aws

Cluster Autoscaler on AWS

On AWS, Cluster Autoscaler utilizes Amazon EC2 Auto Scaling Groups to manage node groups. Cluster Autoscaler typically runs as a Deployment in your cluster.

Requirements

Cluster Autoscaler requires Kubernetes v1.3.0 or greater.

Permissions

Cluster Autoscaler requires the ability to examine and modify EC2 Auto Scaling Groups. We recommend using IAM roles for Service Accounts to associate the Service Account that the Cluster Autoscaler Deployment runs as with an IAM role that is able to perform these functions. If you are unable to use IAM Roles for Service Accounts, you may associate an IAM service role with the EC2 instance on which the Cluster Autoscaler pod runs.

IAM Policy

There are a number of ways to run the autoscaler in AWS, which can significantly impact the range of IAM permissions required for the Cluster Autoscaler to function properly. Two options are provided below, one which will allow use of all of the features of the Cluster Autoscaler, the second with a more limited range of IAM actions enabled, which enforces using certain configuration options in the Cluster Autoscaler binary.

It is strongly recommended to restrict the target resources for the autoscaling actions by either specifying Auto Scaling Group ARNs in the Resource list of the policy or using tag based conditionals. The minimal policy includes an example of restricting by ASG ARN.

Full Cluster Autoscaler Features Policy (Recommended)

Permissions required when using ASG Autodiscovery and Dynamic EC2 List Generation (the default behaviour). In this example, only the second block of actions should be updated to restrict the resources/add conditionals:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "autoscaling:DescribeAutoScalingGroups",
        "autoscaling:DescribeAutoScalingInstances",
        "autoscaling:DescribeLaunchConfigurations",
        "autoscaling:DescribeScalingActivities",
        "autoscaling:DescribeTags",
        "ec2:DescribeImages",
        "ec2:DescribeInstanceTypes",
        "ec2:DescribeLaunchTemplateVersions",
        "ec2:GetInstanceTypesFromInstanceRequirements",
        "eks:DescribeNodegroup"
      ],
      "Resource": ["*"]
    },
    {
      "Effect": "Allow",
      "Action": [
        "autoscaling:SetDesiredCapacity",
        "autoscaling:TerminateInstanceInAutoScalingGroup"
      ],
      "Resource": ["*"]
    }
  ]
}

Minimal IAM Permissions Policy

NOTE: The below policies/arguments to the Cluster Autoscaler need to be modified as appropriate for the names of your ASGs, as well as account ID and AWS region before being used.

The following policy provides the minimum privileges necessary for Cluster Autoscaler to run. When using this policy, you cannot use autodiscovery of ASGs. In addition, it restricts the IAM permissions to the node groups the Cluster Autoscaler is configured to scale.

This in turn means that you must pass the following arguments to the Cluster Autoscaler binary, replacing min and max node counts and the ASG:

--aws-use-static-instance-list=false
--nodes=1:100:exampleASG1
--nodes=1:100:exampleASG2

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "autoscaling:DescribeAutoScalingGroups",
        "autoscaling:DescribeAutoScalingInstances",
        "autoscaling:DescribeLaunchConfigurations",
        "autoscaling:DescribeScalingActivities",
        "autoscaling:SetDesiredCapacity",
        "autoscaling:TerminateInstanceInAutoScalingGroup",
        "eks:DescribeNodegroup"
      ],
      "Resource": ["arn:aws:autoscaling:${YOUR_CLUSTER_AWS_REGION}:${YOUR_AWS_ACCOUNT_ID}:autoScalingGroup:*:autoScalingGroupName/${YOUR_ASG_NAME}"]
    }
  ]
}

The "eks:DescribeNodegroup" permission allows Cluster Autoscaler to pull labels and taints from the EKS DescribeNodegroup API for EKS managed nodegroups. (Note: When an EKS DescribeNodegroup API label and a tag on the underlying autoscaling group have the same key, the EKS DescribeNodegroup API label value will be saved by the Cluster Autoscaler over the autoscaling group tag value.) Currently the Cluster Autoscaler will only call the EKS DescribeNodegroup API when a managed nodegroup is created with 0 nodes and has never had any nodes added to it. Once nodes are added, even if the managed nodegroup is scaled back to 0 nodes, this functionality will not be called anymore. In the case of a Cluster Autoscaler restart, the Cluster Autoscaler will need to repopulate caches so it will call this functionality again if the managed nodegroup is at 0 nodes. Enabling this functionality any time there are 0 nodes in a managed nodegroup (even after a scale-up then scale-down) would require changes to the general shared Cluster Autoscaler code which could happen in the future.

NOTE: For private clusters, in order for the EKS DescribeNodegroup API to work, you need to create an interface endpoint for Amazon EKS (AWS PrivateLink), as described at the AWS Documentation.

Using OIDC Federated Authentication

OIDC federated authentication allows your service to assume an IAM role and interact with AWS services without having to store credentials as environment variables. For an example of how to use AWS IAM OIDC with the Cluster Autoscaler please see here.

Using AWS Credentials

NOTE The following is not recommended for Kubernetes clusters running on AWS. If you are using Amazon EKS, consider using IAM roles for Service Accounts instead.

For on-premise clusters, you may create an IAM user subject to the above policy and provide the IAM credentials as environment variables in the Cluster Autoscaler deployment manifest. Cluster Autoscaler will use these credentials to authenticate and authorize itself.

apiVersion: v1
kind: Secret
metadata:
  name: aws-secret
type: Opaque
data:
  aws_access_key_id: BASE64_OF_YOUR_AWS_ACCESS_KEY_ID
  aws_secret_access_key: BASE64_OF_YOUR_AWS_SECRET_ACCESS_KEY

Please refer to the relevant Kubernetes documentation for creating a secret manually.

env:
  - name: AWS_ACCESS_KEY_ID
    valueFrom:
      secretKeyRef:
        name: aws-secret
        key: aws_access_key_id
  - name: AWS_SECRET_ACCESS_KEY
    valueFrom:
      secretKeyRef:
        name: aws-secret
        key: aws_secret_access_key
  - name: AWS_REGION
    value: YOUR_AWS_REGION

Auto-Discovery Setup

Auto-Discovery Setup is the preferred method to configure Cluster Autoscaler.

To enable this, provide the --node-group-auto-discovery flag as an argument whose value is a list of tag keys that should be looked for. For example, --node-group-auto-discovery=asg:tag=k8s.io/cluster-autoscaler/enabled,k8s.io/cluster-autoscaler/<cluster-name> will find the ASGs that have at least all the given tags. Without the tags, the Cluster Autoscaler will be unable to add new instances to the ASG as it has not been discovered. In the example, a value is not given for the tags and in this case any value will be ignored and will be arbitrary - only the tag name matters. Optionally, the tag value can be set to be usable and custom tags can also be added. For example, --node-group-auto-discovery=asg:tag=k8s.io/cluster-autoscaler/enabled=foo,k8s.io/cluster-autoscaler/<cluster-name>=bar,my-custom-tag=custom-value. Now the ASG tags must have the correct values as well as the custom tag to be successfully discovered by the Cluster Autoscaler.

Example deployment:

kubectl apply -f examples/cluster-autoscaler-autodiscover.yaml

Cluster Autoscaler will respect the minimum and maximum values of each Auto Scaling Group. It will only adjust the desired value.

Each Auto Scaling Group should be composed of instance types that provide approximately equal capacity. For example, ASG "xlarge" could be composed of m5a.xlarge, m4.xlarge, m5.xlarge, and m5d.xlarge instance types, because each of those provide 4 vCPUs and 16GiB RAM. Separately, ASG "2xlarge" could be composed of m5a.2xlarge, m4.2xlarge, m5.2xlarge, and m5d.2xlarge instance types, because each of those provide 8 vCPUs and 32GiB RAM.

Cluster Autoscaler will attempt to determine the CPU, memory, and GPU resources provided by an Auto Scaling Group based on the instance type specified in its Launch Configuration or Launch Template. It will also examine any overrides provided in an ASG's Mixed Instances Policy. If any such overrides are found, only the first instance type found will be used. See Using Mixed Instances Policies and Spot Instances for details.

When scaling up from 0 nodes, the Cluster Autoscaler reads ASG tags to derive information about the specifications of the nodes i.e labels and taints in that ASG. Note that it does not actually apply these labels or taints - this is done by an AWS generated user data script. It gives the Cluster Autoscaler information about whether pending pods will be able to be scheduled should a new node be spun up for a particular ASG with the asumption the ASG tags accurately reflect the labels/taint actually applied.

The following is only required if scaling up from 0 nodes. The Cluster Autoscaler will require the label tag on the ASG should a deployment have a NodeSelector, else no scaling will occur as the Cluster Autoscaler does not realise the ASG has that particular label. The tag is of the format k8s.io/cluster-autoscaler/node-template/label/<label-name>: <label-value> is the name of the label and the value of each tag specifies the label value.

Example tags:

• k8s.io/cluster-autoscaler/node-template/label/foo: bar

The following is only required if scaling up from 0 nodes. The Cluster Autoscaler will require the taint tag on the ASG, else tainted nodes may get spun up that cannot actually have the pending pods run on it. The tag is of the format k8s.io/cluster-autoscaler/node-template/taint/<taint-name>:<taint-value:taint-effect> is the name of the taint and the value of each tag specifies the taint value and effect with the format <taint-value>:<taint-effect>.

Example tags:

• k8s.io/cluster-autoscaler/node-template/taint/dedicated: true:NoSchedule

From version 1.14, Cluster Autoscaler can also determine the resources provided by each Auto Scaling Group via tags. The tag is of the format k8s.io/cluster-autoscaler/node-template/resources/<resource-name>. <resource-name> is the name of the resource, such as ephemeral-storage. The value of each tag specifies the amount of resource provided. The units are identical to the units used in the resources field of a Pod specification.

Example tags:

• k8s.io/cluster-autoscaler/node-template/resources/ephemeral-storage: 100G

ASG labels can specify autoscaling options, overriding the global cluster-autoscaler settings for the labeled ASGs. Those labels takes the same values format as the cluster-autoscaler command line flags they override (a float or a duration, encoded as string). Currently supported autoscaling options (and example values) are:

• k8s.io/cluster-autoscaler/node-template/autoscaling-options/scaledownutilizationthreshold: 0.5 (overrides --scale-down-utilization-threshold value for that specific ASG)
• k8s.io/cluster-autoscaler/node-template/autoscaling-options/scaledowngpuutilizationthreshold: 0.5 (overrides --scale-down-gpu-utilization-threshold value for that specific ASG)
• k8s.io/cluster-autoscaler/node-template/autoscaling-options/scaledownunneededtime: 10m0s (overrides --scale-down-unneeded-time value for that specific ASG)
• k8s.io/cluster-autoscaler/node-template/autoscaling-options/scaledownunreadytime: 20m0s (overrides --scale-down-unready-time value for that specific ASG)
• k8s.io/cluster-autoscaler/node-template/autoscaling-options/ignoredaemonsetsutilization: true (overrides --ignore-daemonsets-utilization value for that specific ASG)

NOTE: It is your responsibility to ensure such labels and/or taints are applied via the node's kubelet configuration at startup. Cluster Autoscaler will not set the node taints for you.

Recommendations:

• It is recommended to use a second tag like k8s.io/cluster-autoscaler/<cluster-name> when k8s.io/cluster-autoscaler/enabled is used across many clusters to prevent ASGs from different clusters having conflicts. An ASG must contain at least all the tags specified and as such secondary tags can differentiate between different clusters ASGs.
• To prevent conflicts, do not provide a --nodes argument if --node-group-auto-discovery is specified.
• Be sure to add autoscaling:DescribeLaunchConfigurations or ec2:DescribeLaunchTemplateVersions to the Action list of the IAM Policy used by Cluster Autoscaler, depending on whether your ASG utilizes Launch Configurations or Launch Templates.
• If Cluster Autoscaler adds a node to the cluster, and the node has taints applied when it joins the cluster that Cluster Autoscaler was unaware of (because the tag wasn't supplied in ASG), this can lead to significant confusion and misbehaviour.

Special note on GPU instances

The device plugin on nodes that provides GPU resources can take some time to advertise the GPU resource to the cluster. This may cause Cluster Autoscaler to unnecessarily scale out multiple times.

To avoid this, you can configure kubelet on your GPU nodes to label the node before it joins the cluster by passing it the --node-labels flag. The label format is as follows:

• Cluster Autoscaler < 1.15: cloud.google.com/gke-accelerator=<gpu-type>
• Cluster Autoscaler >= 1.15: k8s.amazonaws.com/accelerator=<gpu-type>

<gpu-type> varies by instance type. On P2 instances, for example, the value is nvidia-tesla-k80.

Manual configuration

Cluster Autoscaler can also be configured manually if you wish by passing the --nodes argument at startup. The format of the argument is --nodes=<min>:<max>:<asg-name>, where <min> is the minimum number of nodes, <max> is the maximum number of nodes, and <asg-name> is the Auto Scaling Group name.

You can pass multiple --nodes arguments if you have multiple Auto Scaling Groups you want Cluster Autoscaler to use.

NOTES:

• Both <min> and <max> must be within the range of the minimum and maximum instance counts specified by the Auto Scaling group.
• When manual configuration is used, all Auto Scaling groups must use EC2 instance types that provide equal CPU and memory capacity.

Examples:

One ASG Setup (min: 1, max: 10, ASG Name: k8s-worker-asg-1)

kubectl apply -f examples/cluster-autoscaler-one-asg.yaml

Multiple ASG Setup

kubectl apply -f examples/cluster-autoscaler-multi-asg.yaml

Control Plane (previously referred to as master) Node Setup

NOTE: This setup is not compatible with Amazon EKS.

To run a CA pod on a control plane node the CA deployment should tolerate the master taint and nodeSelector should be used to schedule the pods on a control plane node. Please replace {{ node_asg_min }}, {{ node_asg_max }} and {{ name }} with your ASG setting in the yaml file.

kubectl apply -f examples/cluster-autoscaler-run-on-control-plane.yaml

Using Mixed Instances Policies and Spot Instances

NOTE: The minimum version of cluster autoscaler to support MixedInstancePolicy is v1.14.x.

If your workloads can tolerate interruption, consider taking advantage of Spot Instances for a lower price point. To enable diversity among On Demand and Spot Instances, as well as specify multiple EC2 instance types in order to tap into multiple Spot capacity pools, use a mixed instances policy on your ASG. Note that the instance types should have the same amount of RAM and number of CPU cores, since this is fundamental to CA's scaling calculations. Using mismatched instances types can produce unintended results. See an example below.

Additionally, there are other factors which affect scaling, such as node labels. If you are currently using nodeSelector with the beta.kubernetes.io/instance-type label, you will need to apply a common propagating label to the ASG and use that instead, since the instance-type label can no longer be relied upon. One may also use auto-generated tags such as aws:cloudformation:stack-name for this purpose. Node affinity and anti-affinity are not affected in the same way, since these selectors natively accept multiple values; one must add all the configured instances types to the list of values, for example:

spec:
  affinity:
    nodeAffinity:
      requiredDuringSchedulingIgnoredDuringExecution:
        nodeSelectorTerms:
          - matchExpressions:
              - key: beta.kubernetes.io/instance-type
                operator: In
                values:
                  - r5.2xlarge
                  - r5d.2xlarge
                  - r5a.2xlarge
                  - r5ad.2xlarge
                  - r5n.2xlarge
                  - r5dn.2xlarge
                  - r4.2xlarge
                  - i3.2xlarge

Similarly, if using the balancing-label flag, you should only choose labels which have the same value for all nodes in the node group. Otherwise you may get unexpected results, as the flag values will vary based on the nodes created by the ASG.

Example usage:

• Create a Launch Template (LT) with an instance type, for example, r5.2xlarge. Consider this the 'base' instance type. Do not define any spot purchase options here.
• Create an ASG with a MixedInstancesPolicy that refers to the newly-created LT.
• Set LaunchTemplateOverrides to include the 'base' instance type r5.2xlarge and suitable alternatives, e.g. r5d.2xlarge, i3.2xlarge, r5a.2xlarge and r5ad.2xlarge. Differing processor types and speeds should be evaluated depending on your use-case(s).
• Set InstancesDistribution according to your needs.
• See Allocation Strategies for information about how the ASG fulfils capacity from the specified instance types. It is recommended to use the capacity-optimized allocation strategy, which will automatically launch Spot Instances into the most available pools by looking at real-time capacity data and.
• For the same workload or for the generic capacity in your cluster, you can also create more node groups with a vCPU/Mem ratio that is a good fit for your workloads, but from different instance sizes. For example: Node group 1: m5.xlarge, m5a.xlarge, m5d.xlarge, m5ad.xlarge, m4.xlarge. Node group 2: m5.2xlarge, m5a.2xlarge, m5d.2xlarge, m5ad.2xlarge, m4.2xlarge. This approach increases the chance of achieving your desired scale at the lowest cost by tapping into many Spot capacity pools.

See CloudFormation example here.

Use Static Instance List

The set of the latest supported EC2 instance types will be fetched by the CA at run time. You can find all the available instance types in the CA logs. If your network access is restricted such that fetching this set is infeasible, you can specify the command-line flag --aws-use-static-instance-list=true to switch the CA back to its original use of a statically defined set.

To refresh static list, please run go run ec2_instance_types/gen.go under cluster-autoscaler/cloudprovider/aws/ and update staticListLastUpdateTime in aws_util.go

Using the AWS SDK vendored in the AWS cloudprovider

If you want to use a newer version of the AWS SDK than the version currently vendored as a direct dependency by Cluster Autoscaler, then you can use the version vendored under this AWS cloudprovider.

The current version vendored is v1.48.7.

If you want to update the vendored AWS SDK to a newer version, please make sure of the following:

1. Place the copy of the new desired version of the AWS SDK under the aws-sdk-go directory.
2. Remove folders : models and examples. Remove _test.go file find . -name '*_test.go' -exec rm {}+
3. Update the import statements within the newly-copied AWS SDK to reference the new paths (e.g., github.com/aws/aws-sdk-go/aws/awsutil -> k8s.io/autoscaler/cluster-autoscaler/cloudprovider/aws/aws-sdk-go/aws/awsutil). You can use this command from the aws-sdk-go folder find . -type f -exec sed -i ‘s#github.com/aws/aws-sdk-go#k8s.io/autoscaler/cluster-autoscaler/cloudprovider/aws/aws-sdk-go#’ {} \;
4. Update the version number above to indicate the new vendored version.

Using cloud config with helm

If you want to use custom AWS cloud config e.g. endpoint urls

1. Create ConfigMap with cloud config file definition (see example):

   kubectl apply -f examples/configmap-cloudconfig-example.yaml
   

2. Add the following in your values.yaml:

   cloudConfigPath: config/cloud.conf
   
   extraVolumes:
     - name: cloud-config
       configMap:
         name: cloud-config
   
   extraVolumeMounts:
     - name: cloud-config
       mountPath: config
   

3. Install (or upgrade) helm chart with updated values (see example)

Please note: it is also possible to mount the cloud config file from host:

    extraVolumes:
      - name: cloud-config
        hostPath:
          path: /path/to/file/on/host

    extraVolumeMounts:
      - name: cloud-config
        mountPath: config/cloud.conf
        readOnly: true

Common Notes and Gotchas:

• The /etc/ssl/certs/ca-bundle.crt should exist by default on ec2 instance in your EKS cluster. If you use other cluster provision tools like kops with different operating systems other than Amazon Linux 2, please use /etc/ssl/certs/ca-certificates.crt or correct path on your host instead for the volume hostPath in your cluster autoscaler manifest.
• If you’re using Persistent Volumes, your deployment needs to run in the same AZ as where the EBS volume is, otherwise the pod scheduling could fail if it is scheduled in a different AZ and cannot find the EBS volume. To overcome this, either use a single AZ ASG for this use case, or an ASG-per-AZ while enabling --balance-similar-node-groups. Alternately, and depending on your use-case, you might be able to switch from using EBS to using shared storage that is available across AZs (for each pod in its respective AZ). Consider AWS services like Amazon EFS or Amazon FSx for Lustre.
• On creation time, the ASG will have the AZRebalance process enabled, which means it will actively work to balance the number of instances between AZs, and possibly terminate instances. If your applications could be impacted from sudden termination, you can either suspend the AZRebalance feature, or use a tool for automatic draining upon ASG scale-in such as the AWS Node Termination Handler.
• By default, cluster autoscaler will not terminate nodes running pods in the kube-system namespace. You can override this default behaviour by passing in the --skip-nodes-with-system-pods=false flag.
• By default, cluster autoscaler will wait 10 minutes between scale down operations, you can adjust this using the --scale-down-delay-after-add, --scale-down-delay-after-delete, and --scale-down-delay-after-failure flag. E.g. --scale-down-delay-after-add=5m to decrease the scale down delay to 5 minutes after a node has been added.
• If you're running multiple ASGs, the --expander flag supports five options: random, most-pods, least-waste, priority, and grpc. random will expand a random ASG on scale up. most-pods will scale up the ASG that will schedule the most amount of pods. least-waste will expand the ASG that will waste the least amount of CPU/MEM resources. In the event of a tie, cluster autoscaler will fall back torandom. The priority expander lets you define a custom priority ranking in a ConfigMap for selecting ASGs, and the grpc expander allows you to write your own expansion logic.
• If you're managing your own kubelets, they need to be started with the --provider-id flag. The provider id has the format aws:///<availability-zone>/<instance-id>, e.g. aws:///us-east-1a/i-01234abcdef.
• If you want to use regional STS endpoints (e.g. when using VPC endpoint for STS) the env AWS_STS_REGIONAL_ENDPOINTS=regional should be set.
• If you want to run it on instances with IMDSv1 disabled make sure your EC2 launch configuration has the setting Metadata response hop limit set to 2. Otherwise, the /latest/api/token call will timeout and result in an error. See AWS docs here for further information.
• If you don't use EKS managed nodegroups, don't add the eks:nodegroup-name tag to the ASG as this will lead to extra EKS API calls that could slow down scaling when there are 0 nodes in the nodegroup.
• Set AWS_MAX_ATTEMPTS to configure max retries
• If you are running a private cluster in a VPC without certain VPC interfaces for AWS services, the CA might crash on startup due to failing to dynamically fetch supported EC2-instance types. To avoid this, add the argument --aws-use-static-instance-list=true to the CA startup command. For more information on private cluster requirements, see AWS docs here.