Several years ago, when we started our first adventures in the wonderful world of IoT, we created an application for visualizing real-time streams of sensor data. The sensor data came from custom-built devices that used 2G for connectivity. IoT networks and protocols such as SigFox, NB-IoT or Lora were not mainstream at that time. We leveraged what were then new and often preview-level Azure services such as IoT Hub, Stream Analytics, etc… The architecture was loosely based on lambda architecture with a hot and cold path and stateful window-based stream processing. Fun stuff!
Kubernetes already existed but had not taken off yet. Managed Kubernetes services such as Azure Kubernetes Service (AKS) weren’t a thing.
The application (end-user UI and management) was loosely based on a micro-services pattern and we decided to run the services as Docker containers. At that time, Karim Vaes, now a Program Manager for Azure Storage, worked at our company and was very enthusiastic about Rancher. , Rancher was still v1 and we decided to use it in combination with their own container orchestration framework called Cattle.
Our experience with Rancher was very positive. It was easy to deploy and run in production. The combination of GitHub, Shippable and the Rancher CLI made it extremely easy to deploy our code. Rancher, including Cattle, was very stable for our needs.
In recent years though, the growth of Kubernetes as a container orchestrator platform has far outpaced the others. Using an alternative orchestrator such as Cattle made less sense. Rancher 2.0 is now built around Kubernetes but maintains the same experience as earlier versions such as simple deployment and flexible configuration and management.
In this post, I will look at deploying Rancher 2.0 and importing an existing AKS cluster. This is a basic scenario but it allows you to get a feel for how it works. Indeed, besides deploying your cluster with Rancher from scratch (even on-premises on VMware), you can import existing Kubernetes clusters including managed clusters from Google, Amazon and Azure.
For evaluation purposes, it is best to just run Rancher on a single machine. I deployed an Azure virtual machine with the following properties:
- Operating system: Ubuntu 16.04 LTS
- Size: DS2v3 (2 vCPUs, 8GB of RAM)
- Public IP with open ports 22, 80 and 443
- DNS name: somename.westeurope.cloudapp.azure.com
In my personal DNS zone on CloudFlare, I created a CNAME record for the above DNS name. Later, when you install Rancher you can use the custom DNS name in combination with Let’s Encrypt support.
With Docker installed, install Rancher with the following command:
docker run -d --restart=unless-stopped -p 80:80 -p 443:443 \
rancher/rancher:latest --acme-domain your-custom-domain
More details about the single node installation can be found here. Note that Rancher uses etcd as a datastore. With the command above, the data will be in /var/lib/rancher inside the container. This is ok if you are just doing a test drive. In other cases, use external storage and mount it on /var/lib/rancher.
A single-node install is great for test and development. For production, use the HA install. This will actually run Rancher on Kubernetes. Rancher recommends a dedicated cluster in this scenario.
After installation, just connect https://your-custom-domain and provide a password for the default admin user.
Adding a cluster
To get started, I added an existing three-node AKS cluster to Rancher. After you add the cluster and turn on monitoring, you will see the following screen when you navigate to Clusters and select the imported cluster:
To demonstrate the functionality, I deployed a 3-node cluster (1.11.9) with RBAC enabled and standard networking. After deployment, open up Azure Cloud shell and get your credentials:
az aks list -o table
az aks get-credentials -n cluster-name -g cluster-resource-group
The first command lists the clusters in your subscription, including their name and resource group. The second command configures kubectl, the Kubernetes command line admin tool, which is pre-installed in Azure Cloud Shell. To verify you are connected, the last command simply displays cluster information.
Now that the cluster is deployed, let’s try to import it. In Rancher, navigate to Global – Clusters and click Add Cluster:
Click Import, type a name and click Create. You will get a screen with a command to run:
kubectl apply -f https://your-custom-dns/v3/import/somerandomtext.yaml
Back in the Azure Cloud Shell, run the command:
Continue on in Rancher, the cluster will be added (by the components you deployed above):
Click on the cluster:
To see live metrics, you can click Enable Monitoring. This will install and configure Prometheus and Grafana. You can control several parameters of the deployment such as data retention:
Notice that by default, persistent storage for Grafana and Prometheus is not configured.
Note: with monitoring enabled or not, you will notice the following error in the dashboard:
The error is described here. In short, the components are probably healthy. The error is not related to a Rancher issue but an upstream Kubernetes issue.
When the monitoring API is ready, you will see live metrics and Grafana icons. Clicking on the Graphana icon next to Nodes gives you this:
Of course, Azure provides Container Insights for monitoring. The Grafana dashboards are richer though. On the other hand, querying and alerting on logs and metrics from Container Insights is powerful as well. You can of course enable them all and use the best of both worlds.
We briefly looked at Rancher 2.0 and how it can interact with a existing AKS cluster. An existing cluster is easy to add. Once it is added, adding monitoring is “easy peasy lemon squeezy” as my daughter would call it! 😉 As with Rancher 1.x, I am again pleasantly surprised at how Rancher is able to make complex matters simpler and more fun to work with. There is much more to explore and do of course. That’s for some follow-up posts!