You can constrain a PodThe smallest and simplest Kubernetes object. A Pod represents a set of running containers on 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, e.g. 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 nodeSelector
.
This example assumes that you have a basic understanding of Kubernetes pods and that you have set up a Kubernetes cluster.
Run 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.
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:
pods/pod-nginx.yaml
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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.
In addition to labels you attach, nodes come pre-populated with a standard set of labels. These labels are
kubernetes.io/hostname
failure-domain.beta.kubernetes.io/zone
failure-domain.beta.kubernetes.io/region
beta.kubernetes.io/instance-type
kubernetes.io/os
kubernetes.io/arch
Note: The value of these labels is cloud provider specific and is not guaranteed to be reliable. For example, the value ofkubernetes.io/hostname
may 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.
The NodeRestriction
admission plugin prevents kubelets from setting or modifying labels with a node-restriction.kubernetes.io/
prefix.
To make use of that label prefix for node isolation:
node-restriction.kubernetes.io/
prefix to your Node objects, and use those labels in your node selectors.
For example, example.com.node-restriction.kubernetes.io/fips=true
or example.com.node-restriction.kubernetes.io/pci-dss=true
.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 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 requiredDuringSchedulingIgnoredDuringExecution
and
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
to how 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 requiredDuringSchedulingIgnoredDuringExecution
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:
pods/pod-with-node-affinity.yaml
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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-az1
or e2e-az2
. In addition,
among nodes that meet that criteria, nodes with a label whose key is another-node-label-key
and whose
value is 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: In
, NotIn
, Exists
, DoesNotExist
, Gt
, Lt
.
You can use NotIn
and DoesNotExist
to achieve node anti-affinity behavior, or use
node taints to repel pods from specific nodes.
If you specify both nodeSelector
and 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
is satisfied.
If you specify multiple matchExpressions
associated with nodeSelectorTerms
, then the pod can be scheduled onto a node only if all matchExpressions
can be 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.
The 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 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, e.g. 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, i.e. every node in the cluster must have an appropriate label matchingtopologyKey
. If some or all nodes are missing the specifiedtopologyKey
label, it can lead to unintended behavior.
As with node affinity, there are currently two types of pod affinity and anti-affinity, called requiredDuringSchedulingIgnoredDuringExecution
and
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.
pods/pod-with-pod-affinity.yaml
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The affinity on this pod defines one pod affinity rule and one pod anti-affinity rule. In this example, the
podAffinity
is requiredDuringSchedulingIgnoredDuringExecution
while the podAntiAffinity
is preferredDuringSchedulingIgnoredDuringExecution
. 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 failure-domain.beta.kubernetes.io/zone
and
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 prefers not to be scheduled onto a node if that node is already running a pod with label
having key “security” and value “S2”. (If the topologyKey
were failure-domain.beta.kubernetes.io/zone
then
it would mean 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
design doc
for many more examples of pod affinity and anti-affinity, both the requiredDuringSchedulingIgnoredDuringExecution
flavor and the preferredDuringSchedulingIgnoredDuringExecution
flavor.
The legal operators for pod affinity and anti-affinity are In
, NotIn
, Exists
, DoesNotExist
.
In principle, the topologyKey
can be any legal label-key. However,
for performance and security reasons, there are some constraints on topologyKey:
requiredDuringSchedulingIgnoredDuringExecution
pod anti-affinity,
empty topologyKey
is not allowed.requiredDuringSchedulingIgnoredDuringExecution
pod anti-affinity, the admission controller LimitPodHardAntiAffinityTopology
was introduced to limit topologyKey
to kubernetes.io/hostname
. If you want to make it available for custom topologies, you may modify the admission controller, or simply disable it.preferredDuringSchedulingIgnoredDuringExecution
pod anti-affinity, empty topologyKey
is interpreted as “all topologies” (“all topologies” here is now limited to the combination of kubernetes.io/hostname
, failure-domain.beta.kubernetes.io/zone
and failure-domain.beta.kubernetes.io/region
).topologyKey
can be any legal label-key.In addition to labelSelector
and topologyKey
, you can optionally specify a list namespaces
of namespaces which the labelSelector
should match against (this goes at the same level of the definition as labelSelector
and topologyKey
).
If omitted or empty, it defaults to the namespace of the pod where the affinity/anti-affinity definition appears.
All matchExpressions
associated with requiredDuringSchedulingIgnoredDuringExecution
affinity and anti-affinity
must be satisfied for the pod to be scheduled onto a node.
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.
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 podAntiAffinity
and 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:1.12-alpine
If we create the above two deployments, our three node cluster should look like below.
node-1 | node-2 | node-3 |
---|---|---|
webserver-1 | webserver-2 | webserver-3 |
cache-1 | cache-2 | cache-3 |
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
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:
Here is an example of a pod config file using the nodeName
field:
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.
The design documents for node affinity and for inter-pod affinity/anti-affinity contain extra background information about these features.
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.
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