hey @ancient-wolf-19325 When does Flyte sensor task fails with below error? and how to resolve this issue?

rpc error: code = DeadlineExceeded desc = context deadline exceeded

The error

rpc error: code = DeadlineExceeded desc = context deadline exceeded

typically occurs when a task or operation in Flyte takes longer than the allowed time to complete, leading to a timeout. This can happen due to various reasons such as network latency, resource constraints, or misconfigured timeouts. To resolve this issue, you can try the following: 1. Increase Timeout: Adjust the timeout settings for the task or operation. For example, you can set a timeout for the

ExecuteTaskSync

function in the Flyte configuration by adding a timeout value in the

flytepropeller

config map, as shown in this pull request. 2. Check Resource Allocation: Ensure that the resources allocated to the task are sufficient. This includes CPU, memory, and any other necessary resources. 3. Optimize Task Execution: Review the task logic to ensure it is optimized and not performing unnecessary operations that could lead to delays. Would you like more details on any of these steps? Sources: - this pull request 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

Is it possible to automatically retry task failed with the above error?

Yes, Flyte supports automatic retries for tasks that fail due to system-level errors, such as timeouts. You can configure retries in Flyte by setting the

retries

attribute in the task decorator. This allows the task to be retried a specified number of times upon failure. For example, you can define a task with retries as follows:

from flytekit import task

@task(retries=3)
def my_task() -> ...:
    # Task logic here
    ...

This configuration will retry the task up to three times if it fails due to a recoverable error, such as a timeout. Would you like more details on configuring retries or handling specific error types? Sources: - Flyte Blog on Building Indestructible Pipelines - Flyte Documentation on Optimizing Tasks 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 Can we add retry to "file sensor" if a sensor fails?

Yes, you can add retries to a Flyte task, including a file sensor task, by using the

retries

attribute in the task decorator. This allows the task to be retried a specified number of times if it fails. Here's an example of how you might configure a file sensor task with retries:

from flytekit import task, workflow
from datetime import timedelta

@task(retries=3)
def file_sensor_task(path: str) -> str:
    # Logic to check for file existence
    ...
    return path

@workflow
def my_workflow(path: str) -> str:
    return file_sensor_task(path=path)

This setup will retry the

file_sensor_task

up to three times if it fails. Would you like more details on configuring retries for specific scenarios? Sources: - https://github.com/flyteorg/flytesnacks/blob/master/examples/extending/extending/user_container.py - https://github.com/flyteorg/flyte/issues/5513 👍 0 button 👎 1 button 💡 Hint: Mention @ancient-wolf-19325 in the thread for followups.

@millions-night-34157 I think the Sensor task is designed to run forever until it meets the condition, this is, when used with the Agent. Could you share a bit more about the context of how you're using file sensor?

Hey @average-finland-92144 thanks for looking into this. We are using file sensors for s3 objects. Mostly these sensors are working as expected but recently some of them failed with the above error. Not sure if it is a cluster / configuration issue or something else.

It seems likely that the error

rpc error: code = Unavailable desc = connection error: desc = "transport: Error while dialing: dial tcp 17.20.63.219:8000: connect: connection refused"

occurs when the Flyte system is unable to establish a connection to the specified endpoint. This could be due to network issues, the service being down, or incorrect configuration settings. To address this issue, you might want to: 1. Check Network Connectivity: Ensure that the network connection to the specified IP and port is available and not blocked by any firewall or network policy. 2. Verify Service Availability: Confirm that the service at the specified endpoint is running and accessible. This might involve checking the status of the Flyte components and ensuring they are healthy. 3. Review Configuration: Double-check the configuration settings in your Flyte setup, particularly the endpoint details in the

~/.flyte/config.yaml

file, to ensure they are correct. Would you like more details on troubleshooting this issue? Sources: - GitHub Issue #5578 - Flyte Discussion 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 How to configure flyte sensor in k8s cluster?

To configure a Flyte sensor in a Kubernetes cluster, you need to set up the sensor agent and ensure the necessary configurations are in place. Here's a brief overview: 1. Enable Sensor Agent: Add the sensor agent configuration to your Flyte deployment. This involves editing the relevant YAML configuration files to specify the agent. For example, you can modify the

configmap

to include the sensor as an enabled plugin. 2. Configure Plugins: Ensure that the

agent-service

is listed under

enabled-plugins

and

default-for-task-types

in your Flyte configuration. This allows the sensor tasks to be handled by the agent service. 3. Deploy Changes: After making the necessary configuration changes, deploy them to your Kubernetes cluster. This might involve using

kubectl

to apply the changes or using Helm if you are managing your Flyte deployment with Helm charts. 4. Restart Deployment: Once the configuration is updated, restart the Flyte deployment to apply the changes. This can be done using

kubectl rollout restart

for the relevant deployments. Would you like more detailed steps or examples? Sources: - Flyte Sensor Agent Configuration - Flyte GitHub Issue on Sensor Configuration 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 How to check flyte file sensor logs in k8s cluster?

It seems likely that to check Flyte file sensor logs in a Kubernetes cluster, you would typically use

kubectl

to access the logs of the relevant pods. Here’s a general approach: 1. Identify the Pod: First, identify the pod running the Flyte file sensor. You can list the pods in the Flyte namespace using:

kubectl get pods -n <flyte-namespace>

2. Describe the Pod: Use

kubectl describe

to get more details about the pod, which can help in understanding the current state and any events:

kubectl describe pod <pod-name> -n <flyte-namespace>

3. Access Logs: Once you have identified the correct pod, you can view its logs using:

kubectl logs <pod-name> -n <flyte-namespace>

4. Check Specific Containers: If the pod has multiple containers, specify the container name to view its logs:

kubectl logs <pod-name> -c <container-name> -n <flyte-namespace>

Would you like more details on any of these steps? Sources: - Flyte Troubleshooting Guide 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.