Azure AKS Cluster

Azure Kubernetes Service (AKS) is a fully managed container orchestration service. AKS offers serverless Kubernetes, an integrated continuous integration and continuous delivery (CI/CD) experience, and enterprise-grade security and governance.

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Azure Kubernetes Service (AKS) is a simple means of creating a managed Kubernetes cluster in Microsoft Azure. Rather than manually configuring the cluster, you allow Azure to manage the Kubernetes masters and handle most of the mundane but critical tasks including health monitoring and maintenance, leaving you responsible only for the agent nodes. AKS enables rapid development and deployment of cloud-native apps with less management effort and the added protection of interoperability with Microsoft Azure security.

Use Cases

When you deploy an AKS cluster, the Kubernetes control plane and all nodes are deployed and configured for you. Azure handles management of the masters, allowing you to focus on the agent nodes.

Web applications

Serve your web application out of Kubernetes, and leverage the high availability of running across availability zones and the ease of autoscaling your servers with web traffic.


Build large complex systems out of many small microservices, increasing your overall resiliency by isolating failure domains.


Gain the power of the open-source community by using services like Kubeflow and Argo Workflows for ETL (extract, transform, load) or machine-learning capabilities.

Cloud agnostic

If your application can run on Kubernetes, you can run on any cluster, whether it’s Amazon Elastic Kubernetes (EKS), Google Kubernetes Engine (GKE), AKS, or even your own on-premises cluster.

Configuration Presets


The development preset creates the default node group using a two-core burstable vCPU with 4 GB of memory. No additional node groups are created. Use this preset for development only.


The production preset creates a default node group using an autoscaling standard vCPU (starting with two cores) with 8 GB of memory. One additional node group is also created using another autoscaling standard vCPU (starting with two cores) with 8 GB of memory. This preset has sufficient performance for production environments.


Our bundle includes the following design choices to help simplify your deployment:

Cluster Autoscaling

The AKS Cluster Autoscaler is enabled by default to adjust automatically the number of nodes that run your workloads. The cluster autoscaler component can watch for pods in your cluster that cannot be scheduled because of resource constraints. When the autoscaler detects issues, it will increase the number of nodes in a node pool to meet the application demand.

Azure CNI

With Azure Container Networking Interface (CNI), every pod gets an IP address from the subnet and can be accessed directly. These IP addresses must be unique across your network space and can be used to connect resources together.

Ingress Controller

The Ingress is a Kubernetes resource that lets you configure an HTTP load balancer for applications running on Kubernetes, represented by one or more Services, which are abstractions to permit these applications to appear as network services. Such a load balancer is necessary to deliver those applications to clients outside of the Kubernetes cluster.


If you choose to specify an Azure DNS Zone, external-dns and cert-manager will be automatically installed to manage your DNS records dynamically and to generate SSL certificates to ensure that all internet traffic is encrypted.

Best Practices

The bundle includes a number of best practices without needing any additional work on your part. It uses Azure CNI instead of Kubenet so that other resources can use node IPs. We have also enabled autoscaling for all node pools. For monitoring and collecting metrics, we have set up metrics-server and kube-state-metrics.


To improve security, node groups are deployed into a private subnet. Also, an Azure service principal with minimal privileges is created for AKS to manage Azure DNS zones and Azure Container Registry.


Both metrics-server and kube-state-metrics are installed automatically to provide you with metrics.


After you have deployed a Kubernetes cluster through Massdriver, you may want to interact with the cluster using the powerful kubectl command line tool.

Install Kubectl

You will first need to install kubectl to interact with the kubernetes cluster. Installation instructions for Windows, Mac and Linux can be found here.

Note: While kubectl generally has forwards and backwards compatibility of core capabilities, it is best if your kubectl client version is matched with your kubernetes cluster version. This ensures the best stability and compability for your client.

The standard way to manage connection and authentication details for kubernetes clusters is through a configuration file called a kubeconfig file.

Download the Kubeconfig File

The standard way to manage connection and authentication details for kubernetes clusters is through a configuration file called a kubeconfig file. The kubernetes-cluster artifact that is created when you make a kubernetes cluster in Massdriver contains the basic information needed to create a kubeconfig file. Because of this, Massdriver makes it very easy for you to download a kubeconfig file that will allow you to use kubectl to query and administer your cluster.

To download a kubeconfig file for your cluster, navigate to the project and target where the kubernetes cluster is deployed and move the mouse so it hovers over the artifact connection port. This will pop a windows that allows you to download the artifact in raw JSON, or as a kubeconfig yaml. Select “Kube Config” from the drop down, and click the button. This will download the kubeconfig for the kubernetes cluster to your local system.

Download Kubeconfig

Use the Kubeconfig File

Once the kubeconfig file is downloaded, you can move it to your desired location. By default, kubectl will look for a file named config located in the $HOME/.kube directory. If you would like this to be your default configuration, you can rename and move the file to $HOME/.kube/config.

A single kubeconfig file can hold multiple cluster configurations, and you can select your desired cluster through the use of contexts. Alternatively, you can have multiple kubeconfig files and select your desired file through the KUBECONFIG environment variable or the --kubeconfig flag in kubectl.

Once you’ve configured your environment properly, you should be able to run kubectl commands. Here are some commands to try:

# get a list of all pods in the current namespace
kubectl get pods

# get a list of all pods in the kube-system namespace
kubectl get pods --namespace kube-system

# get a list of all the namespaces
kubectl get namespaces

# view the logs of a running pod in the default namespace
kubectl logs <pod name> --namespace default

# describe the status of a deployment in the foo namespace
kubectl describe deployment <deployment name> --namespace foo

# get a list of all the resources the kubernetes cluster can manage
kubectl api-resources


  • Please note that a default node group must be created and cannot be manipulated, as there can be only one default node group. Additional node groups can be provisioned as needed.
  • We do not currently support filtering compute size options by region or subscription-plan availability.
  • We do not support the following:
    • API server availability with SLA configuration
    • Kubenet network configuration
    • Enabling Azure Policy
    • Integrating AKS and Azure Key Vault
cluster.enable_log_analyticsbooleanEnable Log Analytics for this cluster.
cluster.kubernetes_versionstringThe version of Kubernetes that should be used for this cluster. You will be able to upgrade this version after creating the cluster, but you cannot downgrade the version.
core_services.azure_dns_zones[]array(string)No description
core_services.enable_ingressbooleanEnabling this will create an NGINX Ingress Controller in the cluster, allowing internet traffic to flow into web accessible services within the cluster.
node_groups.additional_node_groups[].max_sizenumberMaximum number of instances in the node group.
node_groups.additional_node_groups[].min_sizenumberMinimum number of instances in the node group.
node_groups.additional_node_groups[].namestringNo description
node_groups.additional_node_groups[].node_sizestringCompute size to use in the node group (D = General Purpose, E = Memory Optimized, F = Compute Optimized). Changing this forces a deletion and re-creation of the node group.
node_groups.default_node_group.max_sizenumberMaximum number of instances in the node group.
node_groups.default_node_group.min_sizenumberMinimum number of instances in the node group.
node_groups.default_node_group.namestringNo description
node_groups.default_node_group.node_sizestringCompute size to use in the node group (D = General Purpose, E = Memory Optimized, F = Compute Optimized). Changing this forces a deletion and re-creation of the node group.