@kapa.ai Hello, I run an Airflow Kubernetes pod. I run Airbyte on a Kubernetes pod within the same VPC network/subnetwork. I want to trigger an airbyte connection through airflow DAG. However, I get this error:

urllib3.exceptions.MaxRetryError: HTTPConnectionPool(host='172.16.0.2', port=8080): Max retries exceeded with url: /api/v1/connections/sync (Caused by ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x7838d78526e0>, 'Connection to 172.16.0.2 timed out. (connect timeout=None)'))

172.16.0.2 is the internal endpoint of my Airbyte kb8 pod.

Based on the information provided in the knowledge sources, it appears that you're experiencing a connection timeout issue when trying to trigger an Airbyte connection through an Airflow DAG. This is likely related to network connectivity or timeout settings. Here are some suggestions to address this issue: 1. Ensure proper network connectivity: Make sure that your Airflow pod can reach the Airbyte pod within the VPC network. You might need to check your network policies and firewall rules to allow communication between the pods. 2. Verify the Airbyte API endpoint: Confirm that the Airbyte API is indeed accessible on port 8080. According to the knowledge sources, the default Airbyte API port is usually 8001 [Source](https://discuss.airbyte.io/t/1573). You may need to adjust your connection settings to use the correct port. 3. Increase timeout settings: The error suggests a connection timeout. You can try increasing the timeout settings in your Airflow DAG. Here's an example of how to set up an Airbyte connection in Airflow with extended timeout:

python    money_to_json = AirbyteTriggerSyncOperator(        task_id='airbyte_money_json_example',        airbyte_conn_id='airbyte_conn_example',        connection_id='your-connection-id',        asynchronous=False,        timeout=3600,  # Increase this value        wait_seconds=3    )

[Source](https://docs.airbyte.com/operator-guides/using-the-airflow-airbyte-operator#creating-a-simple-airflow-dag-to-run-an-airbyte-sync-job) 4. Adjust Airbyte configuration: If the issue persists, you may need to increase timeout settings on the Airbyte side. For Kubernetes deployments, you can add the following to your Helm chart values:

yaml    global:      env_vars:        HTTP_IDLE_TIMEOUT: 1800s     webapp:      ingress:        annotations:          <http://nginx.ingress.kubernetes.io/proxy-send-timeout|nginx.ingress.kubernetes.io/proxy-send-timeout>: 1800          <http://nginx.ingress.kubernetes.io/proxy-read-timeout|nginx.ingress.kubernetes.io/proxy-read-timeout>: 1800

[Source](https://github.com/airbytehq/airbyte/discussions/45946) 5. Check Airbyte server logs: If you're still encountering issues, it would be helpful to check the Airbyte server logs for any errors or connection problems. Remember to restart your pods after making configuration changes. If the problem persists, you may need to investigate further by examining logs from both Airflow and Airbyte, and potentially consulting with your network administrator to ensure there are no network-level issues preventing the connection.

@kapa.ai on which pod, should I inspect the logs?

A message from kapa.ai

Based on the information provided in the knowledge sources and our previous conversation, you should inspect the logs on multiple pods to get a comprehensive view of the issue. Here are the key pods you should focus on: 1. Airbyte Server pod: This is the main pod that handles API requests and orchestrates Airbyte operations. You can access these logs using the following command:

kubectl logs -n airbyte-abctl airbyte-abctl-server-[pod-id]

[Source](https://docs.airbyte.com/contributing-to-airbyte/developing-locally#using-abctl-for-airbyte-development) 2. Airbyte Worker pod: This pod is responsible for executing the actual sync jobs. Check these logs for any issues related to the connection or sync process:

kubectl logs -n airbyte-abctl airbyte-abctl-worker-[pod-id]

[Source](https://discuss.airbyte.io/t/1207) 3. Airbyte Scheduler pod: This pod manages the scheduling of jobs. It might provide insights into why the connection is not being established:

kubectl logs -n airbyte-abctl airbyte-abctl-scheduler-[pod-id]

[Source](https://discuss.airbyte.io/t/1207) 4. Airbyte Webapp pod: While less likely to be the source of the issue, it might contain relevant information about the API requests:

kubectl logs -n airbyte-abctl airbyte-abctl-webapp-[pod-id]

[Source](https://discuss.airbyte.io/t/1207) 5. Your Airflow pod: Since the error is occurring in your Airflow DAG, it's crucial to also inspect the logs of your Airflow pod to see any errors or stack traces related to the Airbyte connection attempt. Remember to replace

[pod-id]

with the actual pod identifier in your Kubernetes cluster. You can get a list of all pods in the Airbyte namespace using:

kubectl get pods -n airbyte-abctl

By examining logs from these pods, you should be able to gather more information about why the connection is timing out and potentially identify the root cause of the issue.