This repository contains a blueprint for installing a kubernetes cluster through mist.io.
The aforementioned kubernetes cluster consists of:
- A kubernetes master
- A kubernetes worker
Before you begin it's recommended you familiarize yourself with the
Cloudify Terminology.
You will also need a mist.io account.
This has been succesfully tested on CoreOS and Ubuntu 14.04 images under python 2.7.
Note: Documentation about the blueprints' content is located inside the blueprint files themselves. Presented here are only instructions on how to run the blueprints using the Cloudify CLI & Mist.io plugin.
git clone https://github.com/mistio/kubernetes-blueprint
cd kubernetes-blueprint
virtualenv . # create virtualenv
source bin/activate
./bin/pip install -r dev-requirements.txt # install dependencies
./bin/pip install cloudify https://github.com/mistio/mist.client/archive/master.zip
git clone https://github.com/mistio/cloudify-mist-plugin
cd cloudify-mist-plugin
python setup.py develop
cd ..
First of all, you need to add a cloud to your mist.io account. Login to the mist.io dashboard and click on the "ADD CLOUD" button. Once you have completed the aforementioned step, retrieve your cloud's ID by clicking on the tile containing your cloud's name on the mist.io home screen. The ID will be used later on as part of the required blueprint inputs.
You will also need an SSH key. Visit the Keys tab and generate/upload a key. You can use separate keys for each machine. Once again, note the name/ID of the newly created SSH key, as it will be used by our inputs file.
Then, visit your account page and create a token under the API TOKENS tabs.
Now, check the inputs files (in .yaml format) under the inputs directory in order to use them as a guide to fill in your resources' IDs accordingly.
Here's a sample:
mist_token: 544be89e3016f2fb0ba433802ee432da2e672cd7fe8e4ccc6926e1a54e835eec
mist_key_master: c4b6efa8d0a74f989d2d8a0fae7a04d1
mist_key_worker: c4b6efa8d0a74f989d2d8a0fae7a04d1
mist_cloud_1: 1b2edcb11e524e2aa5fdd89cf1e24278
mist_image_1: ami-d0e21bb1
mist_size_1: m1.medium
mist_location_1: '0'
coreos: true
worker_name: KubernetesWorker
master_name: KubernetesMaster
Afterwards, run:
./bin/cfy local init -p blueprint.yaml -i inputs/<file_name>.yaml
This command will initialize your working directory with the given blueprint.
The output would be something like this:
(kubernetes-blueprint)user@user:~/kubernetes-blueprint$ ./bin/cfy local init -p blueprint.yaml -i inputs/mist_ec2.yaml
Processing Inputs Source: inputs/mist_ec2.yaml
Initiated blueprint.yaml
If you make changes to the blueprint, run 'cfy local init -p mist-blueprint.yaml' again to apply them
Now, you can run any type of workflows using your blueprint.
You are now ready to run the install workflow:
./bin/cfy local execute -w install
This command will deploy a kubernetes master and a kubernetes worker on the specified cloud via mist.io.
The output should be something like:
(kubernetes-blueprint)user@user:~/kubernetes-blueprint$ ./bin/cfy local execute -w install
2016-05-08 16:43:48 CFY <local> Starting 'install' workflow execution
2016-05-08 16:43:48 CFY <local> [key_13e52] Creating node
2016-05-08 16:43:48 CFY <local> [master_677f6] Creating node
2016-05-08 16:43:48 CFY <local> [master_677f6.create] Sending task 'plugin.kubernetes.create'
...
2016-05-08 16:52:43 CFY <local> [worker_7a12b.start] Task succeeded 'plugin.kubernetes.start'
2016-05-08 16:52:44 CFY <local> 'install' workflow execution succeeded
This will take a while (approximately 10 minutes) to be fully executed. At the end, you will have a kubernetes cluster with two nodes.
As soon as the installation has been succesffully completed, you should see your newly created VMs on the
mist.io machines page.
At this point, you may specify the command ./bin/cfy local outputs in order to retrieve the blueprint's outputs, which consist of a
dashboard URL (alongside the required credentials) you may visit in order to verify the deployment of your kubernetes cluster and further
explore it, as well as a kubectl command you may run directly in your shell.
In case you do not have kubectl installed, simply run:
curl -O https://storage.googleapis.com/kubernetes-release/release/v1.1.8/bin/linux/amd64/kubectl && chmod +x kubectl.
To scale the cluster up first edit the inputs/new_worker.yaml file with the proper inputs.
Edit the delta parameter to specify the number of machines to be added to the cluster.
A positive number denotes an increase of kubernetes workers, while a negative number denotes a decrease of instances.
As soon as you are done editing the inputs file, run:
./bin/cfy local execute -w scale_cluster -p inputs/new_worker.yaml
A sample output would be:
(kubernetes-blueprint)user@user:~/kubernetes-blueprint$ ./bin/cfy local execute -w scale_cluster -p inputs/new_worker.yaml
Processing Inputs Source: inputs/new_worker.yaml
2016-05-08 17:15:25 CFY <local> Starting 'scale_cluster' workflow execution
...
2016-05-08 17:18:33 LOG <local> INFO:
2016-05-08 17:18:33 LOG <local> INFO:
2016-05-08 17:18:33 LOG <local> INFO: Kubernetes worker 'NewKubernetesWorker' installation script succeeded
2016-05-08 17:18:33 LOG <local> INFO: Upscaling kubernetes cluster succeeded
2016-05-08 17:18:33 CFY <local> 'scale_cluster' workflow execution succeeded
You may verify that the nodes were created and successfully added to the cluster by either running the kubectl
command or visiting the kubernetes dashboard (both included in the blueprint's outputs section).
To scale the cluster down edit the inputs/remove_worker.yaml file and specify the delta parameter as to how many
machines should be removed (destroyed) from the cluster. Then, run:
./bin/cfy local execute -w scale_cluster -p inputs/remove_worker.yaml
To uninstall the kubernetes cluster and destroy all the machines run the uninstall workflow:
./bin/cfy local execute -w uninstall