Creating clusters in the cloud (GCP, AWS, Azure)

Creating clusters locally is fun. It's also important during development and when trying to troubleshoot problems locally. But, in the end, Kubernetes is designed for cloud-native applications (applications that run in the cloud). Kubernetes doesn't want to be aware of inpidual cloud environments because that doesn't scale. Instead, Kubernetes has the concept of a cloud-provider interface. Every cloud provider can implement this interface and then host Kubernetes. Note that, as of version 1.5, Kubernetes still maintains implementations for many cloud providers in its tree, but in the future, they will be refactored out.

The cloud-provider interface

The cloud-provider interface is a collection of Go data types and interfaces. It is defined in a file called cloud.go, available at https://github.com/kubernetes/cloud-provider/blob/master/cloud.go.

Here is the main interface:

type Interface interface {
     Initialize(clientBuilder controller.ControllerClientBuilder)
  LoadBalancer() (LoadBalancer, bool)
    Instances() (Instances, bool)
     Zones() (Zones, bool)
     Clusters() (Clusters, bool)
   Routes() (Routes, bool)
     ProviderName() string
     HasClusterID() bool
}

This is very clear. Kubernetes operates in terms of instances, zones, clusters, and routes, and also requires access to a load balancer and provider name. The main interface is primarily a gateway. Most methods return yet other interfaces.

For example, the Clusters interface is very simple:

type Clusters interface {
  ListClusters() ([]string, error)
  Master(clusterName string) (string, error)
}

The ListClusters() method returns cluster names. The Master() method returns the IP address or DNS name of the master node.

The other interfaces are not much more complicated. The entire file is 214 lines long (at the time of writing), including lots of comments. The take-home point is that it is not too complicated to implement a Kubernetes provider if your cloud utilizes those basic concepts.

GCP

The Google Cloud Platform (GCP) supports Kubernetes out of the box. The so-called Google Kubernetes Engine (GKE) is a container management solution built on Kubernetes. You don't need to install Kubernetes on GCP, and you can use the Google Cloud API to create Kubernetes clusters and provision them. The fact that Kubernetes is a built-in part of the GCP means it will always be well integrated and well tested, and you don't have to worry about changes in the underlying platform breaking the cloud-provider interface.

All in all, if you plan to base your system on Kubernetes and you don't have any existing code on other cloud platforms, then GCP is a solid choice. It leads the pack in terms of maturity, polish, and depth of integration to GCP services, and is usually the first to update to newer versions of Kubernetes.

AWS

AWS has its own container management service called Elastic Container Service (ECS) that is not based on Kubernetes. It also has a managed Kubernetes service called Elastic Kubernetes Service (EKS). However, you can run Kubernetes yourself on AWS EC2 instances.

In fact, most of the production Kubernetes deployments in the world run on AWS EC2. Let's talk about how to roll your own Kubernetes first and then we'll discuss EKS.

Kubernetes on EC2

AWS was a supported cloud provider from the get-go. There is a lot of documentation on how to set it up. While you could provision some EC2 instances yourself and use kubeadm to create a cluster, I recommend using the Kops (Kubernetes Operations) project. Kops is a Kubernetes project available on GitHub: https://github.com/kubernetes/kops/blob/master/docs/aws.md. It is not part of the core Kubernetes repository, but it is developed and maintained by the Kubernetes developers.

It supports the following features:

• Automated Kubernetes cluster CRUD for the cloud (AWS).
• Highly available Kubernetes clusters.
• Uses a state-sync model for dry-run and automatic idempotency.
• Custom support for kubectl add-ons.
• Kops can generate Terraform configuration.
• Based on a simple meta-model defined in a directory tree.
• Easy command-line syntax.
• Community support.

To create a cluster, you need to do some minimal DNS configuration via route53, set up a S3 bucket to store the cluster configuration, and then run a single command:

kops create cluster --cloud=aws --zones=us-east-1c ${NAME}

The complete instructions can be found here: https://github.com/kubernetes/kops/blob/master/docs/getting_started/aws.md.

At the end of 2017, AWS joined the CNCF and made two big announcements regarding Kubernetes: its own Kubernetes-based container orchestration solution (EKS) and a container-on-demand solution (Fargate).

AWS EKS

AWS EKS is a fully managed and highly available Kubernetes solution. It has three masters running in three AZs. EKS also takes care of upgrades and patching. The great thing about EKS is that it runs a stock Kubernetes. This means you can use all the standard plugins and tools developed by the community. It also opens the door to convenient cluster federation with other cloud providers and/or your own on-premise Kubernetes clusters.

EKS provides deep integration with AWS infrastructure like how IAM authentication is integrated with Kubernetes role-based access control (RBAC).

You can also use AWS PrivateLink if you want to access your Kubernetes masters directly from your own Amazon Virtual Private Cloud (Amazon VPC). With PrivateLink, your Kubernetes masters and the Amazon EKS service endpoint appear as an elastic network interface with private IP addresses in your Amazon VPC.

Another important piece of the puzzle is a special CNI plugin that lets your Kubernetes components talk to each other using AWS networking.

EKS keeps getting better and Amazon demonstrated that it is committed to keeping it up to date and improving it. If you are an AWS shop and getting into Kubernetes, I recommend starting with EKS as opposed to building your own cluster.

The eksctl tool is a great CLI for creating and managing EKS clusters and node groups. I successfully created, deleted, and added nodes to several Kubernetes clusters on AWS using eksctl. Check out https://eksctl.io/.

Fargate

AWS Fargate lets you run containers directly without worrying about provisioning hardware. It eliminates a huge part of the operational complexity at the cost of losing some control. When using Fargate, you package your application into a container, specify CPU and memory requirements, define networking and IAM policies, and you're off to the races. Fargate can run on top of ECS at the moment and EKS in the future. It is a very interesting member in the serverless camp, although it's not directly related to Kubernetes.

Azure

Azure used to have its own container management service. You could use the Mesos-based DC/OS or Docker Swarm to manage them. But you can also use Kubernetes, of course. You could also provision the cluster yourself (for example, using Azure's desired state configuration) and then create the Kubernetes cluster using kubeadm. Azure doesn't have a Kops equivalent, but the Kubespray project is a good option.

However, in the second half of 2017, Azure jumped on the Kubernetes bandwagon too and introduced the Azure Kubernetes Service (AKS). It is similar to Amazon EKS, although it's a little further ahead in its implementation.

AKS provides a REST API as well as a CLI to manage your Kubernetes cluster. However, you can use kubectl and any other Kubernetes tooling directly.

Here are some of the benefits of using AKS:

• Automated Kubernetes version upgrades and patching
• Easy cluster scaling
• Self-healing hosted control plane (masters)
• Cost savings – pay only for running agent pool nodes

AKS also offers integration with Azure Container Instances (ACI), which is similar to AWS Fargate. This means that not only the control plane of your Kubernetes cluster is managed, but also the worker nodes.

Another interesting feature of AKS is AKS-Engine: https://github.com/Azure/aks-engine. AKS-Engine is an open source project, which is the core of AKS. One of the downsides of using a managed service is that you have to accept the choices of the cloud provider. If you have special requirements, then the other option is to create your own cluster, which is a big undertaking. With AKS Engine, you get to take the work the AKS team did and customize just the parts that are important to you.

Other cloud providers

GCP, AWS, and Azure are leading the pack, but there are quite a few other companies that offer managed Kubernetes services. In general, I recommend using these providers if you already have significant business connections or integrations.

Once upon a time in China

If you operate in China with its special constraints and limitations, you should probably use a Chinese cloud platform. There are three big ones: Alibaba, Tencent, and Huawei.

The Chinese Alibaba Cloud is an up and comer on the cloud platform scene. It mimics AWS pretty closely, although its English documentation leaves a lot to be desired. I deployed some production application on Ali baba cloud, but not Kubernetes clusters. The Alibaba cloud supports Kubernetes in several ways via its Alibaba container service for Kubernetes (ACK):

• Run your own dedicated Kubernetes cluster (you must create three master nodes and upgrade and maintain them)
• Use the managed Kubernetes cluster (you're just responsible for the worker nodes)
• Use the serverless Kubernetes cluster via Elastic container instances (ECIs), which is like Fargate and ACI

ACK is a CNCF certified Kubernetes distribution. If you need to deploy cloud-native applications in China, then ACK looks like a solid option.

Tencent is another large Chinese company with its own cloud platform and Kubernetes support. Tencent Kubernetes engine (TKE) seems less mature than ACK.

Finally, the Huawei cloud platform offers the Cloud Container Engine (CCE), which is built on Kubernetes. It supports VMs, bare metal, and GPU accelerated instances.

IBM Kubernetes Service

IBM is investing heavily in Kubernetes. It acquired RedHat at the end of 2018. RedHat was, of course, a major player in the Kubernetes world, building its OpenShift Kubernetes-based platform and contributing RBAC to Kubernetes. IBM has its own cloud platform and offers a managed Kubernetes cluster. You can try it out for free with $200 credit.

IBM is also involved in the development of Istio and Knative, so IKS will likely have deep integration with those up and coming technologies.

Oracle Container Service

Oracle also has a cloud platform and, of course, offers a managed Kubernetes service too, with high availability, bare-metal instances, and multi-AZ support.

In this section, we covered the cloud-provider interface and looked at the recommended ways to create Kubernetes clusters on various cloud providers. The scene is still young, and the tools are evolving quickly. I believe convergence will happen soon. Tools and projects like Kargo and Kubernetes-anywhere have already been deprecated or merged into other projects. Kubeadm has matured and is the underlying foundation of many other tools to bootstrap and create Kubernetes clusters on and off the cloud. Now, let's consider what it takes to create bare-metal clusters where you have to provision the hardware and low-level networking too.