Introduction
- - 2 min read
Pod scheduling is an internal process that determines placement of new pods onto nodes within the cluster. It is probably one of the most important tasks for a Day-2 scenario and should be considered at a very early stage for a new cluster. OpenShift/Kubernetes is already shipped with a default scheduler which schedules pods as they get created accross the cluster, without any manual steps.
However, there are scenarios where a more advanced approach is required, like for example using a specifc group of nodes for dedicated workload or make sure that certain applications do not run on the same nodes. Kubernetes provides different options:
Controlling placement with node selectors
Controlling placement with pod/node affinity/anti-affinity rules
Controlling placement with taints and tolerations
Controlling placement with topology spread constraints
This series will try to go into the detail of the different options and explains in simple examples how to work with pod placement rules. It is not a replacement for any official documentation, so always check out Kubernetes and or OpenShift documentations.
Pod Placement Series
Prerequisites
The following prerequisites are used for all examples. |
Let’s image that our cluster (OpenShift 4) has 4 compute nodes
oc get node --selector='node-role.kubernetes.io/worker'
NAME STATUS ROLES AGE VERSION
compute-0 Ready worker 7h1m v1.19.0+d59ce34
compute-1 Ready worker 7h1m v1.19.0+d59ce34
compute-2 Ready worker 7h1m v1.19.0+d59ce34
compute-3 Ready worker 7h1m v1.19.0+d59ce34
An example application (from the catalog Django + Postgres) has been deployed in the namespace podtesting
. It contains by default 1 pod for a PostGresql database and one pod for a frontend web application.
oc get pods -n podtesting -o wide | grep Running
django-psql-example-1-h6kst 1/1 Running 0 20m 10.130.2.97 compute-2 <none> <none>
postgresql-1-4pcm4 1/1 Running 0 21m 10.131.0.51 compute-3 <none> <none>
Without any configuration the OpenShift scheduler will try to spread the pods evenly accross the cluster.
Let’s increase the replica of the web frontend:
oc scale --replicas=4 dc/django-psql-example -n podtesting
Eventually 4 additional pods will be started accross the compute nodes of the cluster:
oc get pods -n podtesting -o wide | grep Running
django-psql-example-1-842fl 1/1 Running 0 2m7s 10.131.0.65 compute-3 <none> <none>
django-psql-example-1-h6kst 1/1 Running 0 24m 10.130.2.97 compute-2 <none> <none>
django-psql-example-1-pxhlv 1/1 Running 0 2m7s 10.128.2.13 compute-0 <none> <none>
django-psql-example-1-xms7x 1/1 Running 0 2m7s 10.129.2.10 compute-1 <none> <none>
postgresql-1-4pcm4 1/1 Running 0 26m 10.131.0.51 compute-3 <none> <none>
As you can see, the scheduler already tries to spread the pods evenly, so that every worker node will host one frontend pod.
However, let’s try to apply a more advanced configuration for the pod placement, starting with the Pod Placement - NodeSelector
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