': Pod has status 'Pending'. 055556 AM prefect.flow_runs.worker Completed submission of flow run 'flowid' 055557 AM prefect.flow_runs.worker Job 'thepod': Pod 'thepod-a' has started. 055557 AM prefect.flow_runs.worker Job 'thepod': Pod 'thepod-a' has started. 055755 AM prefect.flow_runs.worker Job 'thepod': Pod has status 'Running'. 055755 AM prefect.flow_runs.worker Opening process... 055802 AM prefect.flow_runs.runner Starting my_flow_hello_world 061717 AM ```
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@Marvin Why does my EKS Worker take 23 minutes to start a pod? There seems to be a 19 minutes and 15 seconds delay between "Opening process..." step and the start of the flow "Starting my_flow_hello_world Worker 'KubernetesWorker kwid' submitting flow run 'flowid' 055556 AM prefect.flow_runs.worker Creating Kubernetes job... 055556 AM prefect.flow_runs.worker Job 'thepod': Starting watch for pod start... 055556 AM prefect.flow_runs.worker Job 'thepod': Pod 'thepod-a' has started. 055556 AM prefect.flow_runs.worker Job 'thepod': Pod has status 'Pending'. 055556 AM prefect.flow_runs.worker Completed submission of flow run 'flowid' 055557 AM prefect.flow_runs.worker Job 'thepod': Pod 'thepod-a' has started. 055755 AM prefect.flow_runs.worker Job 'thepod': Pod has status 'Running'. 055755 AM prefect.flow_runs.worker Opening process... 055802 AM prefect.flow_runs.runner Starting my_flow_hello_world 061717 AM
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It looks like you are experiencing a significant delay between the start of the pod and when your flow actually begins execution. This can happen for a variety of reasons, especially when dealing with Kubernetes in an Amazon EKS environment. Here are some potential causes and suggestions: 1. Resource Availability: Check if there are sufficient resources (CPU, memory) available in your cluster. If resources are scarce, Kubernetes might delay the pod scheduling. 2. Pod Scheduling: The Kubernetes scheduler may take time to find the right node to place your pod on, especially in a lightly provisioned cluster or with complex node affinity/anti-affinity rules. You can check the pod events using
kubectl describe pod <pod-name>
to see if there are scheduler-related messages. 3. Cluster Autoscaler: If you're using an autoscaler, it might take time to add new nodes to your cluster if the current ones are at capacity. 4. Networking Issues: Sometimes networking configurations or delays in initializing the network interface for the pod can cause delays. 5. Image Pulling Delays: If your pod is using a Docker image that needs to be pulled from a registry, this process can take time especially for large images or if the network is slow. 6. Initialization Containers or Hooks: If you have init containers or startup hooks, they could add to the delay. 7. Kubernetes Event Logs: Checking the Kubernetes event logs for any unusual messages or errors can provide further insight. Use
kubectl get events --namespace <your-namespace>
. 8. Prefect Version and Known Issues: Since Prefect functionalities can change with versions, there might be specific issues in certain releases related to Kubernetes. Make sure your Prefect setup corresponds to the latest known best practices. I recommend checking the Kubernetes pod events and logs for any additional context or errors. If you identify a specific bottleneck or error in the logs, that could lead you more directly to a solution. For further investigation, please confirm your Prefect version to check on any relevant documentation or known issues in Prefect that might pertain to your case.
To efficiently address the issue you're facing, let's examine potential reasons why a Kubernetes pod might experience significant delays, especially in the context of Prefect. Here are some usual suspects: 1. Resource Availability: Kubernetes pods may remain in the "Pending" state if there aren't enough resources (CPU, memory) to schedule the pod. Check your cluster's resource allocation and requests/limits for the pod. 2. Networking or DNS Issues: Sometimes, networking issues can delay the pod startup. Ensure that your cluster's networking model, including DNS resolution, is functioning correctly. 3. Pod Startup Time: Some containers take time to start due to initialization logic or slow application boot times. Check the container's logs once it starts to see if there's any indication of delays during startup. 4. Image Pulling: If the Docker image is large or needs to be pulled from a remote registry, this can add significant time. Ensure your EKS nodes have efficient access to the image registry and consider using smaller base images or optimizing images for faster pulls. 5. Prefect Worker Configuration: Verify that the Prefect deployment configuration (e.g., Kubernetes namespace, resource settings) aligns with EKS best practices and is appropriately tuned for your workload. To provide more detailed help, I'll check for relevant issues and documentation using your provided conditions. If you're running Prefect 2.x or 3.x, this approach will give insights into any known issues or configurations that could be causing the delay. Let's find more information by checking Prefect's documentation and GitHub issues. It appears there was an issue executing the documentation searches due to missing query parameters. However, a search in the GitHub issues for Prefect has provided some potentially relevant information. GitHub Issues Analysis: 1. ModuleNotFoundError Issue: Some users have reported under specific configurations involving custom images, issues with running flows simultaneously. While this is not directly related to pod start times, concurrency issues might affect service availability and response times which can indirectly cause delays. (Source: GitHub Issue #8337) 2. HTTP2 Connection Errors: Another issue involves HTTP2 connection errors which are seen in longer flow runs. This isn't directly indicative of delays at startup but may provide context if related network issues arise. (Source: GitHub Issue #11660) 3. Job Template Command Addition: A recent pull request to add a command for getting the default base job template could be of interest if you're using custom templates or configurations that deviate from the standard implementations. (Source: GitHub Pull Request #10776) For the most part, the delay you're experiencing might be environment specific, and not necessarily a direct bug within Prefect itself. Here are further recommendations: ### Recommendations: - Resource Checks: Verify that your EKS cluster has sufficient resources and check AWS CloudWatch or similar monitoring for any resource constraints during these delayed periods. - Image Caching: Ensure that your nodes possibly cache images, and the image sizes are optimized. - Prefect Versions and Settings: Make sure your Prefect worker configuration (number of replicas, concurrency settings) is optimal for your workload. Without a detailed examination of your specific deployment and orchestration settings, isolating the cause may require more hands-on debugging and log examination, especially with your Kubernetes environment. If possible, try running with increased logging levels to capture detailed timing metrics around the Kubernetes pod and Prefect worker interactions.
Please let me know if additional queries or checks are needed for documentation with specific details on questions you're looking into!
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1. 2 vcpu and 16 GB
5. Image pulled in 48 seconds