Skip to content

Latest commit

 

History

History
253 lines (178 loc) · 13.1 KB

gce.md

File metadata and controls

253 lines (178 loc) · 13.1 KB
Raw

WARNING WARNING WARNING WARNING WARNING

PLEASE NOTE: This document applies to the HEAD of the source tree

If you are using a released version of Kubernetes, you should refer to the docs that go with that version.

The latest 1.0.x release of this document can be found [here](http://releases.k8s.io/release-1.0/docs/getting-started-guides/gce.md).

Documentation for other releases can be found at releases.k8s.io.

Getting started on Google Compute Engine

Table of Contents

The example below creates a Kubernetes cluster with 4 worker node Virtual Machines and a master Virtual Machine (i.e. 5 VMs in your cluster). This cluster is set up and controlled from your workstation (or wherever you find convenient).

Before you start

If you want a simplified getting started experience and GUI for managing clusters, please consider trying Google Container Engine (GKE) for hosted cluster installation and management.

If you want to use custom binaries or pure open source Kubernetes, please continue with the instructions below.

Prerequisites

  1. You need a Google Cloud Platform account with billing enabled. Visit the Google Developers Console for more details.
  2. Install gcloud as necessary. gcloud can be installed as a part of the Google Cloud SDK.
  3. Then, make sure you have the gcloud preview command line component installed. Run gcloud preview at the command line - if it asks to install any components, go ahead and install them. If it simply shows help text, you're good to go. This is required as the cluster setup script uses GCE Instance Groups, which are in the gcloud preview namespace. You will also need to enable Compute Engine Instance Group Manager API in the developers console.
  4. 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 project and change it via gcloud config set project <project-id>.
  5. Make sure you have credentials for GCloud by running gcloud auth login.
  6. 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.
  7. Make sure you can ssh into the VM without interactive prompts. See the Log in to the instance part of the GCE Quickstart.

Starting a cluster

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

or

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 kibana and elasticsearch 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 google-containers group, or come ask questions on IRC at #google-containers on freenode.

The next few steps will show you:

  1. how to set up the command line client on your workstation to manage the cluster
  2. examples of how to use the cluster
  3. how to delete the cluster
  4. how to start clusters with non-default options (like larger clusters)

Installing the Kubernetes command line tools on your workstation

The cluster startup script will leave you with a running cluster and a kubernetes directory on your workstation. The next step is to make sure the kubectl tool is in your path.

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.

Add the appropriate binary folder to your PATH to access kubectl:

# OS X
export PATH=<path/to/kubernetes-directory>/platforms/darwin/amd64:$PATH

# Linux
export PATH=<path/to/kubernetes-directory>/platforms/linux/amd64:$PATH

Note: gcloud also ships with kubectl, which by default is added to your path. However the gcloud bundled kubectl version may be older than the one downloaded by the get.k8s.io install script. We recommend you use the downloaded binary to avoid potential issues with client/server version skew.

Getting started with your cluster

Inspect your cluster

Once 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                  LABELS                                                                           SELECTOR                IP(S)       PORT(S)
default       kubernetes            component=apiserver,provider=kubernetes                                          <none>                  10.0.0.1    443/TCP
kube-system   kube-dns              k8s-app=kube-dns,kubernetes.io/cluster-service=true,kubernetes.io/name=KubeDNS   k8s-app=kube-dns        10.0.0.10   53/UDP
                                                                                                                                                         53/TCP
kube-system   kube-ui               k8s-app=kube-ui,kubernetes.io/cluster-service=true,kubernetes.io/name=KubeUI     k8s-app=kube-ui         10.0.59.25     80/TCP
kube-system   monitoring-grafana    kubernetes.io/cluster-service=true,kubernetes.io/name=Grafana                    k8s-app=influxGrafana   10.0.41.246    80/TCP
kube-system   monitoring-heapster   kubernetes.io/cluster-service=true,kubernetes.io/name=Heapster                   k8s-app=heapster        10.0.59.48     80/TCP
kube-system   monitoring-influxdb   kubernetes.io/cluster-service=true,kubernetes.io/name=InfluxDB                   k8s-app=influxGrafana   10.0.210.156   8083/TCP
                                                                                                                                                            8086/TCP

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

command.

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   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-dns-v5-7ztia                              3/3       Running   0          15m
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.

Run some examples

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.

Tearing down the cluster

To remove/delete/teardown the cluster, use the kube-down.sh script.

cd kubernetes
cluster/kube-down.sh

Likewise, the kube-up.sh in the same directory will bring it back up. You do not need to rerun the curl or wget command: everything needed to setup the Kubernetes cluster is now on your workstation.

Customizing

The script above relies on Google Storage to stage the Kubernetes release. It then will start (by default) a single master VM along with 4 worker VMs. You can tweak some of these parameters by editing kubernetes/cluster/gce/config-default.sh You can view a transcript of a successful cluster creation here.

Troubleshooting

Project settings

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 Prerequsites 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.

Cluster initialization hang

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 /var/log/startupscript.log.

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.

SSH

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 expose it: 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 using ssh-agent.

Networking

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 field values:

  • Source Ranges: 10.0.0.0/8
  • Allowed Protocols and Port: tcp:1-65535;udp:1-65535;icmp

Analytics