I have written about using Taints and Tolerations to prevent pods from running on certain (tainted) nodes and there is some influence on scheduling that we can exert using Limits and Requests. But if we really want to control pod placement we have to look no further than Node/Pod Affinity and Anti-Affinity. This allows you to specify nodes that your pod can run on (Pod Affinity) and can be used to spread out your pods at runtime to different nodes using Anti-Affinity. Why? Because it’s great to have a container cluster, but if all your pods are landing on a single note your not gonna have a great (up)time. Let’s get started!

As always, these concepts apply to both Kubernetes and Openshift. We will try to do everything from the oc command line.

# Understanding Affinity

Affinity means to have a natural liking to something. In Openshift it means that there is a connection (a preferred grouping) of resources. Naturally Anti-Affinity inverses this. With Affinity you can group workloads together on a single host or ensure that pods land on the same server. This can be useful if your workload gains performance by being scheduled together. The inverse is also true. By using Anti-Affinity rules we can make sure not all of our frontend pods are being run on the same node so that when it might go down or get busy our application pods won’t go down all at once.

Affinity is specified in your pod spec, pod.spec.affinity. Tip! Use oc explain pod.spec.affinity for some helpful info:

$oc explain pod.spec.affinity KIND: Pod VERSION: v1 RESOURCE: affinity <Object> DESCRIPTION: If specified, the pod's scheduling constraints Affinity is a group of affinity scheduling rules. FIELDS: nodeAffinity <Object> Describes node affinity scheduling rules for the pod. podAffinity <Object> Describes pod affinity scheduling rules (e.g. co-locate this pod in the same node, zone, etc. as some other pod(s)). podAntiAffinity <Object> Describes pod anti-affinity scheduling rules (e.g. avoid putting this pod in the same node, zone, etc. as some other pod(s)).  ## Node Affinity With nodeAffinity we can ask the pod to be scheduled (or not to be scheduled) on a node with a certain label. This works a lot like a toleration (pod.spec.tolerations) ## Pod Affinity • podAffinity is used to tell our pod to schedule our pod with other pods based on affinity rules • podAntiAffinity enables us to separate pods based on affinity rules ## Required fiels When using a Affinity rule you also need to specify the topologyKey: kubernetes.io/hostname in the yaml. Also, when using a Preferred rule you need to set a weight so that the scheduler knows (on a scale from 1-100) how strongly it should weigh the preference. ## Why not taint? At this point you might be asking, why not use a toleration or the nodeSelector found in the pods spec? This is a good question. Using these techniques gives us controll on where to place a pod but it does based on static information on the node. Using Affinity rules we can schedule dynamilcy based on where other pods are located. # Affinity Rules So, how does this work? Affinity Rules use matchExpressions based on key=value pairs to match. We will take the following yaml as an example: kind: Pod metadata: name: looking-for-a-green-pod spec: affinity: podAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: color operator: In values: - green - darkgreen - lightgreen topologyKey: kubernetes.io/hostname containers: - name: looking-for-a-green-pod image: docker.io/ocpqe/hello-pod  This will create a pod called looking-for-a-green-pod that looks for another pod that has the key color with one of three values green, darkgreen and lightgreen. We could easily create a pod called black-and-white that just wont schedule on the same node as a pod with color defined using the following affinity rule: spec: affinity: podAffinity: requiredDuringSchedulingIgnoredDuringExecution: labelSelector: - matchExpressions: - key: color operator: Exists  ## Understanding operators The operators we can use are: • In Meaning one of the values in the key matches our value • NotIn Meaning the value is not in the value of the key • Exists Meaning the value exists in the key • DoesNotExist The value should not exist in the key • Lt Lesser then • Gt Greater then ## Required and Preferred We can set up our Affinity rules in two modes, “Required” and “Preferred”. Let me explain: • Required Affinity rules have to be met before a pod is scheduled on a node • Preferred Affinity rules are, well, preferred. We would like these rules to be met but we can be a bit more flexible # Creating pods with Affinity rules Lets spin up two pods that want to be scheduled together, green-pod and looking-for-a-green-pod: # green-pod.yaml apiVersion: v1 kind: Pod metadata: name: green-pod labels: color: green spec: containers: - name: green-pod image: docker.io/ocpqe/hello-pod  # looking-for-a-green-pod apiVersion: v1 kind: Pod metadata: name: looking-for-a-green-pod spec: affinity: podAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: color operator: In values: - green - darkgreen - lightgreen topologyKey: kubernetes.io/hostname containers: - name: looking-for-a-green-pod image: docker.io/ocpqe/hello-pod  You can save both these definitions to a yaml file and use oc apply -f FILE to create the. When this is done they should both be running on the same node: $ oc get pods -o wide
green-pod                 1/1     Running   0          11m   10.217.0.98    crc-ktfxm-master-0   <none>           <none>
looking-for-a-green-pod   1/1     Running   0          64s   10.217.0.101   crc-ktfxm-master-0   <none>           <none>


Let’s create our pod that does not like any color:

# black-and-white.yaml
apiVersion: v1
kind: Pod
name: black-and-white
spec:
affinity:
podAntiAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
- labelSelector:
matchExpressions:
- key: color
operator: Exists
topologyKey: kubernetes.io/hostname
containers:
- name: black-and-white
image: docker.io/ocpqe/hello-pod


Now when we have a look at our pods we will see that our newest one does not like to run with the other pods:

$oc get pods -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES black-and-white 0/1 Pending 0 14s <none> <none> <none> <none> green-pod 1/1 Running 0 16m 10.217.0.98 crc-ktfxm-master-0 <none> <none> looking-for-a-green-pod 1/1 Running 0 6m34s 10.217.0.101 crc-ktfxm-master-0 <none> <none>  Note Because this is running on CRC which is single node cluster the pod will not start because there are no other nodes available. And we can see the effect with oc describe: $ oc describe pod black-and-white
....
Events:
Type     Reason            Age                 From               Message
----     ------            ----                ----               -------
Warning  FailedScheduling  36s (x2 over 101s)  default-scheduler  0/1 nodes are available: 1 node(s) didn't match pod anti-affinity rules.


Not lets change the pod from requiring the affinity rule from being met to a preffered rule. This is not as simple as swapping out requiredDuringSchedulingIgnoredDuringExecution because a preferred rules needs some extra information to work with, we will update our yaml to:

apiVersion: v1
kind: Pod
name: black-and-white
spec:
affinity:
podAffinity:
preferredDuringSchedulingIgnoredDuringExecution:
- weight: 50
podAffinityTerm:
labelSelector:
matchExpressions:
- key: color
operator: Exists
topologyKey: kubernetes.io/hostname
containers:
- name: black-and-white
image: docker.io/ocpqe/hello-pod


As we can see in the events now all pods are scheduled on the same node. Even the black-and-white pod because despite its preference there is simply no other node to run on.

\$ oc get events
LAST SEEN   TYPE      REASON             OBJECT                        MESSAGE
1m         Normal    Scheduled          pod/black-and-white           Successfully assigned all-together-now/black-and-white to crc-ktfxm-master-0


# Wrapping up

Using Affinity Rules can help us dynamically select where our pods are scheduled based on node labels and other pods. This makes it easy to spread out a workload across a cluster or keep pods together for maximum performance.

I hope this post has helped you. Check out my other EX280 related content on my EX280 page

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