Karpenter is an open-source tool for automating node provisioning in Kubernetes. Karpenter aims to enhance both the effectiveness and affordability of managing workloads within a Kubernetes cluster. The core mechanics of Karpenter involve:
- Monitoring unschedulable pods identified by the Kubernetes scheduler.
- Scrutinizing the scheduling constraints, including resource requests, node selectors, affinities, tolerations, and topology spread constraints, as stipulated by the pods.
- Provisioning nodes that precisely align with the pods' requirements.
- Streamlining cluster resource usage by removing nodes once their services are no longer required.
Why we moved to Karpenter?
We at NimbleWork used AWS Fargate in the past for running on-demand, short-lived or one-off workloads, one of the examples being running Jenkins slaves in AWS Fargate while the Master runs on worker nodes. Fargate is good in the sense that it takes care of managing node infrastructure, but can cost premium if you're using it for long running workloads. It is for this reason that EKS deployment with Worker Nodes is the more preferred path. But with that comes a new problem, unlike Fargate, we have to not just manage creating nodes and node groups, we also have to ensure that our EC2 nodes utilisation is optimal. It comes back to hurt us specially when we realise there's an entire VM running on just 10% of the CPU/Mem capacity because it has two active pods, which we could have moved to another node and claimed this one. In the past we've relied on a cocktail of Prometheus Alerts and Fluent-Bit monitoring data to conclude we can reschedule pods and clean-up un-used nodes. But any self-respecting Engineering Manager would tell you they'd jump to a better alternative than this as soon as they find one. For us Karpenter came as that alternative.
How it works?
Karpenter allows you to define Provisioners which are the heart of it's cluster management capability. When initially installing Karpenter, you establish a default Provisioner, which imparts specific constraints on the nodes created by Karpenter and the pods eligible to run on these nodes. These constraints encompass defining taints to restrict pod deployment on Karpenter-created nodes, establishing startup taints to indicate temporary node tainting, narrowing down node creation to preferred zones, instance types, and computer architectures, and configuring default settings for node expiration. The Provisioner, in essence, empowers you with fine-grained control over resource allocation within your Kubernetes cluster. You can read up more on Provisioners here.
Deploying EKS Cluster
Here's how to deploy the EKS cluster with Karpenter.
Setting Up the VPC
Before we begin, let's deploy the AWS VPC to run our EKS cluster. we'll be using terraform for provisioning on the AWS Cloud.
module "vpc" {
source = "terraform-aws-modules/vpc/aws"
version = "3.19.0"
name = "mycluster-vpc"
cidr = var.vpc_cidr
azs = ["us-east-1a", "us-east-1b", "us-east-1c"]
private_subnets = var.private_subnets_cidr
public_subnets = var.public_subnets_cidr
enable_nat_gateway = true
single_nat_gateway = true
enable_dns_hostnames = true
public_subnet_tags = {
"kubernetes.io/cluster/mycluster" = "shared"
"kubernetes.io/role/elb" = "1"
}
private_subnet_tags = {
"kubernetes.io/cluster/mycluster = "shared"
"kubernetes.io/role/internal-elb" = "1"
"karpenter.sh/discovery" = "mycluster"
}
tags = {
"kubernetes.io/cluster/mycluster" = "shared"
}
}
module "vpc-security-group" {
source = "terraform-aws-modules/security-group/aws"
version = "4.17.1"
create = true
name = "mycluster-security-group"
description = "Security group for VPC"
vpc_id = module.vpc.vpc_id
ingress_with_cidr_blocks = var.ingress_rules
ingress_with_self = [
{
from_port = 0
to_port = 0
protocol = -1
description = "Ingress with Self"
}
]
egress_with_cidr_blocks = [{
cidr_blocks = "0.0.0.0/0"
from_port = 0
to_port = 0
protocol = -1
}]
tags = {
Name = "mycluster-security-group"
"karpenter.sh/discovery" = "mycluster"
}
}
We're using the community contributed modules here for spinning up a VPC which has public and private subnets, and ingress rules. For those interested in more details here a simple example of what could potentially go in the ingress rules
variable "ingress_rules" {
type = list(map(string))
description = "VPC Default Security Group Ingress Rules"
default = [
{
cidr_blocks = "0.0.0.0/0"
from_port = 443
to_port = 443
protocol = "tcp"
description = "Karpenter ingress allow"
},
{ #other CIDR blocks to which you might want to restrict access to (for example if this was your dev cluster)
cidr_blocks = "XX.XX.XX.XXX/XX"
from_port = 0
to_port = 0
protocol = -1
description = "MyCLuster-NAT"
}
]
}
The "karpenter.sh/discovery" = "mycluster" tag in the vpc module and the in the security group tags is our hint to AWS about using aws-karpenter for autoscaling nodes and pods in this cluster. You can get the VPC up and running via the
terraform plan
terraform apply
commands, it's a good practice to define key values that you will need in other modules as outputs to this module run, also, we save the state in a S3 bucket as our TF builds run from a Jenkins Salve on Fargate with ephemeral storage. You'd see the following values in the console output of the terraform apply command if you've included publishing the VPC and security group IDs in the outputs.tf of your vpc module.
security_group_id = "sg-dkfjksdhf83983c883"
vpc_id = "vpc-2l4jc2lj4l2cbj42"
With this we have our VPC ready, let's deploy the EKS cluster with Node Groups and Karpenter.
Deploying EKS Cluster with Node Group Workers and Karpenter
Add the following code to you terraform module to include EKS
module "eks-cluster" {
source = "terraform-aws-modules/eks/aws"
version = "19.12.0"
cluster_name = "mycluster"
cluster_version = 1.26
subnet_ids = [ "subnet-XX","subnet-YY","subnet-ZZ"]
create_cloudwatch_log_group = false
tags = {
Name = "mycluster"
"karpenter.sh/discovery" = "mycluster"
}
vpc_id = "vpc-2l4jc2lj4l2cbj42"
cluster_endpoint_public_access_cidrs = ["XX.XX.XX.XXX/YY"] #important if the cluster_endpoint_public_access is set to true
cluster_endpoint_private_access = true
cluster_endpoint_public_access = true
cluster_security_group_id = "sg-dkfjksdhf83983c883"
}
module "mycluster-workernodes" {
source = "terraform-aws-modules/eks/aws//modules/eks-managed-node-group"
version = "19.12.0"
name = "${var.eks_cluster_name}-services"
cluster_name = module.eks-cluster.cluster_name
cluster_version = module.eks-cluster.cluster_version
create_iam_role = false
iam_role_arn = aws_iam_role.nodegroup_role.arn
subnet_ids = flatten([data.terraform_remote_state.db.outputs.private_subnets])
cluster_primary_security_group_id = "sg-dkfjksdhf83983c883"
vpc_security_group_ids = [module.eks-cluster.cluster_security_group_id]
min_size = 1
max_size = 5
desired_size = 2
instance_types = ["t3.large"]
capacity_type = "ON_DEMAND"
labels = {
NodeGroups = "mycluster-workernodes"
}
tags = {
Name = "mycluster-workernodes"
"karpenter.sh/discovery" = module.eks-cluster.cluster_name
}
}
It's the same "karpenter.sh/discovery" tag at play here too, and that's it! You have an eks cluster with Karpenter managed provisioning ready!
Configuring Karpenter Provisioners
Now that we have a cluster ready let's have a look at using Karpenter to manage the Pods. We'll define provisioners for different purposes and then associate pods to each of them.
Provisioner for Nodes running Spot Instances
This is good alternative to Fargate, specially for running the one-off workloads which do not live beyond the job completion. Here's an example of a Karpenter provisioner using spot instances.
# spot default
apiVersion: karpenter.sh/v1alpha5
kind: Provisioner
metadata:
name: default
spec:
requirements:
- key: karpenter.sh/capacity-type
operator: In
values: ["spot"]
- key: "karpenter.k8s.aws/instance-category"
operator: In
values: ["c", "m", "r"]
- key: "karpenter.k8s.aws/instance-cpu"
operator: In
values: ["4", "8", "16", "32"]
limits:
resources:
cpu: 1000
providerRef:
name: default
consolidation:
enabled: true
---
apiVersion: karpenter.k8s.aws/v1alpha1
kind: AWSNodeTemplate
metadata:
name: default
spec:
subnetSelector:
karpenter.sh/discovery: mycluster
securityGroupSelector:
karpenter.sh/discovery: mycluster
---
To use this provisioner add the following tag to the nodeSelector in kube deployment.
nodeSelector:
karpenter.sh/provisioner-name: default
This will provision the pods to run on spot instances.
Provisioner for Nodes running On-Demand Instances
Here's a sample of how to use on-demand node for worker nodes, and schedule pods on it. The following file defines a provisioner for on-demand instances
# on-demand
apiVersion: karpenter.sh/v1alpha5
kind: Provisioner
metadata:
name: on-demand
spec:
# taints:
# - key: "name"
# value: "on-demand"
# effect: "NoSchedule"
requirements:
- key: karpenter.sh/capacity-type
operator: In
values: ["on-demand"]
- key: "karpenter.k8s.aws/instance-category"
operator: In
values: ["c", "m", "r"]
- key: "karpenter.k8s.aws/instance-cpu"
operator: In
values: ["2","4","8", "16", "32"]
- key: "topology.kubernetes.io/zone"
operator: NotIn
values: ["us-east-1b"]
limits:
resources:
cpu: 1000
providerRef:
name: on-demand
# consolidation:
# enabled: true
ttlSecondsAfterEmpty: 30
---
apiVersion: karpenter.k8s.aws/v1alpha1
kind: AWSNodeTemplate
metadata:
name: on-demand
spec:
subnetSelector:
karpenter.sh/discovery: mycluster
securityGroupSelector:
karpenter.sh/discovery: mycluster
---
Once again we can utilise the nodeSelector in kube deployment yaml to provision pods on these nodes
nodeSelector:
karpenter.sh/provisioner-name: on-demand
Conclusion
This is a simplified example of how to get started with Karpenter on AWS EKS. production grade deployments require more nuanced provisioner definitions including but not limited to resource limits, eviction policies as well.
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