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Package software.amazon.awscdk.services.eks

Amazon EKS Construct Library

See: Description

Package software.amazon.awscdk.services.eks Description

Amazon EKS Construct Library

---

cfn-resources: Stable

cdk-constructs: Stable


This construct library allows you to define Amazon Elastic Container Service for Kubernetes (EKS) clusters. In addition, the library also supports defining Kubernetes resource manifests within EKS clusters.

Table Of Contents

Quick Start

This example defines an Amazon EKS cluster with the following configuration:

 // provisiong a cluster
 Cluster cluster = Cluster.Builder.create(this, "hello-eks")
         .version(KubernetesVersion.V1_21)
         .build();
 
 // apply a kubernetes manifest to the cluster
 cluster.addManifest("mypod", Map.of(
         "apiVersion", "v1",
         "kind", "Pod",
         "metadata", Map.of("name", "mypod"),
         "spec", Map.of(
                 "containers", List.of(Map.of(
                         "name", "hello",
                         "image", "paulbouwer/hello-kubernetes:1.5",
                         "ports", List.of(Map.of("containerPort", 8080)))))));
 

In order to interact with your cluster through kubectl, you can use the aws eks update-kubeconfig AWS CLI command to configure your local kubeconfig. The EKS module will define a CloudFormation output in your stack which contains the command to run. For example:

 Outputs:
 ClusterConfigCommand43AAE40F = aws eks update-kubeconfig --name cluster-xxxxx --role-arn arn:aws:iam::112233445566:role/yyyyy
 

Execute the aws eks update-kubeconfig ... command in your terminal to create or update a local kubeconfig context:

 $ aws eks update-kubeconfig --name cluster-xxxxx --role-arn arn:aws:iam::112233445566:role/yyyyy
 Added new context arn:aws:eks:rrrrr:112233445566:cluster/cluster-xxxxx to /home/boom/.kube/config
 

And now you can simply use kubectl:

 $ kubectl get all -n kube-system
 NAME                           READY   STATUS    RESTARTS   AGE
 pod/aws-node-fpmwv             1/1     Running   0          21m
 pod/aws-node-m9htf             1/1     Running   0          21m
 pod/coredns-5cb4fb54c7-q222j   1/1     Running   0          23m
 pod/coredns-5cb4fb54c7-v9nxx   1/1     Running   0          23m
 ...
 

Architectural Overview

The following is a qualitative diagram of the various possible components involved in the cluster deployment.

  +-----------------------------------------------+               +-----------------+
  |                 EKS Cluster                   |    kubectl    |                 |
  |-----------------------------------------------|<-------------+| Kubectl Handler |
  |                                               |               |                 |
  |                                               |               +-----------------+
  | +--------------------+    +-----------------+ |
  | |                    |    |                 | |
  | | Managed Node Group |    | Fargate Profile | |               +-----------------+
  | |                    |    |                 | |               |                 |
  | +--------------------+    +-----------------+ |               | Cluster Handler |
  |                                               |               |                 |
  +-----------------------------------------------+               +-----------------+
     ^                                   ^                          +
     |                                   |                          |
     | connect self managed capacity     |                          | aws-sdk
     |                                   | create/update/delete     |
     +                                   |                          v
  +--------------------+                 +              +-------------------+
  |                    |                 --------------+| eks.amazonaws.com |
  | Auto Scaling Group |                                +-------------------+
  |                    |
  +--------------------+
 

In a nutshell:

A more detailed breakdown of each is provided further down this README.

Provisioning clusters

Creating a new cluster is done using the Cluster or FargateCluster constructs. The only required property is the kubernetes version.

 Cluster.Builder.create(this, "HelloEKS")
         .version(KubernetesVersion.V1_21)
         .build();
 

You can also use FargateCluster to provision a cluster that uses only fargate workers.

 FargateCluster.Builder.create(this, "HelloEKS")
         .version(KubernetesVersion.V1_21)
         .build();
 

NOTE: Only 1 cluster per stack is supported. If you have a use-case for multiple clusters per stack, or would like to understand more about this limitation, see https://github.com/aws/aws-cdk/issues/10073.

Below you'll find a few important cluster configuration options. First of which is Capacity. Capacity is the amount and the type of worker nodes that are available to the cluster for deploying resources. Amazon EKS offers 3 ways of configuring capacity, which you can combine as you like:

Managed node groups

Amazon EKS managed node groups automate the provisioning and lifecycle management of nodes (Amazon EC2 instances) for Amazon EKS Kubernetes clusters. With Amazon EKS managed node groups, you don’t need to separately provision or register the Amazon EC2 instances that provide compute capacity to run your Kubernetes applications. You can create, update, or terminate nodes for your cluster with a single operation. Nodes run using the latest Amazon EKS optimized AMIs in your AWS account while node updates and terminations gracefully drain nodes to ensure that your applications stay available.

For more details visit Amazon EKS Managed Node Groups.

Managed Node Groups are the recommended way to allocate cluster capacity.

By default, this library will allocate a managed node group with 2 m5.large instances (this instance type suits most common use-cases, and is good value for money).

At cluster instantiation time, you can customize the number of instances and their type:

 Cluster.Builder.create(this, "HelloEKS")
         .version(KubernetesVersion.V1_21)
         .defaultCapacity(5)
         .defaultCapacityInstance(InstanceType.of(InstanceClass.M5, InstanceSize.SMALL))
         .build();
 

To access the node group that was created on your behalf, you can use cluster.defaultNodegroup.

Additional customizations are available post instantiation. To apply them, set the default capacity to 0, and use the cluster.addNodegroupCapacity method:

 Cluster cluster = Cluster.Builder.create(this, "HelloEKS")
         .version(KubernetesVersion.V1_21)
         .defaultCapacity(0)
         .build();
 
 cluster.addNodegroupCapacity("custom-node-group", NodegroupOptions.builder()
         .instanceTypes(List.of(new InstanceType("m5.large")))
         .minSize(4)
         .diskSize(100)
         .amiType(NodegroupAmiType.AL2_X86_64_GPU)
         .build());
 

To set node taints, you can set taints option.

 Cluster cluster;
 
 cluster.addNodegroupCapacity("custom-node-group", NodegroupOptions.builder()
         .instanceTypes(List.of(new InstanceType("m5.large")))
         .taints(List.of(TaintSpec.builder()
                 .effect(TaintEffect.NO_SCHEDULE)
                 .key("foo")
                 .value("bar")
                 .build()))
         .build());
 

Spot Instances Support

Use capacityType to create managed node groups comprised of spot instances. To maximize the availability of your applications while using Spot Instances, we recommend that you configure a Spot managed node group to use multiple instance types with the instanceTypes property.

For more details visit Managed node group capacity types.

 Cluster cluster;
 
 cluster.addNodegroupCapacity("extra-ng-spot", NodegroupOptions.builder()
         .instanceTypes(List.of(
             new InstanceType("c5.large"),
             new InstanceType("c5a.large"),
             new InstanceType("c5d.large")))
         .minSize(3)
         .capacityType(CapacityType.SPOT)
         .build());
 

Launch Template Support

You can specify a launch template that the node group will use. For example, this can be useful if you want to use a custom AMI or add custom user data.

When supplying a custom user data script, it must be encoded in the MIME multi-part archive format, since Amazon EKS merges with its own user data. Visit the Launch Template Docs for mode details.

 Cluster cluster;
 
 
 String userData = "MIME-Version: 1.0\nContent-Type: multipart/mixed; boundary=\"==MYBOUNDARY==\"\n\n--==MYBOUNDARY==\nContent-Type: text/x-shellscript; charset=\"us-ascii\"\n\n#!/bin/bash\necho \"Running custom user data script\"\n\n--==MYBOUNDARY==--\\\n";
 CfnLaunchTemplate lt = CfnLaunchTemplate.Builder.create(this, "LaunchTemplate")
         .launchTemplateData(LaunchTemplateDataProperty.builder()
                 .instanceType("t3.small")
                 .userData(Fn.base64(userData))
                 .build())
         .build();
 
 cluster.addNodegroupCapacity("extra-ng", NodegroupOptions.builder()
         .launchTemplateSpec(LaunchTemplateSpec.builder()
                 .id(lt.getRef())
                 .version(lt.getAttrLatestVersionNumber())
                 .build())
         .build());
 

Note that when using a custom AMI, Amazon EKS doesn't merge any user data. Which means you do not need the multi-part encoding. and are responsible for supplying the required bootstrap commands for nodes to join the cluster. In the following example, /ect/eks/bootstrap.sh from the AMI will be used to bootstrap the node.

 Cluster cluster;
 
 UserData userData = UserData.forLinux();
 userData.addCommands("set -o xtrace", String.format("/etc/eks/bootstrap.sh %s", cluster.getClusterName()));
 CfnLaunchTemplate lt = CfnLaunchTemplate.Builder.create(this, "LaunchTemplate")
         .launchTemplateData(LaunchTemplateDataProperty.builder()
                 .imageId("some-ami-id") // custom AMI
                 .instanceType("t3.small")
                 .userData(Fn.base64(userData.render()))
                 .build())
         .build();
 cluster.addNodegroupCapacity("extra-ng", NodegroupOptions.builder()
         .launchTemplateSpec(LaunchTemplateSpec.builder()
                 .id(lt.getRef())
                 .version(lt.getAttrLatestVersionNumber())
                 .build())
         .build());
 

You may specify one instanceType in the launch template or multiple instanceTypes in the node group, but not both.

For more details visit Launch Template Support.

Graviton 2 instance types are supported including c6g, m6g, r6g and t4g.

Fargate profiles

AWS Fargate is a technology that provides on-demand, right-sized compute capacity for containers. With AWS Fargate, you no longer have to provision, configure, or scale groups of virtual machines to run containers. This removes the need to choose server types, decide when to scale your node groups, or optimize cluster packing.

You can control which pods start on Fargate and how they run with Fargate Profiles, which are defined as part of your Amazon EKS cluster.

See Fargate Considerations in the AWS EKS User Guide.

You can add Fargate Profiles to any EKS cluster defined in your CDK app through the addFargateProfile() method. The following example adds a profile that will match all pods from the "default" namespace:

 Cluster cluster;
 
 cluster.addFargateProfile("MyProfile", FargateProfileOptions.builder()
         .selectors(List.of(Selector.builder().namespace("default").build()))
         .build());
 

You can also directly use the FargateProfile construct to create profiles under different scopes:

 Cluster cluster;
 
 FargateProfile.Builder.create(this, "MyProfile")
         .cluster(cluster)
         .selectors(List.of(Selector.builder().namespace("default").build()))
         .build();
 

To create an EKS cluster that only uses Fargate capacity, you can use FargateCluster. The following code defines an Amazon EKS cluster with a default Fargate Profile that matches all pods from the "kube-system" and "default" namespaces. It is also configured to run CoreDNS on Fargate.

 FargateCluster cluster = FargateCluster.Builder.create(this, "MyCluster")
         .version(KubernetesVersion.V1_21)
         .build();
 

FargateCluster will create a default FargateProfile which can be accessed via the cluster's defaultProfile property. The created profile can also be customized by passing options as with addFargateProfile.

NOTE: Classic Load Balancers and Network Load Balancers are not supported on pods running on Fargate. For ingress, we recommend that you use the ALB Ingress Controller on Amazon EKS (minimum version v1.1.4).

Self-managed nodes

Another way of allocating capacity to an EKS cluster is by using self-managed nodes. EC2 instances that are part of the auto-scaling group will serve as worker nodes for the cluster. This type of capacity is also commonly referred to as EC2 Capacity* or EC2 Nodes.

For a detailed overview please visit Self Managed Nodes.

Creating an auto-scaling group and connecting it to the cluster is done using the cluster.addAutoScalingGroupCapacity method:

 Cluster cluster;
 
 cluster.addAutoScalingGroupCapacity("frontend-nodes", AutoScalingGroupCapacityOptions.builder()
         .instanceType(new InstanceType("t2.medium"))
         .minCapacity(3)
         .vpcSubnets(SubnetSelection.builder().subnetType(SubnetType.PUBLIC).build())
         .build());
 

To connect an already initialized auto-scaling group, use the cluster.connectAutoScalingGroupCapacity() method:

 Cluster cluster;
 AutoScalingGroup asg;
 
 cluster.connectAutoScalingGroupCapacity(asg, AutoScalingGroupOptions.builder().build());
 

To connect a self-managed node group to an imported cluster, use the cluster.connectAutoScalingGroupCapacity() method:

 Cluster cluster;
 AutoScalingGroup asg;
 
 ICluster importedCluster = Cluster.fromClusterAttributes(this, "ImportedCluster", ClusterAttributes.builder()
         .clusterName(cluster.getClusterName())
         .clusterSecurityGroupId(cluster.getClusterSecurityGroupId())
         .build());
 
 importedCluster.connectAutoScalingGroupCapacity(asg, AutoScalingGroupOptions.builder().build());
 

In both cases, the cluster security group will be automatically attached to the auto-scaling group, allowing for traffic to flow freely between managed and self-managed nodes.

Note: The default updateType for auto-scaling groups does not replace existing nodes. Since security groups are determined at launch time, self-managed nodes that were provisioned with version 1.78.0 or lower, will not be updated. To apply the new configuration on all your self-managed nodes, you'll need to replace the nodes using the UpdateType.REPLACING_UPDATE policy for the updateType property.

You can customize the /etc/eks/boostrap.sh script, which is responsible for bootstrapping the node to the EKS cluster. For example, you can use kubeletExtraArgs to add custom node labels or taints.

 Cluster cluster;
 
 cluster.addAutoScalingGroupCapacity("spot", AutoScalingGroupCapacityOptions.builder()
         .instanceType(new InstanceType("t3.large"))
         .minCapacity(2)
         .bootstrapOptions(BootstrapOptions.builder()
                 .kubeletExtraArgs("--node-labels foo=bar,goo=far")
                 .awsApiRetryAttempts(5)
                 .build())
         .build());
 

To disable bootstrapping altogether (i.e. to fully customize user-data), set bootstrapEnabled to false. You can also configure the cluster to use an auto-scaling group as the default capacity:

 Cluster cluster = Cluster.Builder.create(this, "HelloEKS")
         .version(KubernetesVersion.V1_21)
         .defaultCapacityType(DefaultCapacityType.EC2)
         .build();
 

This will allocate an auto-scaling group with 2 m5.large instances (this instance type suits most common use-cases, and is good value for money). To access the AutoScalingGroup that was created on your behalf, you can use cluster.defaultCapacity. You can also independently create an AutoScalingGroup and connect it to the cluster using the cluster.connectAutoScalingGroupCapacity method:

 Cluster cluster;
 AutoScalingGroup asg;
 
 cluster.connectAutoScalingGroupCapacity(asg, AutoScalingGroupOptions.builder().build());
 

This will add the necessary user-data to access the apiserver and configure all connections, roles, and tags needed for the instances in the auto-scaling group to properly join the cluster.

Spot Instances

When using self-managed nodes, you can configure the capacity to use spot instances, greatly reducing capacity cost. To enable spot capacity, use the spotPrice property:

 Cluster cluster;
 
 cluster.addAutoScalingGroupCapacity("spot", AutoScalingGroupCapacityOptions.builder()
         .spotPrice("0.1094")
         .instanceType(new InstanceType("t3.large"))
         .maxCapacity(10)
         .build());
 

Spot instance nodes will be labeled with lifecycle=Ec2Spot and tainted with PreferNoSchedule.

The AWS Node Termination Handler DaemonSet will be installed from Amazon EKS Helm chart repository on these nodes. The termination handler ensures that the Kubernetes control plane responds appropriately to events that can cause your EC2 instance to become unavailable, such as EC2 maintenance events and EC2 Spot interruptions and helps gracefully stop all pods running on spot nodes that are about to be terminated.

Handler Version: 1.7.0

Chart Version: 0.9.5

To disable the installation of the termination handler, set the spotInterruptHandler property to false. This applies both to addAutoScalingGroupCapacity and connectAutoScalingGroupCapacity.

Bottlerocket

Bottlerocket is a Linux-based open-source operating system that is purpose-built by Amazon Web Services for running containers on virtual machines or bare metal hosts.

Bottlerocket is supported when using managed nodegroups or self-managed auto-scaling groups.

To create a Bottlerocket managed nodegroup:

 Cluster cluster;
 
 cluster.addNodegroupCapacity("BottlerocketNG", NodegroupOptions.builder()
         .amiType(NodegroupAmiType.BOTTLEROCKET_X86_64)
         .build());
 

The following example will create an auto-scaling group of 2 t3.small Linux instances running with the Bottlerocket AMI.

 Cluster cluster;
 
 cluster.addAutoScalingGroupCapacity("BottlerocketNodes", AutoScalingGroupCapacityOptions.builder()
         .instanceType(new InstanceType("t3.small"))
         .minCapacity(2)
         .machineImageType(MachineImageType.BOTTLEROCKET)
         .build());
 

The specific Bottlerocket AMI variant will be auto selected according to the k8s version for the x86_64 architecture. For example, if the Amazon EKS cluster version is 1.17, the Bottlerocket AMI variant will be auto selected as aws-k8s-1.17 behind the scene.

See Variants for more details.

Please note Bottlerocket does not allow to customize bootstrap options and bootstrapOptions properties is not supported when you create the Bottlerocket capacity.

For more details about Bottlerocket, see Bottlerocket FAQs and Bottlerocket Open Source Blog.

Endpoint Access

When you create a new cluster, Amazon EKS creates an endpoint for the managed Kubernetes API server that you use to communicate with your cluster (using Kubernetes management tools such as kubectl)

By default, this API server endpoint is public to the internet, and access to the API server is secured using a combination of AWS Identity and Access Management (IAM) and native Kubernetes Role Based Access Control (RBAC).

You can configure the cluster endpoint access by using the endpointAccess property:

 Cluster cluster = Cluster.Builder.create(this, "hello-eks")
         .version(KubernetesVersion.V1_21)
         .endpointAccess(EndpointAccess.PRIVATE)
         .build();
 

The default value is eks.EndpointAccess.PUBLIC_AND_PRIVATE. Which means the cluster endpoint is accessible from outside of your VPC, but worker node traffic and kubectl commands issued by this library stay within your VPC.

Alb Controller

Some Kubernetes resources are commonly implemented on AWS with the help of the ALB Controller.

From the docs:

AWS Load Balancer Controller is a controller to help manage Elastic Load Balancers for a Kubernetes cluster.

  • It satisfies Kubernetes Ingress resources by provisioning Application Load Balancers.
  • It satisfies Kubernetes Service resources by provisioning Network Load Balancers.

To deploy the controller on your EKS cluster, configure the albController property:

 Cluster.Builder.create(this, "HelloEKS")
         .version(KubernetesVersion.V1_21)
         .albController(AlbControllerOptions.builder()
                 .version(AlbControllerVersion.V2_3_1)
                 .build())
         .build();
 

Querying the controller pods should look something like this:

 ❯ kubectl get pods -n kube-system
 NAME                                            READY   STATUS    RESTARTS   AGE
 aws-load-balancer-controller-76bd6c7586-d929p   1/1     Running   0          109m
 aws-load-balancer-controller-76bd6c7586-fqxph   1/1     Running   0          109m
 ...
 ...
 

Every Kubernetes manifest that utilizes the ALB Controller is effectively dependant on the controller. If the controller is deleted before the manifest, it might result in dangling ELB/ALB resources. Currently, the EKS construct library does not detect such dependencies, and they should be done explicitly.

For example:

 Cluster cluster;
 
 KubernetesManifest manifest = cluster.addManifest("manifest", Map.of());
 if (cluster.getAlbController()) {
     manifest.node.addDependency(cluster.getAlbController());
 }
 

VPC Support

You can specify the VPC of the cluster using the vpc and vpcSubnets properties:

 Vpc vpc;
 
 
 Cluster.Builder.create(this, "HelloEKS")
         .version(KubernetesVersion.V1_21)
         .vpc(vpc)
         .vpcSubnets(List.of(SubnetSelection.builder().subnetType(SubnetType.PRIVATE).build()))
         .build();
 

Note: Isolated VPCs (i.e with no internet access) are not currently supported. See https://github.com/aws/aws-cdk/issues/12171

If you do not specify a VPC, one will be created on your behalf, which you can then access via cluster.vpc. The cluster VPC will be associated to any EKS managed capacity (i.e Managed Node Groups and Fargate Profiles).

Please note that the vpcSubnets property defines the subnets where EKS will place the control plane ENIs. To choose the subnets where EKS will place the worker nodes, please refer to the Provisioning clusters section above.

If you allocate self managed capacity, you can specify which subnets should the auto-scaling group use:

 Vpc vpc;
 Cluster cluster;
 
 cluster.addAutoScalingGroupCapacity("nodes", AutoScalingGroupCapacityOptions.builder()
         .vpcSubnets(SubnetSelection.builder().subnets(vpc.getPrivateSubnets()).build())
         .instanceType(new InstanceType("t2.medium"))
         .build());
 

There are two additional components you might want to provision within the VPC.

Kubectl Handler

The KubectlHandler is a Lambda function responsible to issuing kubectl and helm commands against the cluster when you add resource manifests to the cluster.

The handler association to the VPC is derived from the endpointAccess configuration. The rule of thumb is: If the cluster VPC can be associated, it will be.

Breaking this down, it means that if the endpoint exposes private access (via EndpointAccess.PRIVATE or EndpointAccess.PUBLIC_AND_PRIVATE), and the VPC contains private subnets, the Lambda function will be provisioned inside the VPC and use the private subnets to interact with the cluster. This is the common use-case.

If the endpoint does not expose private access (via EndpointAccess.PUBLIC) or the VPC does not contain private subnets, the function will not be provisioned within the VPC.

If your use-case requires control over the IAM role that the KubeCtl Handler assumes, a custom role can be passed through the ClusterProps (as kubectlLambdaRole) of the EKS Cluster construct.

Cluster Handler

The ClusterHandler is a set of Lambda functions (onEventHandler, isCompleteHandler) responsible for interacting with the EKS API in order to control the cluster lifecycle. To provision these functions inside the VPC, set the placeClusterHandlerInVpc property to true. This will place the functions inside the private subnets of the VPC based on the selection strategy specified in the vpcSubnets property.

You can configure the environment of the Cluster Handler functions by specifying it at cluster instantiation. For example, this can be useful in order to configure an http proxy:

 SecurityGroup proxyInstanceSecurityGroup;
 
 Cluster cluster = Cluster.Builder.create(this, "hello-eks")
         .version(KubernetesVersion.V1_21)
         .clusterHandlerEnvironment(Map.of(
                 "https_proxy", "http://proxy.myproxy.com"))
         /**
            * If the proxy is not open publicly, you can pass a security group to the
            * Cluster Handler Lambdas so that it can reach the proxy.
            */
         .clusterHandlerSecurityGroup(proxyInstanceSecurityGroup)
         .build();
 

Kubectl Support

The resources are created in the cluster by running kubectl apply from a python lambda function.

By default, CDK will create a new python lambda function to apply your k8s manifests. If you want to use an existing kubectl provider function, for example with tight trusted entities on your IAM Roles - you can import the existing provider and then use the imported provider when importing the cluster:

 IRole handlerRole = Role.fromRoleArn(this, "HandlerRole", "arn:aws:iam::123456789012:role/lambda-role");
 IKubectlProvider kubectlProvider = KubectlProvider.fromKubectlProviderAttributes(this, "KubectlProvider", KubectlProviderAttributes.builder()
         .functionArn("arn:aws:lambda:us-east-2:123456789012:function:my-function:1")
         .kubectlRoleArn("arn:aws:iam::123456789012:role/kubectl-role")
         .handlerRole(handlerRole)
         .build());
 
 ICluster cluster = Cluster.fromClusterAttributes(this, "Cluster", ClusterAttributes.builder()
         .clusterName("cluster")
         .kubectlProvider(kubectlProvider)
         .build());
 

Environment

You can configure the environment of this function by specifying it at cluster instantiation. For example, this can be useful in order to configure an http proxy:

 Cluster cluster = Cluster.Builder.create(this, "hello-eks")
         .version(KubernetesVersion.V1_21)
         .kubectlEnvironment(Map.of(
                 "http_proxy", "http://proxy.myproxy.com"))
         .build();
 

Runtime

The kubectl handler uses kubectl, helm and the aws CLI in order to interact with the cluster. These are bundled into AWS Lambda layers included in the @aws-cdk/lambda-layer-awscli and @aws-cdk/lambda-layer-kubectl modules.

You can specify a custom lambda.LayerVersion if you wish to use a different version of these tools. The handler expects the layer to include the following three executables:

 helm/helm
 kubectl/kubectl
 awscli/aws
 

See more information in the Dockerfile for @aws-cdk/lambda-layer-awscli and the Dockerfile for @aws-cdk/lambda-layer-kubectl.

 LayerVersion layer = LayerVersion.Builder.create(this, "KubectlLayer")
         .code(Code.fromAsset("layer.zip"))
         .build();
 

Now specify when the cluster is defined:

 LayerVersion layer;
 Vpc vpc;
 
 
 Cluster cluster1 = Cluster.Builder.create(this, "MyCluster")
         .kubectlLayer(layer)
         .vpc(vpc)
         .clusterName("cluster-name")
         .version(KubernetesVersion.V1_21)
         .build();
 
 // or
 ICluster cluster2 = Cluster.fromClusterAttributes(this, "MyCluster", ClusterAttributes.builder()
         .kubectlLayer(layer)
         .vpc(vpc)
         .clusterName("cluster-name")
         .build());
 

Memory

By default, the kubectl provider is configured with 1024MiB of memory. You can use the kubectlMemory option to specify the memory size for the AWS Lambda function:

 // or
 Vpc vpc;
 Cluster.Builder.create(this, "MyCluster")
         .kubectlMemory(Size.gibibytes(4))
         .version(KubernetesVersion.V1_21)
         .build();
 Cluster.fromClusterAttributes(this, "MyCluster", ClusterAttributes.builder()
         .kubectlMemory(Size.gibibytes(4))
         .vpc(vpc)
         .clusterName("cluster-name")
         .build());
 

ARM64 Support

Instance types with ARM64 architecture are supported in both managed nodegroup and self-managed capacity. Simply specify an ARM64 instanceType (such as m6g.medium), and the latest Amazon Linux 2 AMI for ARM64 will be automatically selected.

 Cluster cluster;
 
 // add a managed ARM64 nodegroup
 cluster.addNodegroupCapacity("extra-ng-arm", NodegroupOptions.builder()
         .instanceTypes(List.of(new InstanceType("m6g.medium")))
         .minSize(2)
         .build());
 
 // add a self-managed ARM64 nodegroup
 cluster.addAutoScalingGroupCapacity("self-ng-arm", AutoScalingGroupCapacityOptions.builder()
         .instanceType(new InstanceType("m6g.medium"))
         .minCapacity(2)
         .build());
 

Masters Role

When you create a cluster, you can specify a mastersRole. The Cluster construct will associate this role with the system:masters RBAC group, giving it super-user access to the cluster.

 Role role;
 
 Cluster.Builder.create(this, "HelloEKS")
         .version(KubernetesVersion.V1_21)
         .mastersRole(role)
         .build();
 

If you do not specify it, a default role will be created on your behalf, that can be assumed by anyone in the account with sts:AssumeRole permissions for this role.

This is the role you see as part of the stack outputs mentioned in the Quick Start.

 $ aws eks update-kubeconfig --name cluster-xxxxx --role-arn arn:aws:iam::112233445566:role/yyyyy
 Added new context arn:aws:eks:rrrrr:112233445566:cluster/cluster-xxxxx to /home/boom/.kube/config
 

Encryption

When you create an Amazon EKS cluster, envelope encryption of Kubernetes secrets using the AWS Key Management Service (AWS KMS) can be enabled. The documentation on creating a cluster can provide more details about the customer master key (CMK) that can be used for the encryption.

You can use the secretsEncryptionKey to configure which key the cluster will use to encrypt Kubernetes secrets. By default, an AWS Managed key will be used.

This setting can only be specified when the cluster is created and cannot be updated.

 Key secretsKey = new Key(this, "SecretsKey");
 Cluster cluster = Cluster.Builder.create(this, "MyCluster")
         .secretsEncryptionKey(secretsKey)
         .version(KubernetesVersion.V1_21)
         .build();
 

You can also use a similar configuration for running a cluster built using the FargateCluster construct.

 Key secretsKey = new Key(this, "SecretsKey");
 FargateCluster cluster = FargateCluster.Builder.create(this, "MyFargateCluster")
         .secretsEncryptionKey(secretsKey)
         .version(KubernetesVersion.V1_21)
         .build();
 

The Amazon Resource Name (ARN) for that CMK can be retrieved.

 Cluster cluster;
 
 String clusterEncryptionConfigKeyArn = cluster.getClusterEncryptionConfigKeyArn();
 

Permissions and Security

Amazon EKS provides several mechanism of securing the cluster and granting permissions to specific IAM users and roles.

AWS IAM Mapping

As described in the Amazon EKS User Guide, you can map AWS IAM users and roles to Kubernetes Role-based access control (RBAC).

The Amazon EKS construct manages the aws-auth ConfigMap Kubernetes resource on your behalf and exposes an API through the cluster.awsAuth for mapping users, roles and accounts.

Furthermore, when auto-scaling group capacity is added to the cluster, the IAM instance role of the auto-scaling group will be automatically mapped to RBAC so nodes can connect to the cluster. No manual mapping is required.

For example, let's say you want to grant an IAM user administrative privileges on your cluster:

 Cluster cluster;
 
 User adminUser = new User(this, "Admin");
 cluster.awsAuth.addUserMapping(adminUser, AwsAuthMapping.builder().groups(List.of("system:masters")).build());
 

A convenience method for mapping a role to the system:masters group is also available:

 Cluster cluster;
 Role role;
 
 cluster.awsAuth.addMastersRole(role);
 

Cluster Security Group

When you create an Amazon EKS cluster, a cluster security group is automatically created as well. This security group is designed to allow all traffic from the control plane and managed node groups to flow freely between each other.

The ID for that security group can be retrieved after creating the cluster.

 Cluster cluster;
 
 String clusterSecurityGroupId = cluster.getClusterSecurityGroupId();
 

Node SSH Access

If you want to be able to SSH into your worker nodes, you must already have an SSH key in the region you're connecting to and pass it when you add capacity to the cluster. You must also be able to connect to the hosts (meaning they must have a public IP and you should be allowed to connect to them on port 22):

See SSH into nodes for a code example.

If you want to SSH into nodes in a private subnet, you should set up a bastion host in a public subnet. That setup is recommended, but is unfortunately beyond the scope of this documentation.

Service Accounts

With services account you can provide Kubernetes Pods access to AWS resources.

 Cluster cluster;
 
 // add service account
 ServiceAccount serviceAccount = cluster.addServiceAccount("MyServiceAccount");
 
 Bucket bucket = new Bucket(this, "Bucket");
 bucket.grantReadWrite(serviceAccount);
 
 KubernetesManifest mypod = cluster.addManifest("mypod", Map.of(
         "apiVersion", "v1",
         "kind", "Pod",
         "metadata", Map.of("name", "mypod"),
         "spec", Map.of(
                 "serviceAccountName", serviceAccount.getServiceAccountName(),
                 "containers", List.of(Map.of(
                         "name", "hello",
                         "image", "paulbouwer/hello-kubernetes:1.5",
                         "ports", List.of(Map.of("containerPort", 8080)))))));
 
 // create the resource after the service account.
 mypod.node.addDependency(serviceAccount);
 
 // print the IAM role arn for this service account
 // print the IAM role arn for this service account
 CfnOutput.Builder.create(this, "ServiceAccountIamRole").value(serviceAccount.getRole().getRoleArn()).build();
 

Note that using serviceAccount.serviceAccountName above does not translate into a resource dependency. This is why an explicit dependency is needed. See https://github.com/aws/aws-cdk/issues/9910 for more details.

You can also add service accounts to existing clusters. To do so, pass the openIdConnectProvider property when you import the cluster into the application.

 // or create a new one using an existing issuer url
 String issuerUrl;
 // you can import an existing provider
 IOpenIdConnectProvider provider = OpenIdConnectProvider.fromOpenIdConnectProviderArn(this, "Provider", "arn:aws:iam::123456:oidc-provider/oidc.eks.eu-west-1.amazonaws.com/id/AB123456ABC");
 OpenIdConnectProvider provider2 = OpenIdConnectProvider.Builder.create(this, "Provider")
         .url(issuerUrl)
         .build();
 
 ICluster cluster = Cluster.fromClusterAttributes(this, "MyCluster", ClusterAttributes.builder()
         .clusterName("Cluster")
         .openIdConnectProvider(provider)
         .kubectlRoleArn("arn:aws:iam::123456:role/service-role/k8sservicerole")
         .build());
 
 ServiceAccount serviceAccount = cluster.addServiceAccount("MyServiceAccount");
 
 Bucket bucket = new Bucket(this, "Bucket");
 bucket.grantReadWrite(serviceAccount);
 

Note that adding service accounts requires running kubectl commands against the cluster. This means you must also pass the kubectlRoleArn when importing the cluster. See Using existing Clusters.

Applying Kubernetes Resources

The library supports several popular resource deployment mechanisms, among which are:

Kubernetes Manifests

The KubernetesManifest construct or cluster.addManifest method can be used to apply Kubernetes resource manifests to this cluster.

When using cluster.addManifest, the manifest construct is defined within the cluster's stack scope. If the manifest contains attributes from a different stack which depend on the cluster stack, a circular dependency will be created and you will get a synth time error. To avoid this, directly use new KubernetesManifest to create the manifest in the scope of the other stack.

The following examples will deploy the paulbouwer/hello-kubernetes service on the cluster:

 Cluster cluster;
 
 Map<String, String> appLabel = Map.of("app", "hello-kubernetes");
 
 Map<String, Object> deployment = Map.of(
         "apiVersion", "apps/v1",
         "kind", "Deployment",
         "metadata", Map.of("name", "hello-kubernetes"),
         "spec", Map.of(
                 "replicas", 3,
                 "selector", Map.of("matchLabels", appLabel),
                 "template", Map.of(
                         "metadata", Map.of("labels", appLabel),
                         "spec", Map.of(
                                 "containers", List.of(Map.of(
                                         "name", "hello-kubernetes",
                                         "image", "paulbouwer/hello-kubernetes:1.5",
                                         "ports", List.of(Map.of("containerPort", 8080))))))));
 
 Map<String, Object> service = Map.of(
         "apiVersion", "v1",
         "kind", "Service",
         "metadata", Map.of("name", "hello-kubernetes"),
         "spec", Map.of(
                 "type", "LoadBalancer",
                 "ports", List.of(Map.of("port", 80, "targetPort", 8080)),
                 "selector", appLabel));
 
 // option 1: use a construct
 // option 1: use a construct
 KubernetesManifest.Builder.create(this, "hello-kub")
         .cluster(cluster)
         .manifest(List.of(deployment, service))
         .build();
 
 // or, option2: use `addManifest`
 cluster.addManifest("hello-kub", service, deployment);
 

ALB Controller Integration

The KubernetesManifest construct can detect ingress resources inside your manifest and automatically add the necessary annotations so they are picked up by the ALB Controller.

See Alb Controller

To that end, it offers the following properties:

Adding resources from a URL

The following example will deploy the resource manifest hosting on remote server:

 // This example is only available in TypeScript
 
 import * as yaml from 'js-yaml';
 import * as request from 'sync-request';
 
 declare const cluster: eks.Cluster;
 const manifestUrl = 'https://url/of/manifest.yaml';
 const manifest = yaml.safeLoadAll(request('GET', manifestUrl).getBody());
 cluster.addManifest('my-resource', manifest);
 

Dependencies

There are cases where Kubernetes resources must be deployed in a specific order. For example, you cannot define a resource in a Kubernetes namespace before the namespace was created.

You can represent dependencies between KubernetesManifests using resource.node.addDependency():

 Cluster cluster;
 
 KubernetesManifest namespace = cluster.addManifest("my-namespace", Map.of(
         "apiVersion", "v1",
         "kind", "Namespace",
         "metadata", Map.of("name", "my-app")));
 
 KubernetesManifest service = cluster.addManifest("my-service", Map.of(
         "metadata", Map.of(
                 "name", "myservice",
                 "namespace", "my-app"),
         "spec", Map.of()));
 
 service.node.addDependency(namespace);
 

NOTE: when a KubernetesManifest includes multiple resources (either directly or through cluster.addManifest()) (e.g. cluster.addManifest('foo', r1, r2, r3,...)), these resources will be applied as a single manifest via kubectl and will be applied sequentially (the standard behavior in kubectl).


Since Kubernetes manifests are implemented as CloudFormation resources in the CDK. This means that if the manifest is deleted from your code (or the stack is deleted), the next cdk deploy will issue a kubectl delete command and the Kubernetes resources in that manifest will be deleted.

Resource Pruning

When a resource is deleted from a Kubernetes manifest, the EKS module will automatically delete these resources by injecting a prune label to all manifest resources. This label is then passed to kubectl apply --prune.

Pruning is enabled by default but can be disabled through the prune option when a cluster is defined:

 Cluster.Builder.create(this, "MyCluster")
         .version(KubernetesVersion.V1_21)
         .prune(false)
         .build();
 

Manifests Validation

The kubectl CLI supports applying a manifest by skipping the validation. This can be accomplished by setting the skipValidation flag to true in the KubernetesManifest props.

 Cluster cluster;
 
 KubernetesManifest.Builder.create(this, "HelloAppWithoutValidation")
         .cluster(cluster)
         .manifest(List.of(Map.of("foo", "bar")))
         .skipValidation(true)
         .build();
 

Helm Charts

The HelmChart construct or cluster.addHelmChart method can be used to add Kubernetes resources to this cluster using Helm.

When using cluster.addHelmChart, the manifest construct is defined within the cluster's stack scope. If the manifest contains attributes from a different stack which depend on the cluster stack, a circular dependency will be created and you will get a synth time error. To avoid this, directly use new HelmChart to create the chart in the scope of the other stack.

The following example will install the NGINX Ingress Controller to your cluster using Helm.

 Cluster cluster;
 
 // option 1: use a construct
 // option 1: use a construct
 HelmChart.Builder.create(this, "NginxIngress")
         .cluster(cluster)
         .chart("nginx-ingress")
         .repository("https://helm.nginx.com/stable")
         .namespace("kube-system")
         .build();
 
 // or, option2: use `addHelmChart`
 cluster.addHelmChart("NginxIngress", HelmChartOptions.builder()
         .chart("nginx-ingress")
         .repository("https://helm.nginx.com/stable")
         .namespace("kube-system")
         .build());
 

Helm charts will be installed and updated using helm upgrade --install, where a few parameters are being passed down (such as repo, values, version, namespace, wait, timeout, etc). This means that if the chart is added to CDK with the same release name, it will try to update the chart in the cluster.

Additionally, the chartAsset property can be an aws-s3-assets.Asset. This allows the use of local, private helm charts.

 import software.amazon.awscdk.services.s3.assets.*;
 
 Cluster cluster;
 
 Asset chartAsset = Asset.Builder.create(this, "ChartAsset")
         .path("/path/to/asset")
         .build();
 
 cluster.addHelmChart("test-chart", HelmChartOptions.builder()
         .chartAsset(chartAsset)
         .build());
 

Helm charts are implemented as CloudFormation resources in CDK. This means that if the chart is deleted from your code (or the stack is deleted), the next cdk deploy will issue a helm uninstall command and the Helm chart will be deleted.

When there is no release defined, a unique ID will be allocated for the release based on the construct path.

By default, all Helm charts will be installed concurrently. In some cases, this could cause race conditions where two Helm charts attempt to deploy the same resource or if Helm charts depend on each other. You can use chart.node.addDependency() in order to declare a dependency order between charts:

 Cluster cluster;
 
 HelmChart chart1 = cluster.addHelmChart("MyChart", HelmChartOptions.builder()
         .chart("foo")
         .build());
 HelmChart chart2 = cluster.addHelmChart("MyChart", HelmChartOptions.builder()
         .chart("bar")
         .build());
 
 chart2.node.addDependency(chart1);
 

CDK8s Charts

CDK8s is an open-source library that enables Kubernetes manifest authoring using familiar programming languages. It is founded on the same technologies as the AWS CDK, such as constructs and jsii.

To learn more about cdk8s, visit the Getting Started tutorials.

The EKS module natively integrates with cdk8s and allows you to apply cdk8s charts on AWS EKS clusters via the cluster.addCdk8sChart method.

In addition to cdk8s, you can also use cdk8s+, which provides higher level abstraction for the core kubernetes api objects. You can think of it like the L2 constructs for Kubernetes. Any other cdk8s based libraries are also supported, for example cdk8s-debore.

To get started, add the following dependencies to your package.json file:

 "dependencies": {
   "cdk8s": "^1.0.0",
   "cdk8s-plus-21": "^1.0.0-beta.38",
   "constructs": "^3.3.69"
 }
 

Note that here we are using cdk8s-plus-21 as we are targeting Kubernetes version 1.21.0. If you operate a different kubernetes version, you should use the corresponding cdk8s-plus-XX library. See Select the appropriate cdk8s+ library for more details.

Similarly to how you would create a stack by extending @aws-cdk/core.Stack, we recommend you create a chart of your own that extends cdk8s.Chart, and add your kubernetes resources to it. You can use aws-cdk construct attributes and properties inside your cdk8s construct freely.

In this example we create a chart that accepts an s3.Bucket and passes its name to a kubernetes pod as an environment variable.

Notice that the chart must accept a constructs.Construct type as its scope, not an @aws-cdk/core.Construct as you would normally use. For this reason, to avoid possible confusion, we will create the chart in a separate file:

+ my-chart.ts

 import software.amazon.awscdk.services.s3.*;
 import software.constructs.*;
 import org.cdk8s.*;
 import org.cdk8s.plus21.*;
 
 public class MyChartProps {
     private Bucket bucket;
     public Bucket getBucket() {
         return this.bucket;
     }
     public MyChartProps bucket(Bucket bucket) {
         this.bucket = bucket;
         return this;
     }
 }
 
 public class MyChart extends Chart {
     public MyChart(Construct scope, String id, MyChartProps props) {
         super(scope, id);
 
         Pod.Builder.create(this, "Pod")
                 .containers(List.of(
                     Container.Builder.create()
                             .image("my-image")
                             .env(Map.of(
                                     "BUCKET_NAME", EnvValue.fromValue(props.getBucket().getBucketName())))
                             .build()))
                 .build();
     }
 }
 

Then, in your AWS CDK app:

 Cluster cluster;
 
 
 // some bucket..
 Bucket bucket = new Bucket(this, "Bucket");
 
 // create a cdk8s chart and use `cdk8s.App` as the scope.
 MyChart myChart = new MyChart(new App(), "MyChart", new MyChartProps().bucket(bucket));
 
 // add the cdk8s chart to the cluster
 cluster.addCdk8sChart("my-chart", myChart);
 

Custom CDK8s Constructs

You can also compose a few stock cdk8s+ constructs into your own custom construct. However, since mixing scopes between aws-cdk and cdk8s is currently not supported, the Construct class you'll need to use is the one from the constructs module, and not from @aws-cdk/core like you normally would. This is why we used new cdk8s.App() as the scope of the chart above.

 import software.constructs.*;
 import org.cdk8s.*;
 import org.cdk8s.plus21.*;
 
 public class LoadBalancedWebService {
     private Number port;
     public Number getPort() {
         return this.port;
     }
     public LoadBalancedWebService port(Number port) {
         this.port = port;
         return this;
     }
     private String image;
     public String getImage() {
         return this.image;
     }
     public LoadBalancedWebService image(String image) {
         this.image = image;
         return this;
     }
     private Number replicas;
     public Number getReplicas() {
         return this.replicas;
     }
     public LoadBalancedWebService replicas(Number replicas) {
         this.replicas = replicas;
         return this;
     }
 }
 
 App app = new App();
 Chart chart = new Chart(app, "my-chart");
 
 public class LoadBalancedWebService extends Construct {
     public LoadBalancedWebService(Construct scope, String id, LoadBalancedWebService props) {
         super(scope, id);
 
         Deployment deployment = Deployment.Builder.create(chart, "Deployment")
                 .replicas(props.getReplicas())
                 .containers(List.of(Container.Builder.create().image(props.getImage()).build()))
                 .build();
 
         deployment.exposeViaService(ExposeDeploymentViaServiceOptions.builder()
                 .port(props.getPort())
                 .serviceType(ServiceType.LOAD_BALANCER)
                 .build());
     }
 }
 

Manually importing k8s specs and CRD's

If you find yourself unable to use cdk8s+, or just like to directly use the k8s native objects or CRD's, you can do so by manually importing them using the cdk8s-cli.

See Importing kubernetes objects for detailed instructions.

Patching Kubernetes Resources

The KubernetesPatch construct can be used to update existing kubernetes resources. The following example can be used to patch the hello-kubernetes deployment from the example above with 5 replicas.

 Cluster cluster;
 
 KubernetesPatch.Builder.create(this, "hello-kub-deployment-label")
         .cluster(cluster)
         .resourceName("deployment/hello-kubernetes")
         .applyPatch(Map.of("spec", Map.of("replicas", 5)))
         .restorePatch(Map.of("spec", Map.of("replicas", 3)))
         .build();
 

Querying Kubernetes Resources

The KubernetesObjectValue construct can be used to query for information about kubernetes objects, and use that as part of your CDK application.

For example, you can fetch the address of a LoadBalancer type service:

 Cluster cluster;
 
 // query the load balancer address
 KubernetesObjectValue myServiceAddress = KubernetesObjectValue.Builder.create(this, "LoadBalancerAttribute")
         .cluster(cluster)
         .objectType("service")
         .objectName("my-service")
         .jsonPath(".status.loadBalancer.ingress[0].hostname")
         .build();
 
 // pass the address to a lambda function
 Function proxyFunction = Function.Builder.create(this, "ProxyFunction")
         .handler("index.handler")
         .code(Code.fromInline("my-code"))
         .runtime(Runtime.NODEJS_14_X)
         .environment(Map.of(
                 "myServiceAddress", myServiceAddress.getValue()))
         .build();
 

Specifically, since the above use-case is quite common, there is an easier way to access that information:

 Cluster cluster;
 
 String loadBalancerAddress = cluster.getServiceLoadBalancerAddress("my-service");
 

Using existing clusters

The Amazon EKS library allows defining Kubernetes resources such as Kubernetes manifests and Helm charts on clusters that are not defined as part of your CDK app.

First, you'll need to "import" a cluster to your CDK app. To do that, use the eks.Cluster.fromClusterAttributes() static method:

 ICluster cluster = Cluster.fromClusterAttributes(this, "MyCluster", ClusterAttributes.builder()
         .clusterName("my-cluster-name")
         .kubectlRoleArn("arn:aws:iam::1111111:role/iam-role-that-has-masters-access")
         .build());
 

Then, you can use addManifest or addHelmChart to define resources inside your Kubernetes cluster. For example:

 Cluster cluster;
 
 cluster.addManifest("Test", Map.of(
         "apiVersion", "v1",
         "kind", "ConfigMap",
         "metadata", Map.of(
                 "name", "myconfigmap"),
         "data", Map.of(
                 "Key", "value",
                 "Another", "123454")));
 

At the minimum, when importing clusters for kubectl management, you will need to specify:

If the cluster is configured with private-only or private and restricted public Kubernetes endpoint access, you must also specify:

Known Issues and Limitations

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