Simple, elastic Kubernetes cluster autoscaler for AWS Auto Scaling Groups
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README.rst

Kubernetes AWS Cluster Autoscaler

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Simple cluster autoscaler for AWS Auto Scaling Groups which sets the DesiredCapacity of one or more ASGs to the calculated number of nodes.

Goals:

  • support multiple Auto Scaling Groups
  • support resource buffer (overprovision fixed or percentage amount)
  • respect Availability Zones, i.e. make sure that all AZs provide enough capacity
  • be deterministic and predictable, i.e. the DesiredCapacity is only calculated based on the current cluster state
  • scale down slowly to mitigate service disruptions, i.e. at most one node at a time
  • support "elastic" workloads like daily up/down scaling
  • support AWS Spot Fleet (not yet implemented)
  • require a minimum amount of configuration (preferably none)
  • keep it simple

This autoscaler was initially created as a proof of concept and born out of frustration with the "official" cluster-autoscaler:

  • it only scales up when "it's too late" (pods are unschedulable)
  • it does not honor Availability Zones
  • it does not support multiple Auto Scaling Groups
  • it requires unnecessary configuration
  • the code is quite complex

Disclaimer

Use at your own risk! This autoscaler was only tested with Kubernetes versions 1.5.2 to 1.7.7. There is no guarantee that it works in previous Kubernetes versions.

Is it production ready? Yes, the kube-aws-autoscaler is running in production at Zalando for months, see https://github.com/zalando-incubator/kubernetes-on-aws for more information and deployment configuration.

How it works

The autoscaler consists of a simple main loop which calls the autoscale function every 60 seconds (configurable via the --interval option). The main loop keeps no state (like history), all input for the autoscale function comes from either static configuration or the Kubernetes API server. The autoscale function performs the following task:

  • retrieve the list of all (worker) nodes from the Kubernetes API and group them by Auto Scaling Group (ASG) and Availability Zone (AZ)
  • retrieve the list of all pods from the Kubernetes API
  • calculate the current resource "usage" for every ASG and AZ by summing up all pod resource requests (CPU, memory and number of pods)
  • calculates the currently required number of nodes per AWS Auto Scaling Group:
    • iterate through every ASG/AZ combination
    • use the calculated resource usage (sum of resource requests) and add the resource requests of any unassigned pods (pods not scheduled on any node yet)
    • apply the configured buffer values (10% extra for CPU and memory by default)
    • find the allocatable capacity of the weakest node
    • calculate the number of required nodes by adding up the capacity of the weakest node until the sum is greater than or equal to requested+buffer for both CPU and memory
    • sum up the number of required nodes from all AZ for the ASG
  • adjust the number of required nodes if it would scale down more than one node at a time
  • set the DesiredCapacity for each ASG to the calculated number of required nodes

The whole process relies on having properly configured resource requests for all pods.

Usage

Create the necessary IAM role (to be used by kube2iam if you have it deployed):

  • Modify deploy/cloudformation.yaml and change the AWS account ID and the worker node's role name as necessary.
  • Create the Cloud Formation stack from deploy/cloudformation.yaml.

Deploy the autoscaler to your running cluster:

$ kubectl apply -f deploy/deployment.yaml

See below for optional configuration parameters.

Configuration

The following command line options are supported:

--buffer-cpu-percentage
Extra CPU requests % to add to calculation, defaults to 10%.
--buffer-memory-percentage
Extra memory requests % to add to calculation, defaults to 10%.
--buffer-pods-percentage
Extra pods requests % to add to calculation, defaults to 10%.
--buffer-cpu-fixed
Extra CPU requests to add to calculation, defaults to 200m.
--buffer-memory-fixed
Extra memory requests to add to calculation, defaults to 200Mi.
--buffer-pods-fixed
Extra number of pods to overprovision for, defaults to 10.
--buffer-spare-nodes
Number of extra "spare" nodes to provision per ASG/AZ, defaults to 1.
--include-master-nodes
Do not ignore auto scaling group with master nodes.
--interval
Time to sleep between runs in seconds, defaults to 60 seconds.
--once
Only run once and exit (useful for debugging).
--scale-down-step-fixed
Scale down step in terms of node count, defaults to 1.
--scale-down-step-percentage
Scale down step in terms of node percentage (1.0 is 100%), defaults to 0%