Single-node Kubernetes deployment

In order to test k8s you can always deploy a single-node setup locally using minikube, however it is a bit limited if you want to test interactions that require your services to be externally accessible from a mobile or web front-end.

For this reason, I created a basic k8s setup for a Core OS single node in Azure using . Once I did this, I decided to automate its deployment via script.

It requires a Core OS instance running, then connect to it and:

git clone k8
cd k8
./ [myip-address] –> ip associated to eth, you can find it using ifconfig

This will deploy k8 into a single node, it sets up kubectl in the node and deploys skydns add on.

It also includes a busybox node file that can be deployed by:

kubectl create -f files/busybox

This might come useful to debug issues with the set up. To execute commands in busybox run:
kubectl exec busybox — [command]

The script and config files can be access at

If you hit any issues while deploying k8s in a single node a few things worth checking are:

sudo systemctl status etcd
sudo systemctl status flanneld
sudo systemctl status docker

Also it is worth checking what docker containers are running and if necessarily check the logs

docker ps -a
docker logs [container-id]

Deploying Heapster to Kubernetes

I recently blogged about deploying kubernetes in Azure.  After doing so, I wanted to keep an eye on usage of the instances and pods.

Kubernetes recommends Heapster as a cluster aggregator to monitor usage of nodes and pods. Very handy if you are deploying in Google Compute (GCE) as it has a pre-build dashboard to hook it to.

Heapster runs on each node, collects statistics of the system and pods which pipes to a storage backend of your choice. A very handy part of Heapster is that export user labels as part of metadata, which I believe can be used to create custom reports on services across nodes.


If you are not using GCE or just don’t want to use their dashboard, you can deploy a combo of InfluxDB and Grafana as a DIY solution. While this seems promising the documentation, as usual, is pretty short on details..

Start by using the “detailed” guide to deploy the add on, which basically consists of:

**wait! don’t run this yet until you finished reading article**

git clone
cd heapster
kubectl create -f deploy/kube-config/influxdb/

These steps exposes Grafana and InfluxDB via the api proxy, you can see them in your deployment by doing:

kubectl cluster-info

This didn’t quite work for me, and while rummaging in the yamls, I found out that this is not really the recommended configuration for live deployments anyway…

So here is what I did:

  1. Remove env variables influxdb-grafana-controller.yaml
  2. Expose service as NodePort or LoadBalancer depends of your preference in grafana-service.yaml. E.g. Under spec section add: type: NodePort
  3. Now run >kubectl create -f deploy/kube-config/influxdb/

You can see the expose port for Grafana by running:
kubectl --namespace=kube-system describe service grafana-service

In this deployment, all the services, rc and pods are added under the kube-system namespace, so remember to add the –namespace flag to your kubectl commands.

Now you should be able to access Grafana on any external ip or dns on the port listed under NodePort. But I was not able to see any data.

Login to Grafana as admin (admin:admin by default), select DataSources>influxdb-datasource and test the connection. The connection is set up as http://monitoring-influxdb:8086, this failed for me.

Since InfluxDB and Grafana are both in the same pod, you can use localhost to access the service. So change the url to http://localhost:8086, save and test the connection again. This worked for me and a minute later I was getting realtime data from nodes and pods.

Proxying Grafana

I run an nginx proxy that terminates https  requests for my domain and a created a https://mydomain/monitoring/ end point as part of it.

For some reason, Grafana needs to know the root-url format that is being accessed from to work properly. This is defined in a config file.. while you could change it and rebuild the image, I preferred to override it via an enviroment variable in the influxdb-grafana-controller.yaml kubernetes file. Just add to the Grafana container section:

value: "%(protocol)s://%(domain)s:%(http_port)s/monitoring"

You can do this with any of the Grafana config values, which allows you to reuse the official Grafana docker image straight from the main registry.

Deploying Kubernetes on Azure

I recently looked to do my first live deployment of kubernetes, after having playing succesfully with minikube.

When trying to deploy kubernetes in public cloud, there is a couple of base options. You could start from scratch or use one of the turnkey solutions.

You have two turnkey solutions fro Azure, Fannel or Weave based. Basically these are two different networking solutions, but the actual turnkey solutions differ more than just the networking layer. I tried both and had issues with both, yeay!! However, I liked the fannel solution over Weave’s straight away. Flannel’s seems to be able to configure and used Azure better. For example, It uses a VM scale sets for the slave nodes, and configures external ips and security groups. This might be because the Flannel solution is sponsored by Microsoft, so I ended up focusing on it over Weave’s.

The documentation is not bad, but a bit short on some basic details. I  did the deployment in both Ubuntu 14.04 and OSX10 and worked in both. The documetation details jq and docker as the main dependencies. I found issues with older versions of jq that are part of the 14.04 Ubuntu archive, so make sure to install the lastest version from the jq website.

Ultimately, seems to be a basic configuration wrapper around azkube, a link to it is burried at the end of the kubernetes doc. Cole Mickens is the main developer for azkube and the turnkey soultion. While looking around his github profile, I found this very useful link on the status of support for Kubernetes in Azure. I would hope this eventually lands in the main kubernetes doc site.

As part of the first install instructions, you will need to provide the subscription and tenant id. I found the subscription id easily enough from the web console, but the tenant id was a bit more elusive. Altough the tenant id is not required for installations of 1.3, the script failed to execute without it. It seems like the best way to find it is the Azure cli tool, which you can get from node.js

npm install azure
azure login
azure account show

This will give you ll the details that you need to set it up. You can then just go ahead or you can edit deatils in  cluster/azure/

You might want to edit the number of VMs that the operation will create. Once you run, you should hopefully get a working kubernetes deployment.

If for any reason, you would like to change the version to be install, you will need to edit the file called “version” under the kubernetes folder setup by the first installation step.

The deployment comes with a ‘utils’ script that makes it very simple do a few things. One is to copy the ssh key that will give you access to the slaves to the master.

$ ./ copykey

From the master, you just need to access the internal ip using the “kube” username and specify your private key for authentication.

Next, I would suggest to configure your local kubectl and deploy the SkyDNS addon. You will really need this to easly access services.

$ ./ configure-kubectl
$ kubectl create -f

And that is it, if you run kubectl get nodes, you will be able to see the master and the slaves.

Since Azure does not have direct integretion for loadbalancer, any services that you expose you will need to configure with a self-deployed solution. But it seems that version 1.4  ofKubernetes is comming with equivalent support for Azure that the current versions boast for  AWS and Co.