Concepts

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Taints and Tolerations

Node affinity, described here, is a property of pods that attracts them to a set of nodes (either as a preference or a hard requirement). Taints are the opposite – they allow a node to repel a set of pods.

Taints and tolerations work together to ensure that pods are not scheduled onto inappropriate nodes. One or more taints are applied to a node; this marks that the node should not accept any pods that do not tolerate the taints. Tolerations are applied to pods, and allow (but do not require) the pods to schedule onto nodes with matching taints.

Concepts

You add a taint to a node using kubectl taint. For example,

kubectl taint nodes node1 key=value:NoSchedule

places a taint on node node1. The taint has key key, value value, and taint effect NoSchedule. This means that no pod will be able to schedule onto node1 unless it has a matching toleration.

To remove the taint added by the command above, you can run:

kubectl taint nodes node1 key:NoSchedule-

You specify a toleration for a pod in the PodSpec. Both of the following tolerations “match” the taint created by the kubectl taint line above, and thus a pod with either toleration would be able to schedule onto node1:

tolerations:
- key: "key"
  operator: "Equal"
  value: "value"
  effect: "NoSchedule"
tolerations:
- key: "key"
  operator: "Exists"
  effect: "NoSchedule"

Here’s an example of a pod that uses tolerations:

pods/pod-with-toleration.yaml
apiVersion: v1
kind: Pod
metadata:
  name: nginx
  labels:
    env: test
spec:
  containers:
  - name: nginx
    image: nginx
    imagePullPolicy: IfNotPresent
  tolerations:
  - key: "example-key"
    operator: "Exists"
    effect: "NoSchedule"

A toleration “matches” a taint if the keys are the same and the effects are the same, and:

  • the operator is Exists (in which case no value should be specified), or
  • the operator is Equal and the values are equal

Operator defaults to Equal if not specified.

Note:

There are two special cases:

  • An empty key with operator Exists matches all keys, values and effects which means this will tolerate everything.

    tolerations:
    - operator: "Exists"
  • An empty effect matches all effects with key key.

    tolerations:
    - key: "key"
      operator: "Exists"

The above example used effect of NoSchedule. Alternatively, you can use effect of PreferNoSchedule. This is a “preference” or “soft” version of NoSchedule – the system will try to avoid placing a pod that does not tolerate the taint on the node, but it is not required. The third kind of effect is NoExecute, described later.

You can put multiple taints on the same node and multiple tolerations on the same pod. The way Kubernetes processes multiple taints and tolerations is like a filter: start with all of a node’s taints, then ignore the ones for which the pod has a matching toleration; the remaining un-ignored taints have the indicated effects on the pod. In particular,

  • if there is at least one un-ignored taint with effect NoSchedule then Kubernetes will not schedule the pod onto that node
  • if there is no un-ignored taint with effect NoSchedule but there is at least one un-ignored taint with effect PreferNoSchedule then Kubernetes will try to not schedule the pod onto the node
  • if there is at least one un-ignored taint with effect NoExecute then the pod will be evicted from the node (if it is already running on the node), and will not be scheduled onto the node (if it is not yet running on the node).

For example, imagine you taint a node like this

kubectl taint nodes node1 key1=value1:NoSchedule
kubectl taint nodes node1 key1=value1:NoExecute
kubectl taint nodes node1 key2=value2:NoSchedule

And a pod has two tolerations:

tolerations:
- key: "key1"
  operator: "Equal"
  value: "value1"
  effect: "NoSchedule"
- key: "key1"
  operator: "Equal"
  value: "value1"
  effect: "NoExecute"

In this case, the pod will not be able to schedule onto the node, because there is no toleration matching the third taint. But it will be able to continue running if it is already running on the node when the taint is added, because the third taint is the only one of the three that is not tolerated by the pod.

Normally, if a taint with effect NoExecute is added to a node, then any pods that do not tolerate the taint will be evicted immediately, and pods that do tolerate the taint will never be evicted. However, a toleration with NoExecute effect can specify an optional tolerationSeconds field that dictates how long the pod will stay bound to the node after the taint is added. For example,

tolerations:
- key: "key1"
  operator: "Equal"
  value: "value1"
  effect: "NoExecute"
  tolerationSeconds: 3600

means that if this pod is running and a matching taint is added to the node, then the pod will stay bound to the node for 3600 seconds, and then be evicted. If the taint is removed before that time, the pod will not be evicted.

Example Use Cases

Taints and tolerations are a flexible way to steer pods away from nodes or evict pods that shouldn’t be running. A few of the use cases are

  • Dedicated Nodes: If you want to dedicate a set of nodes for exclusive use by a particular set of users, you can add a taint to those nodes (say, kubectl taint nodes nodename dedicated=groupName:NoSchedule) and then add a corresponding toleration to their pods (this would be done most easily by writing a custom admission controller). The pods with the tolerations will then be allowed to use the tainted (dedicated) nodes as well as any other nodes in the cluster. If you want to dedicate the nodes to them and ensure they only use the dedicated nodes, then you should additionally add a label similar to the taint to the same set of nodes (e.g. dedicated=groupName), and the admission controller should additionally add a node affinity to require that the pods can only schedule onto nodes labeled with dedicated=groupName.

  • Nodes with Special Hardware: In a cluster where a small subset of nodes have specialized hardware (for example GPUs), it is desirable to keep pods that don’t need the specialized hardware off of those nodes, thus leaving room for later-arriving pods that do need the specialized hardware. This can be done by tainting the nodes that have the specialized hardware (e.g. kubectl taint nodes nodename special=true:NoSchedule or kubectl taint nodes nodename special=true:PreferNoSchedule) and adding a corresponding toleration to pods that use the special hardware. As in the dedicated nodes use case, it is probably easiest to apply the tolerations using a custom admission controller. For example, it is recommended to use Extended Resources to represent the special hardware, taint your special hardware nodes with the extended resource name and run the ExtendedResourceToleration admission controller. Now, because the nodes are tainted, no pods without the toleration will schedule on them. But when you submit a pod that requests the extended resource, the ExtendedResourceToleration admission controller will automatically add the correct toleration to the pod and that pod will schedule on the special hardware nodes. This will make sure that these special hardware nodes are dedicated for pods requesting such hardware and you don’t have to manually add tolerations to your pods.

  • Taint based Evictions: A per-pod-configurable eviction behavior when there are node problems, which is described in the next section.

Taint based Evictions

FEATURE STATE: Kubernetes 1.18 stable
This feature is stable, meaning:

  • The version name is vX where X is an integer.
  • Stable versions of features will appear in released software for many subsequent versions.

Earlier we mentioned the NoExecute taint effect, which affects pods that are already running on the node as follows

  • pods that do not tolerate the taint are evicted immediately
  • pods that tolerate the taint without specifying tolerationSeconds in their toleration specification remain bound forever
  • pods that tolerate the taint with a specified tolerationSeconds remain bound for the specified amount of time

In addition, Kubernetes 1.6 introduced alpha support for representing node problems. In other words, the node controller automatically taints a node when certain condition is true. The following taints are built in:

  • node.kubernetes.io/not-ready: Node is not ready. This corresponds to the NodeCondition Ready being “False”.
  • node.kubernetes.io/unreachable: Node is unreachable from the node controller. This corresponds to the NodeCondition Ready being “Unknown”.
  • node.kubernetes.io/out-of-disk: Node becomes out of disk.
  • node.kubernetes.io/memory-pressure: Node has memory pressure.
  • node.kubernetes.io/disk-pressure: Node has disk pressure.
  • node.kubernetes.io/network-unavailable: Node’s network is unavailable.
  • node.kubernetes.io/unschedulable: Node is unschedulable.
  • node.cloudprovider.kubernetes.io/uninitialized: When the kubelet is started with “external” cloud provider, this taint is set on a node to mark it as unusable. After a controller from the cloud-controller-manager initializes this node, the kubelet removes this taint.

In case a node is to be evicted, the node controller or the kubelet adds relevant taints with NoExecute effect. If the fault condition returns to normal the kubelet or node controller can remove the relevant taint(s).

Note: To maintain the existing rate limiting behavior of pod evictions due to node problems, the system actually adds the taints in a rate-limited way. This prevents massive pod evictions in scenarios such as the master becoming partitioned from the nodes.

The feature, in combination with tolerationSeconds, allows a pod to specify how long it should stay bound to a node that has one or both of these problems.

For example, an application with a lot of local state might want to stay bound to node for a long time in the event of network partition, in the hope that the partition will recover and thus the pod eviction can be avoided. The toleration the pod would use in that case would look like

tolerations:
- key: "node.kubernetes.io/unreachable"
  operator: "Exists"
  effect: "NoExecute"
  tolerationSeconds: 6000

Note that Kubernetes automatically adds a toleration for node.kubernetes.io/not-ready with tolerationSeconds=300 unless the pod configuration provided by the user already has a toleration for node.kubernetes.io/not-ready. Likewise it adds a toleration for node.kubernetes.io/unreachable with tolerationSeconds=300 unless the pod configuration provided by the user already has a toleration for node.kubernetes.io/unreachable.

These automatically-added tolerations ensure that the default pod behavior of remaining bound for 5 minutes after one of these problems is detected is maintained. The two default tolerations are added by the DefaultTolerationSeconds admission controller.

DaemonSet pods are created with NoExecute tolerations for the following taints with no tolerationSeconds:

  • node.kubernetes.io/unreachable
  • node.kubernetes.io/not-ready

This ensures that DaemonSet pods are never evicted due to these problems.

Taint Nodes by Condition

The node lifecycle controller automatically creates taints corresponding to Node conditions with NoSchedule effect. Similarly the scheduler does not check Node conditions; instead the scheduler checks taints. This assures that Node conditions don’t affect what’s scheduled onto the Node. The user can choose to ignore some of the Node’s problems (represented as Node conditions) by adding appropriate Pod tolerations.

Starting in Kubernetes 1.8, the DaemonSet controller automatically adds the following NoSchedule tolerations to all daemons, to prevent DaemonSets from breaking.

  • node.kubernetes.io/memory-pressure
  • node.kubernetes.io/disk-pressure
  • node.kubernetes.io/out-of-disk (only for critical pods)
  • node.kubernetes.io/unschedulable (1.10 or later)
  • node.kubernetes.io/network-unavailable (host network only)

Adding these tolerations ensures backward compatibility. You can also add arbitrary tolerations to DaemonSets.

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