@ancient-wolf-19325 I started a local flyte cluster with

flytectl demo start

and then added a workflow with

pyflyte run --image toy-pipeline:latest --remote -p toy-pipeline -d development workflows/pipeline.py pipeline

. Without the

--remote

tag the task is run, but with it the tasks are not executed and the container is killed with a timeout after 3 minutes. Why?

The issue you're experiencing with the

--remote

flag is likely related to the configuration or connectivity of your local Flyte cluster. When you run a workflow with the

--remote

flag, Flyte attempts to execute the workflow on a remote cluster, which requires proper network configuration and access to the necessary resources. According to this discussion, a common issue is the inability to connect to the Flyte backend due to incorrect configuration or closed ports. Ensure that your Flyte cluster is correctly configured and that the necessary ports are open and accessible. Additionally, verify that the Flyte configuration file is correctly set up with the appropriate endpoint and authentication details. Would you like more detailed guidance on troubleshooting this issue or setting up your Flyte configuration? Sources: - Flyte Community Discussion 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 The discussion was not helping. Exporting the config again did not change anything and the pods are up and running.

If the configuration and pods are correctly set up, but the issue persists, it might be related to the network or service configuration. Here are a few steps to troubleshoot further: 1. Check Network Connectivity: Ensure that the Flyte services are accessible from your local machine. You can use

kubectl port-forward

to expose the Flyte services to your local machine and verify connectivity. 2. Verify Flyte Configuration: Double-check the Flyte configuration file (e.g.,

config-sandbox.yaml

) to ensure that the

admin.endpoint

is correctly set to the Flyte service's address and port. The endpoint should match the address where Flyte Admin is running. 3. Inspect Logs: Check the logs of the Flyte components, especially Flyte Admin and Flyte Propeller, for any error messages or warnings that might indicate the cause of the issue. Use

kubectl logs <pod-name>

to view the logs. 4. Check Resource Limits: Ensure that your local Kubernetes cluster has sufficient resources (CPU, memory) to run the Flyte components and the workflow tasks. Would you like more detailed guidance on any of these steps? Sources: - Flyte Community Discussion 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 Since I am running it locally, Ports are not a problem. How do I find out where the workflow was supposed to be run to see the relevant logs?

To find out where the workflow was supposed to be run and access the relevant logs, you can follow these steps: 1. Inspect Workflow Execution in FlyteConsole: When you run a workflow with

pyflyte run --remote

, it should provide a URL to the FlyteConsole where you can view the execution details. This URL typically looks like

http://localhost:30080/console/projects/<project>/domains/<domain>/executions/<execution_name>

. Navigate to this URL to see the execution details, including the logs. 2. Check Pod Status and Logs: Use

kubectl

to check the status of the pods associated with your workflow execution. You can list the pods in the relevant namespace using:

kubectl get pods -n <project>-<domain>

Replace

<project>

and

<domain>

with your specific project and domain names. Once you identify the relevant pod, you can view its logs using:

kubectl logs <pod-name> -n <project>-<domain>

3. Use Flytectl for Detailed Logs: If you need more detailed logs, you can use the

flytectl

command-line tool to fetch logs for specific executions. Ensure that your

FLYTECTL_CONFIG

is correctly set to point to your Flyte cluster configuration. Would you like more detailed guidance on any of these steps? Sources: - Running a Workflow Locally - Debugging Executions 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 The logs show that the my locally build docker image is failing to be pulled:

trying and failing to pull image

Why is that the case?

The issue of your locally built Docker image failing to be pulled is likely due to the image not being accessible to the Kubernetes nodes running your Flyte tasks. Here are some steps to resolve this: 1. Push Image to Local Registry: If you're running Flyte locally, you can push your Docker image to a local Docker registry. According to this discussion, you can push your image to a local registry using:

docker push localhost:30000/<image_name>:<tag>

Then, specify this image in your Flyte workflow. 2. Use Public Registry: If a local registry is not feasible, consider pushing your image to a public Docker registry like Docker Hub or GitHub Container Registry, ensuring that the Kubernetes nodes can access it. 3. Configure ImagePullPolicy: Ensure that the

imagePullPolicy

is set correctly. If you want to use a locally built image without pushing it to a registry, set

image_pull_policy="Never"

in your task decorator. However, this requires the image to be present on all nodes. 4. Verify Image Name and Tag: Double-check that the image name and tag specified in your workflow match exactly with what is available in the registry. Would you like more detailed guidance on any of these steps? Sources: - Flyte Community Discussion 👍 1 button 👎 0 button 💡 Hint: Mention @ancient-wolf-19325 in the thread for followups.

omg, it might be memory pressure