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).
If you want a simplified getting started experience and GUI for managing clusters, please consider trying [Google Container Engine](https://cloud.google.com/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](http://cloud.google.com/console) for more details.
1. Install `gcloud` as necessary. `gcloud` can be installed as a part of the [Google Cloud SDK](https://cloud.google.com/sdk/).
1. Enable the [Compute Engine Instance Group Manager API](https://developers.google.com/console/help/new/#activatingapis) in the [Google Cloud developers console](https://console.developers.google.com).
1. 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>`.
1. Make sure you can start up a GCE VM from the command line. At least make sure you can do the [Create an instance](https://cloud.google.com/compute/docs/instances/#startinstancegcloud) part of the GCE Quickstart.
1. Make sure you can ssh into the VM without interactive prompts. See the [Log in to the instance](https://cloud.google.com/compute/docs/instances/#sshing) 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):
By default, some containers will already be running on your cluster. Containers like `fluentd` provide [logging](/docs/getting-started-guides/logging), while `heapster` provides [monitoring](http://releases.k8s.io/{{page.githubbranch}}/cluster/addons/cluster-monitoring/README.md) 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](https://github.com/kubernetes/kubernetes/releases), then run the `<kubernetes>/cluster/kube-up.sh` script to start the cluster:
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](/docs/getting-started-guides/gce/#troubleshooting), post to the
### 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](/docs/user-guide/kubectl/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:
**Note**: The above commands will last for the duration of your bash session. If you want to make this permanent you need to add corresponding command in your bash profile.
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](/docs/user-guide/simple-nginx) to try out your new cluster.
For more complete applications, please look in the [examples directory](https://github.com/kubernetes/kubernetes/tree/{{page.githubbranch}}/examples/). The [guestbook example](https://github.com/kubernetes/kubernetes/tree/{{page.githubbranch}}/examples/guestbook/) is a good "getting started" walkthrough.
### Tearing down the cluster
To remove/delete/teardown the cluster, use the `kube-down.sh` script.
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
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](https://cloud.google.com/storage/docs/json_api/) for more
details.
Also ensure that-- as listed in the [Prerequsites section](#prerequisites)-- 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](https://cloud.google.com/compute/docs/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