Assigning Pods to Nodes
You can constrain a PodA Pod represents a set of running containers in your cluster. to only be able to run on particular Node(s)A node is a worker machine in Kubernetes. , or to prefer to run on particular nodes. There are several ways to do this, and the recommended approaches all use label selectors to make the selection. Generally such constraints are unnecessary, as the scheduler will automatically do a reasonable placement (e.g. spread your pods across nodes, not place the pod on a node with insufficient free resources, etc.) but there are some circumstances where you may want more control on a node where a pod lands, for example to ensure that a pod ends up on a machine with an SSD attached to it, or to co-locate pods from two different services that communicate a lot into the same availability zone.
nodeSelector is the simplest recommended form of node selection constraint.
nodeSelector is a field of PodSpec. It specifies a map of key-value pairs. For the pod to be eligible
to run on a node, the node must have each of the indicated key-value pairs as labels (it can have
additional labels as well). The most common usage is one key-value pair.
Let's walk through an example of how to use
Step Zero: Prerequisites
This example assumes that you have a basic understanding of Kubernetes pods and that you have set up a Kubernetes cluster.
Step One: Attach label to the node
kubectl get nodes to get the names of your cluster's nodes. Pick out the one that you want to add a label to, and then run
kubectl label nodes <node-name> <label-key>=<label-value> to add a label to the node you've chosen. For example, if my node name is 'kubernetes-foo-node-1.c.a-robinson.internal' and my desired label is 'disktype=ssd', then I can run
kubectl label nodes kubernetes-foo-node-1.c.a-robinson.internal disktype=ssd.
You can verify that it worked by re-running
kubectl get nodes --show-labels and checking that the node now has a label. You can also use
kubectl describe node "nodename" to see the full list of labels of the given node.
Step Two: Add a nodeSelector field to your pod configuration
Take whatever pod config file you want to run, and add a nodeSelector section to it, like this. For example, if this is my pod config:
apiVersion: v1 kind: Pod metadata: name: nginx labels: env: test spec: containers: - name: nginx image: nginx
Then add a nodeSelector like so:
When you then run
kubectl apply -f https://k8s.io/examples/pods/pod-nginx.yaml,
the Pod will get scheduled on the node that you attached the label to. You can
verify that it worked by running
kubectl get pods -o wide and looking at the
"NODE" that the Pod was assigned to.
Interlude: built-in node labels
In addition to labels you attach, nodes come pre-populated with a standard set of labels. These labels are
Note: The value of these labels is cloud provider specific and is not guaranteed to be reliable. For example, the value of
kubernetes.io/hostnamemay be the same as the Node name in some environments and a different value in other environments.
Adding labels to Node objects allows targeting pods to specific nodes or groups of nodes. This can be used to ensure specific pods only run on nodes with certain isolation, security, or regulatory properties. When using labels for this purpose, choosing label keys that cannot be modified by the kubelet process on the node is strongly recommended. This prevents a compromised node from using its kubelet credential to set those labels on its own Node object, and influencing the scheduler to schedule workloads to the compromised node.
NodeRestriction admission plugin prevents kubelets from setting or modifying labels with a
To make use of that label prefix for node isolation:
- Ensure you are using the Node authorizer and have enabled the NodeRestriction admission plugin.
- Add labels under the
node-restriction.kubernetes.io/prefix to your Node objects, and use those labels in your node selectors. For example,
Affinity and anti-affinity
nodeSelector provides a very simple way to constrain pods to nodes with particular labels. The affinity/anti-affinity
feature, greatly expands the types of constraints you can express. The key enhancements are
- The affinity/anti-affinity language is more expressive. The language offers more matching rules besides exact matches created with a logical AND operation;
- you can indicate that the rule is "soft"/"preference" rather than a hard requirement, so if the scheduler can't satisfy it, the pod will still be scheduled;
- you can constrain against labels on other pods running on the node (or other topological domain), rather than against labels on the node itself, which allows rules about which pods can and cannot be co-located
The affinity feature consists of two types of affinity, "node affinity" and "inter-pod affinity/anti-affinity".
Node affinity is like the existing
nodeSelector (but with the first two benefits listed above),
while inter-pod affinity/anti-affinity constrains against pod labels rather than node labels, as
described in the third item listed above, in addition to having the first and second properties listed above.
Node affinity is conceptually similar to
nodeSelector -- it allows you to constrain which nodes your
pod is eligible to be scheduled on, based on labels on the node.
There are currently two types of node affinity, called
preferredDuringSchedulingIgnoredDuringExecution. You can think of them as "hard" and "soft" respectively,
in the sense that the former specifies rules that must be met for a pod to be scheduled onto a node (just like
nodeSelector but using a more expressive syntax), while the latter specifies preferences that the scheduler
will try to enforce but will not guarantee. The "IgnoredDuringExecution" part of the names means that, similar
nodeSelector works, if labels on a node change at runtime such that the affinity rules on a pod are no longer
met, the pod will still continue to run on the node. In the future we plan to offer
requiredDuringSchedulingRequiredDuringExecution which will be just like
except that it will evict pods from nodes that cease to satisfy the pods' node affinity requirements.
Thus an example of
requiredDuringSchedulingIgnoredDuringExecution would be "only run the pod on nodes with Intel CPUs"
and an example
preferredDuringSchedulingIgnoredDuringExecution would be "try to run this set of pods in failure
zone XYZ, but if it's not possible, then allow some to run elsewhere".
Node affinity is specified as field
nodeAffinity of field
affinity in the PodSpec.
Here's an example of a pod that uses node affinity:
This node affinity rule says the pod can only be placed on a node with a label whose key is
kubernetes.io/e2e-az-name and whose value is either
e2e-az2. In addition,
among nodes that meet that criteria, nodes with a label whose key is
another-node-label-key and whose
another-node-label-value should be preferred.
You can see the operator
In being used in the example. The new node affinity syntax supports the following operators:
You can use
DoesNotExist to achieve node anti-affinity behavior, or use
node taints to repel pods from specific nodes.
If you specify both
nodeAffinity, both must be satisfied for the pod
to be scheduled onto a candidate node.
If you specify multiple
nodeSelectorTerms associated with
nodeAffinity types, then the pod can be scheduled onto a node if one of the
nodeSelectorTerms can be satisfied.
If you specify multiple
matchExpressions associated with
nodeSelectorTerms, then the pod can be scheduled onto a node only if all
matchExpressions is satisfied.
If you remove or change the label of the node where the pod is scheduled, the pod won't be removed. In other words, the affinity selection works only at the time of scheduling the pod.
weight field in
preferredDuringSchedulingIgnoredDuringExecution is in the range 1-100. For each node that meets all of the scheduling requirements (resource request, RequiredDuringScheduling affinity expressions, etc.), the scheduler will compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node matches the corresponding MatchExpressions. This score is then combined with the scores of other priority functions for the node. The node(s) with the highest total score are the most preferred.
Inter-pod affinity and anti-affinity
Inter-pod affinity and anti-affinity allow you to constrain which nodes your pod is eligible to be scheduled based on
labels on pods that are already running on the node rather than based on labels on nodes. The rules are of the form
"this pod should (or, in the case of anti-affinity, should not) run in an X if that X is already running one or more pods that meet rule Y".
Y is expressed as a LabelSelector with an optional associated list of namespaces; unlike nodes, because pods are namespaced
(and therefore the labels on pods are implicitly namespaced),
a label selector over pod labels must specify which namespaces the selector should apply to. Conceptually X is a topology domain
like node, rack, cloud provider zone, cloud provider region, etc. You express it using a
topologyKey which is the
key for the node label that the system uses to denote such a topology domain; for example, see the label keys listed above
in the section Interlude: built-in node labels.
Note: Inter-pod affinity and anti-affinity require substantial amount of processing which can slow down scheduling in large clusters significantly. We do not recommend using them in clusters larger than several hundred nodes.
Note: Pod anti-affinity requires nodes to be consistently labelled, in other words every node in the cluster must have an appropriate label matching
topologyKey. If some or all nodes are missing the specified
topologyKeylabel, it can lead to unintended behavior.
As with node affinity, there are currently two types of pod affinity and anti-affinity, called
preferredDuringSchedulingIgnoredDuringExecution which denote "hard" vs. "soft" requirements.
See the description in the node affinity section earlier.
An example of
requiredDuringSchedulingIgnoredDuringExecution affinity would be "co-locate the pods of service A and service B
in the same zone, since they communicate a lot with each other"
and an example
preferredDuringSchedulingIgnoredDuringExecution anti-affinity would be "spread the pods from this service across zones"
(a hard requirement wouldn't make sense, since you probably have more pods than zones).
Inter-pod affinity is specified as field
podAffinity of field
affinity in the PodSpec.
And inter-pod anti-affinity is specified as field
podAntiAffinity of field
affinity in the PodSpec.
An example of a pod that uses pod affinity:
The affinity on this pod defines one pod affinity rule and one pod anti-affinity rule. In this example, the
pod affinity rule says that the pod can be scheduled onto a node only if that node is in the same zone
as at least one already-running pod that has a label with key "security" and value "S1". (More precisely, the pod is eligible to run
on node N if node N has a label with key
failure-domain.beta.kubernetes.io/zone and some value V
such that there is at least one node in the cluster with key
value V that is running a pod that has a label with key "security" and value "S1".) The pod anti-affinity
rule says that the pod cannot be scheduled onto a node if that node is in the same zone as a pod with
label having key "security" and value "S2". See the
for many more examples of pod affinity and anti-affinity, both the
flavor and the
The legal operators for pod affinity and anti-affinity are
In principle, the
topologyKey can be any legal label-key. However,
for performance and security reasons, there are some constraints on topologyKey:
- For pod affinity, empty
topologyKeyis not allowed in both
- For pod anti-affinity, empty
topologyKeyis also not allowed in both
requiredDuringSchedulingIgnoredDuringExecutionpod anti-affinity, the admission controller
LimitPodHardAntiAffinityTopologywas introduced to limit
kubernetes.io/hostname. If you want to make it available for custom topologies, you may modify the admission controller, or simply disable it.
- Except for the above cases, the
topologyKeycan be any legal label-key.
In addition to
topologyKey, you can optionally specify a list
of namespaces which the
labelSelector should match against (this goes at the same level of the definition as
If omitted or empty, it defaults to the namespace of the pod where the affinity/anti-affinity definition appears.
matchExpressions associated with
requiredDuringSchedulingIgnoredDuringExecution affinity and anti-affinity
must be satisfied for the pod to be scheduled onto a node.
More Practical Use-cases
Interpod Affinity and AntiAffinity can be even more useful when they are used with higher level collections such as ReplicaSets, StatefulSets, Deployments, etc. One can easily configure that a set of workloads should be co-located in the same defined topology, eg., the same node.
Always co-located in the same node
In a three node cluster, a web application has in-memory cache such as redis. We want the web-servers to be co-located with the cache as much as possible.
Here is the yaml snippet of a simple redis deployment with three replicas and selector label
app=store. The deployment has
PodAntiAffinity configured to ensure the scheduler does not co-locate replicas on a single node.
apiVersion: apps/v1 kind: Deployment metadata: name: redis-cache spec: selector: matchLabels: app: store replicas: 3 template: metadata: labels: app: store spec: affinity: podAntiAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: app operator: In values: - store topologyKey: "kubernetes.io/hostname" containers: - name: redis-server image: redis:3.2-alpine
The below yaml snippet of the webserver deployment has
podAffinity configured. This informs the scheduler that all its replicas are to be co-located with pods that have selector label
app=store. This will also ensure that each web-server replica does not co-locate on a single node.
apiVersion: apps/v1 kind: Deployment metadata: name: web-server spec: selector: matchLabels: app: web-store replicas: 3 template: metadata: labels: app: web-store spec: affinity: podAntiAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: app operator: In values: - web-store topologyKey: "kubernetes.io/hostname" podAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: app operator: In values: - store topologyKey: "kubernetes.io/hostname" containers: - name: web-app image: nginx:1.16-alpine
If we create the above two deployments, our three node cluster should look like below.
As you can see, all the 3 replicas of the
web-server are automatically co-located with the cache as expected.
kubectl get pods -o wide
The output is similar to this:
NAME READY STATUS RESTARTS AGE IP NODE redis-cache-1450370735-6dzlj 1/1 Running 0 8m 10.192.4.2 kube-node-3 redis-cache-1450370735-j2j96 1/1 Running 0 8m 10.192.2.2 kube-node-1 redis-cache-1450370735-z73mh 1/1 Running 0 8m 10.192.3.1 kube-node-2 web-server-1287567482-5d4dz 1/1 Running 0 7m 10.192.2.3 kube-node-1 web-server-1287567482-6f7v5 1/1 Running 0 7m 10.192.4.3 kube-node-3 web-server-1287567482-s330j 1/1 Running 0 7m 10.192.3.2 kube-node-2
Never co-located in the same node
The above example uses
PodAntiAffinity rule with
topologyKey: "kubernetes.io/hostname" to deploy the redis cluster so that
no two instances are located on the same host.
See ZooKeeper tutorial
for an example of a StatefulSet configured with anti-affinity for high availability, using the same technique.
nodeName is the simplest form of node selection constraint, but due
to its limitations it is typically not used.
nodeName is a field of
PodSpec. If it is non-empty, the scheduler ignores the pod and the
kubelet running on the named node tries to run the pod. Thus, if
nodeName is provided in the PodSpec, it takes precedence over the
above methods for node selection.
Some of the limitations of using
nodeName to select nodes are:
- If the named node does not exist, the pod will not be run, and in some cases may be automatically deleted.
- If the named node does not have the resources to accommodate the pod, the pod will fail and its reason will indicate why, for example OutOfmemory or OutOfcpu.
- Node names in cloud environments are not always predictable or stable.
Here is an example of a pod config file using the
apiVersion: v1 kind: Pod metadata: name: nginx spec: containers: - name: nginx image: nginx nodeName: kube-01
The above pod will run on the node kube-01.
Taints allow a Node to repel a set of Pods.
Once a Pod is assigned to a Node, the kubelet runs the Pod and allocates node-local resources. The topology manager can take part in node-level resource allocation decisions.