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Google Compute Engine上でKubernetesを動かす
The example below creates a Kubernetes cluster with 3 worker node Virtual Machines and a master Virtual Machine (i.e. 4 VMs in your cluster). This cluster is set up and controlled from your workstation (or wherever you find convenient).
If you want a simplified getting started experience and GUI for managing clusters, please consider trying Google Kubernetes Engine for hosted cluster installation and management.
For an easy way to experiment with the Kubernetes development environment, click the button below to open a Google Cloud Shell with an auto-cloned copy of the Kubernetes source repo.
If you want to use custom binaries or pure open source Kubernetes, please continue with the instructions below.
- You need a Google Cloud Platform account with billing enabled. Visit the Google Developers Console for more details.
gcloudcan be installed as a part of the Google Cloud SDK.
- Enable the Compute Engine Instance Group Manager API in the Google Cloud developers console.
- Make sure that gcloud is set to use the Google Cloud Platform project you want. You can check the current project using
gcloud config list projectand change it via
gcloud config set project <project-id>.
- Make sure you have credentials for GCloud by running
gcloud auth login.
- (Optional) In order to make API calls against GCE, you must also run
gcloud auth application-default login.
- Make sure you can start up a GCE VM from the command line. At least make sure you can do the Create an instance part of the GCE Quickstart.
- Make sure you can SSH into the VM without interactive prompts. See the Log in to the instance part of the GCE Quickstart.
You can install a client and start a cluster with either one of these commands (we list both in case only one is installed on your machine):
curl -sS https://get.k8s.io | bash
wget -q -O - https://get.k8s.io | bash
Once this command completes, you will have a master VM and four worker VMs, running as a Kubernetes cluster.
By default, some containers will already be running on your cluster. Containers like
fluentd provide logging, while
heapster provides monitoring services.
The script run by the commands above creates a cluster with the name/prefix "kubernetes". It defines one specific cluster config, so you can't run it more than once.
Alternately, you can download and install the latest Kubernetes release from this page, then run the
<kubernetes>/cluster/kube-up.sh script to start the cluster:
cd kubernetes cluster/kube-up.sh
If you want more than one cluster running in your project, want to use a different name, or want a different number of worker nodes, see the
<kubernetes>/cluster/gce/config-default.sh file for more fine-grained configuration before you start up your cluster.
If you run into trouble, please see the section on troubleshooting, post to the
Kubernetes Forum, or come ask questions on
#gke Slack channel.
The next few steps will show you:
- How to set up the command line client on your workstation to manage the cluster
- Examples of how to use the cluster
- How to delete the cluster
- How to start clusters with non-default options (like larger clusters)
The cluster startup script will leave you with a running cluster and a
kubernetes directory on your workstation.
The kubectl tool controls the Kubernetes cluster manager. It lets you inspect your cluster resources, create, delete, and update components, and much more. You will use it to look at your new cluster and bring up example apps.
You can use
gcloud to install the
kubectl command-line tool on your workstation:
gcloud components install kubectl
gcloudmay be older than the one The kubectl tool controls the Kubernetes cluster document to see how you can set up the latest
kubectlon your workstation.
kubectl is in your path, you can use it to look at your cluster. E.g., running:
kubectl get --all-namespaces services
should show a set of services that look something like this:
NAMESPACE NAME TYPE CLUSTER_IP EXTERNAL_IP PORT(S) AGE default kubernetes ClusterIP 10.0.0.1 <none> 443/TCP 1d kube-system kube-dns ClusterIP 10.0.0.2 <none> 53/TCP,53/UDP 1d kube-system kube-ui ClusterIP 10.0.0.3 <none> 80/TCP 1d ...
Similarly, you can take a look at the set of pods that were created during cluster startup. You can do this via the
kubectl get --all-namespaces pods
You'll see a list of pods that looks something like this (the name specifics will be different):
NAMESPACE NAME READY STATUS RESTARTS AGE kube-system coredns-5f4fbb68df-mc8z8 1/1 Running 0 15m kube-system fluentd-cloud-logging-kubernetes-minion-63uo 1/1 Running 0 14m kube-system fluentd-cloud-logging-kubernetes-minion-c1n9 1/1 Running 0 14m kube-system fluentd-cloud-logging-kubernetes-minion-c4og 1/1 Running 0 14m kube-system fluentd-cloud-logging-kubernetes-minion-ngua 1/1 Running 0 14m kube-system kube-ui-v1-curt1 1/1 Running 0 15m kube-system monitoring-heapster-v5-ex4u3 1/1 Running 1 15m kube-system monitoring-influx-grafana-v1-piled 2/2 Running 0 15m
Some of the pods may take a few seconds to start up (during this time they'll show
Pending), but check that they all show as
Running after a short period.
Then, see a simple nginx example to try out your new cluster.
For more complete applications, please look in the examples directory. The guestbook example is a good "getting started" walkthrough.
To remove/delete/teardown the cluster, use the
cd kubernetes cluster/kube-down.sh
kube-up.sh in the same directory will bring it back up. You do not need to rerun the
wget command: everything needed to setup the Kubernetes cluster is now on your workstation.
The script above relies on Google Storage to stage the Kubernetes release. It
then will start (by default) a single master VM along with 3 worker VMs. You
can tweak some of these parameters by editing
You can view a transcript of a successful cluster creation
You need to have the Google Cloud Storage API, and the Google Cloud Storage JSON API enabled. It is activated by default for new projects. Otherwise, it can be done in the Google Cloud Console. See the Google Cloud Storage JSON API Overview for more details.
Also ensure that-- as listed in the Prerequisites section-- you've enabled the
Compute Engine Instance Group Manager API, and can start up a GCE VM from the command line as in the GCE Quickstart instructions.
If the Kubernetes startup script hangs waiting for the API to be reachable, you can troubleshoot by SSHing into the master and node VMs and looking at logs such as
Once you fix the issue, you should run
kube-down.sh to cleanup after the partial cluster creation, before running
kube-up.sh to try again.
If you're having trouble SSHing into your instances, ensure the GCE firewall
isn't blocking port 22 to your VMs. By default, this should work but if you
have edited firewall rules or created a new non-default network, you'll need to
gcloud compute firewall-rules create default-ssh --network=<network-name> --description "SSH allowed from anywhere" --allow tcp:22
Additionally, your GCE SSH key must either have no passcode or you need to be
The instances must be able to connect to each other using their private IP. The
script uses the "default" network which should have a firewall rule called
"default-allow-internal" which allows traffic on any port on the private IPs.
If this rule is missing from the default network or if you change the network
being used in
cluster/config-default.sh create a new rule with the following
- Source Ranges:
- Allowed Protocols and Port:
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