Kubernetes AWS Cluster Autoscaler
THIS PROJECT IS NO LONGER MAINTAINED, PLEASE USE THE OFFICIAL CLUSTER AUTOSCALER INSTEAD
Simple cluster autoscaler for AWS Auto Scaling Groups which sets the
DesiredCapacity of one or more ASGs to the calculated number of nodes.
- 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
DesiredCapacityis 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
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?
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
The main loop keeps no state (like history), all input for the
autoscale function comes from either static configuration or the Kubernetes API server.
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
DesiredCapacityfor each ASG to the calculated number of required nodes
The whole process relies on having properly configured resource requests for all pods.
Create the necessary IAM role (to be used by
kube2iam if you have it deployed):
deploy/cloudformation.yamland change the AWS account ID and the worker node's role name as necessary.
- Create the Cloud Formation stack from
Deploy the autoscaler to your running cluster:
$ kubectl apply -f deploy/deployment.yaml
See below for optional configuration parameters.
The following command line options are supported:
- Extra CPU requests % to add to calculation, defaults to 10%.
- Extra memory requests % to add to calculation, defaults to 10%.
- Extra pods requests % to add to calculation, defaults to 10%.
- Extra CPU requests to add to calculation, defaults to 200m.
- Extra memory requests to add to calculation, defaults to 200Mi.
- Extra number of pods to overprovision for, defaults to 10.
- Number of extra "spare" nodes to provision per ASG/AZ, defaults to 1.
- Do not ignore auto scaling group with master nodes.
- Time to sleep between runs in seconds, defaults to 60 seconds.
- Only run once and exit (useful for debugging).
- Scale down step in terms of node count, defaults to 1.
- Scale down step in terms of node percentage (1.0 is 100%), defaults to 0%