I have created a sample node.js app and other required files (deployment.yml, service.yml) but I am not able to access the external IP of the service.
#kubectl get services
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
kubernetes ClusterIP 10.7.240.1 <none> 443/TCP 23h
node-api LoadBalancer 10.7.254.32 35.193.227.250 8000:30164/TCP 4m37s
#kubectl get pods
NAME READY STATUS RESTARTS AGE
node-api-6b9c8b4479-nclgl 1/1 Running 0 5m55s
#kubectl describe svc node-api
Name: node-api
Namespace: default
Labels: <none>
Annotations: <none>
Selector: app=node-api
Type: LoadBalancer
IP: 10.7.254.32
LoadBalancer Ingress: 35.193.227.250
Port: <unset> 8000/TCP
TargetPort: 8000/TCP
NodePort: <unset> 30164/TCP
Endpoints: 10.4.0.12:8000
Session Affinity: None
External Traffic Policy: Cluster
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal EnsuringLoadBalancer 6m19s service-controller Ensuring load balancer
Normal EnsuredLoadBalancer 5m25s service-controller Ensured load balancer
When I try to do a curl on external ip it gives connection refused
curl 35.193.227.250:8000
curl: (7) Failed to connect to 35.193.227.250 port 8000: Connection refused
I have exposed port 8000 in Dockerfile also. Let me know if I am missing anything.
Looking at your description on this thread it seems everything is fine. Here is what you can try:
SSH to the GKE node where the pod is running. You can get the node name by running the same command you used with "-o wide" flag.
$ kubectl get pods -o wide
After that doing the SSH, try to curl Cluster as well as Service IP to see if you get response or not.
Try to SSH to the pod
$ kubectl exec -it -- /bin/bash
After that, run local host to see if you get response or not
$ curl localhost
So if you get response upon trying above troubleshooting steps then it could be an issue underlying at the GKE. You can file a defect report here.
If you do not get any response while trying the above steps, it is possible that you have misconfigured the cluster somewhere.
This seems to me a good starting point for troubleshooting your use case.