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cloudprovider Caches should be updated after async PUT succeeds Apr 6, 2020
clusterstate Fix passing convention for metav1.DeleteOptions Mar 10, 2020
config Add support for passing in custom ignore labels Mar 17, 2020
context Add ClusterSnapshot to AutoscalingContext Feb 4, 2020
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vendor Properly propagate scale-up failures in scale sets. Mar 24, 2020
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OWNERS Remove piosz and add vivekbagade to cluster-autoscaler OWNERS Jan 3, 2020 Add DigitalOcean as supported cloudprovider Jan 22, 2020
cloudbuild.yaml Add GCB config for cluster-autoscaler Feb 16, 2018 Bug with with globbing Apr 8, 2019
go.mod Properly propagate scale-up failures in scale sets. Mar 24, 2020
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go.sum Properly propagate scale-up failures in scale sets. Mar 24, 2020
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Cluster Autoscaler


Cluster Autoscaler is a tool that automatically adjusts the size of the Kubernetes cluster when one of the following conditions is true:

  • there are pods that failed to run in the cluster due to insufficient resources,
  • there are nodes in the cluster that have been underutilized for an extended period of time and their pods can be placed on other existing nodes.


An FAQ is available HERE.

You should also take a look at the notes and "gotchas" for your specific cloud provider:


We recommend using Cluster Autoscaler with the Kubernetes master version for which it was meant. The below combinations have been tested on GCP. We don't do cross version testing or compatibility testing in other environments. Some user reports indicate successful use of a newer version of Cluster Autoscaler with older clusters, however, there is always a chance that it won't work as expected.

Starting from Kubernetes 1.12, versioning scheme was changed to match Kubernetes minor releases exactly.

Kubernetes Version CA Version
1.16.X 1.16.X
1.15.X 1.15.X
1.14.X 1.14.X
1.13.X 1.13.X
1.12.X 1.12.X
1.11.X 1.3.X
1.10.X 1.2.X
1.9.X 1.1.X
1.8.X 1.0.X
1.7.X 0.6.X
1.6.X 0.5.X, 0.6.X*
1.5.X 0.4.X
1.4.X 0.3.X

*Cluster Autoscaler 0.5.X is the official version shipped with k8s 1.6. We've done some basic tests using k8s 1.6 / CA 0.6 and we're not aware of any problems with this setup. However, Cluster Autoscaler internally simulates Kubernetes' scheduler and using different versions of scheduler code can lead to subtle issues.

Notable changes

For CA 1.1.2 and later, please check release notes.

CA version 1.1.1:

  • Fixes around metrics in the multi-master configuration.
  • Fixes for unready nodes issues when quota is overrun.

CA version 1.1.0:

CA version 1.0.3:

  • Adds support for safe-to-evict annotation on pod. Pods with this annotation can be evicted even if they don't meet other requirements for it.
  • Fixes an issue when too many nodes with GPUs could be added during scale-up (

CA Version 1.0.2:

CA Version 1.0.1:

CA Version 1.0:

With this release we graduated Cluster Autoscaler to GA.

  • Support for 1000 nodes running 30 pods each. See: Scalability testing report
  • Support for 10 min graceful termination.
  • Improved eventing and monitoring.
  • Node allocatable support.
  • Removed Azure support. See: PR removing support with reasoning behind this decision
  • annotation for marking nodes that should not be scaled down.
  • scale-down-delay-after-delete and scale-down-delay-after-failure flags replaced scale-down-trial-interval

CA Version 0.6:

CA Version 0.5.4:

  • Fixes problems with node drain when pods are ignoring SIGTERM.

CA Version 0.5.3:

CA Version 0.5.2:

CA Version 0.5.1:

CA Version 0.5:

  • CA continues to operate even if some nodes are unready and is able to scale-down them.
  • CA exports its status to kube-system/cluster-autoscaler-status config map.
  • CA respects PodDisruptionBudgets.
  • Azure support.
  • Alpha support for dynamic config changes.
  • Multiple expanders to decide which node group to scale up.

CA Version 0.4:

  • Bulk empty node deletions.
  • Better scale-up estimator based on binpacking.
  • Improved logging.

CA Version 0.3:

  • AWS support.
  • Performance improvements around scale down.


Cluster Autoscaler is designed to run on Kubernetes master node. This is the default deployment strategy on GCP. It is possible to run a customized deployment of Cluster Autoscaler on worker nodes, but extra care needs to be taken to ensure that Cluster Autoscaler remains up and running. Users can put it into kube-system namespace (Cluster Autoscaler doesn't scale down node with non-mirrored kube-system pods running on them) and set a priorityClassName: system-cluster-critical property on your pod spec (to prevent your pod from being evicted).

Supported cloud providers:

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