google-kubernetes-engine

问题 I cannot create a virtual machines in GCE.. While creating it is showing the error message, i have attached my screen-shot of error message.. i will briefly explain what i have done.. --> I have deleted my compute engine default service account from my service account list.. later i created new service account.. --> While creating virtual machines i selected newly created service account, vm creating was failed but the error shows the deleted service account id is not found under service

问题 I am trying to integrate CircleCi with gcloud Kubernetes engine. I created a service account with Kubernetes Engine Developer and Storage Admin roles. Created CircleCi yaml file and configured CI. Part of my yaml file includes: docker: - image: google/cloud-sdk environment: - PROJECT_NAME: 'my-project' - GOOGLE_PROJECT_ID: 'my-project-112233' - GOOGLE_COMPUTE_ZONE: 'us-central1-a' - GOOGLE_CLUSTER_NAME: 'my-project-bed' steps: - checkout - run: name: Setup Google Cloud SDK command: | apt-get

问题 Using Kubernetes 1.12.6-gke.7 or higher it is possible to create a ManagedCertificate which is then referenced from an Ingress Resource exposing a Service to the Internet. Running kubectl describe managedcertificate certificate-name first indicates the certificate is in a Provisioning state but eventually goes to FailedNotVisible. Despite using a Static IP and DNS that resolves fine to the http version of said service all ManagedCertificate's end up in a "Status: FailedNotVisible" state.

问题 I need to access an internal application running on GKE Nginx Ingress service riding on Internal Load Balancer, from another GCP region. I am fully aware that it is not possible using direct Google networking and it is a huge limitation (GCP Feature Request). Internal Load Balancer can be accessed perfectly well via VPN tunnel from AWS, but I am not sure that creating such a tunnel between GCP regions under the same network is a good idea. Workarounds are welcomed! 回答1: Another possible way

问题 For a use case I need to create deployments from a pod when a script is being executed from inside the pod. I am using google container engine for my cluster. How to configure the container inside the pod to be able to run commands like kubectl create deployment.yaml? P.S A bit clueless about it at the moment. 回答1: Your container is going to need to have kubectl available. There are some container images available, personally I can't vouch for any of them. Personally I'd probably build my own

问题 My stdout logs are not showing up in Google Logs Viewer, or when using kubectl logs <pod> . The cluster has Cloud Logging enabled and fluentd containers are running on each node. Example Python code: logger = logging.getLogger() logger.setLevel(logging.INFO) handler = logging.StreamHandler(sys.stdout) handler.setLevel(logging.INFO) logger.addHandler(handler) logger.info("test log") The "counter-pod" example from their docs does work on my cluster, so the fluentd containers are picking up

问题 I have a cluster of 2 nodes, each node is a VM of 2 CPU on GCE Here is the chart for VM CPU usage metric VM CPU Here is the chart for CPU usage from GKE containers GKE CPU So why is there much difference between 2 metric? Also why total CPU usage of GKE can be higher than 4 seconds (because I have 4 cores ) Cluster nodes PS1 : I found that there is a "bug" or something is not perfect with the chart in stackdriver monitoring. When I change the chart to be 1w then I get something like this 1w

问题 I have a cluster of 2 nodes, each node is a VM of 2 CPU on GCE Here is the chart for VM CPU usage metric VM CPU Here is the chart for CPU usage from GKE containers GKE CPU So why is there much difference between 2 metric? Also why total CPU usage of GKE can be higher than 4 seconds (because I have 4 cores ) Cluster nodes PS1 : I found that there is a "bug" or something is not perfect with the chart in stackdriver monitoring. When I change the chart to be 1w then I get something like this 1w

问题 I've got a node pool defined with min instances set to 1 and max instances set to 5, and autoscaling enabled. However it does not seem to be scaling down. I have cordoned a node. It has been over 12 hours There are no pending pods Removing a node would not reduce the amount of replicas of my own deployment The node in question has the following pods running on it: fluentd kube-dns kube-proxy-gke metrics-server redis All the pods above are in the kube-system namespace besides the redis pod

问题 So on GKE I have a Node.js app which for each pod uses about: CPU(cores): 5m, MEMORY: 100Mi However I am only able to deploy 1 pod of it per node. I am using the GKE n1-standard-1 cluster which has 1 vCPU, 3.75 GB per node. So in order to get 2 pods of app up total = CPU(cores): 10m, MEMORY: 200Mi , it requires another entire +1 node = 2 nodes = 2 vCPU, 7.5 GB to make it work. If I try to deploy those 2 pods on the same single node, I get insufficient CPU error. I have a feeling I should