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Introduction

August 26, 2021 - By: Thomas Jungbauer ( Lastmod: 2021-09-03 )

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.

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

Introduction

Pod Placement Series

Prerequisites