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Taints and Tolerations
Node affinity 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.
Tolerations are applied to pods. Tolerations allow the scheduler to schedule pods with matching taints. Tolerations allow scheduling but don't guarantee scheduling: the scheduler also evaluates other parameters as part of its function.
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.
You add a taint to a node using kubectl taint. For example,
kubectl taint nodes node1 key1=value1:NoSchedule
places a taint on node
node1. The taint has key
value1, and taint effect
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 key1=value1: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
tolerations: - key: "key1" operator: "Equal" value: "value1" effect: "NoSchedule"
tolerations: - key: "key1" operator: "Exists" effect: "NoSchedule"
Here's an example of a pod that uses tolerations:
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"
The default value for
A toleration "matches" a taint if the keys are the same and the effects are the same, and:
Exists(in which case no
valueshould be specified), or
values are equal.
There are two special cases:
key with operator
Exists matches all keys, values and effects which means this
will tolerate everything.
effect matches all effects with key
The above example used
NoSchedule. Alternatively, you can use
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
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
NoSchedulethen Kubernetes will not schedule the pod onto that node
- if there is no un-ignored taint with effect
NoSchedulebut there is at least one un-ignored taint with effect
PreferNoSchedulethen Kubernetes will try to not schedule the pod onto the node
- if there is at least one un-ignored taint with effect
NoExecutethen 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
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
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:NoScheduleor
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
ExtendedResourceTolerationadmission 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
Kubernetes v1.18 [stable]
NoExecute taint effect, mentioned above, 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
tolerationSecondsin their toleration specification remain bound forever
- pods that tolerate the taint with a specified
tolerationSecondsremain bound for the specified amount of time
The node controller automatically taints a Node when certain conditions are true. The following taints are built in:
node.kubernetes.io/not-ready: Node is not ready. This corresponds to the NodeCondition
node.kubernetes.io/unreachable: Node is unreachable from the node controller. This corresponds to the NodeCondition
node.kubernetes.io/memory-pressure: Node has memory pressure.
node.kubernetes.io/disk-pressure: Node has disk pressure.
node.kubernetes.io/pid-pressure: Node has PID 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
NoExecute effect. If the fault condition returns to normal the kubelet or node
controller can remove the relevant taint(s).
You can specify
tolerationSeconds for a Pod to define how long that Pod stays bound
to a failing or unresponsive Node.
For example, you might want to keep an application with a lot of local state bound to node for a long time in the event of network partition, hoping that the partition will recover and thus the pod eviction can be avoided. The toleration you set for that Pod might look like:
tolerations: - key: "node.kubernetes.io/unreachable" operator: "Exists" effect: "NoExecute" tolerationSeconds: 6000
Kubernetes automatically adds a toleration for
unless you, or a controller, set those tolerations explicitly.
These automatically-added tolerations mean that Pods remain bound to Nodes for 5 minutes after one of these problems is detected.
DaemonSet pods are created with
NoExecute tolerations for the following taints with no
This ensures that DaemonSet pods are never evicted due to these problems.
Taint Nodes by Condition
The control plane, using the node controller,
automatically creates taints with a
NoSchedule effect for
The scheduler checks taints, not node conditions, when it makes scheduling
decisions. This ensures that node conditions don't directly affect scheduling.
For example, if the
DiskPressure node condition is active, the control plane
node.kubernetes.io/disk-pressure taint and does not schedule new pods
onto the affected node. If the
MemoryPressure node condition is active, the
control plane adds the
You can ignore node conditions for newly created pods by adding the corresponding
Pod tolerations. The control plane also adds the
toleration on pods that have a QoS class
BestEffort. This is because Kubernetes treats pods in the
Burstable QoS classes (even pods with no memory request set) as if they are
able to cope with memory pressure, while new
BestEffort pods are not scheduled
onto the affected node.
The DaemonSet controller automatically adds the following
tolerations to all daemons, to prevent DaemonSets from breaking.
node.kubernetes.io/pid-pressure(1.14 or later)
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.
- Read about Node-pressure Eviction and how you can configure it
- Read about Pod Priority