Introduction

OpenShift Pod Placement

- Thomas Jungbauer Thomas Jungbauer ( Lastmod: 2024-05-08 ) - 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

  1. NodeSelector

  2. Pod Affinity and Anti Affinity

  3. Node Affinity

  4. Taints and Tolerations

  5. Topology Spread Constraints

  6. Descheduler

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

See Also:

  • Introducing AdminNetworkPolicies –

    Classic Kubernetes/OpenShift offer a feature called NetworkPolicy that allows users to control the traffic to and from their assigned Namespace. NetworkPolicies are designed to give project owners or tenants the ability to protect their own namespace. Sometimes, however, I worked with customers where the cluster administrators or a dedicated (network) team need to enforce these policies. Since the NetworkPolicy API is namespace-scoped, it is not possible to enforce policies across namespaces. The only solution was to create custom (project) admin and edit roles, and remove the ability of creating, modifying or deleting NetworkPolicy objects. Technically, this is possible and easily done. But shifts the whole network security to cluster administrators. Luckily, this is where AdminNetworkPolicy (ANP) and BaselineAdminNetworkPolicy (BANP) comes into play.

  • Using Kustomize to post render a Helm Chart –

    Lately I came across several issues where a given Helm Chart must be modified after it has been rendered by Argo CD. Argo CD does a helm template to render a Chart. Sometimes, especially when you work with Subcharts or when a specific setting is not yet supported by the Chart, you need to modify it later …​ you need to post-render the Chart. In this very short article, I would like to demonstrate this on a real-live example I had to do. I would like to inject annotations to a Route objects, so that the certificate can be injected. This is done by the cert-utils operator. For the post-rendering the Argo CD repo pod will be extended with a sidecar container, that is watching for the repos and patches them if required.

  • Managing Certificates using GitOps approach –

    The article SSL Certificate Management for OpenShift on AWS explains how to use the Cert-Manager Operator to request and install a new SSL Certificate. This time, I would like to leverage the GitOps approach using the Helm Chart cert-manager I have prepared to deploy the Operator and order new Certificates. I will use an ACME Letsencrypt issuer with a DNS challenge. My domain is hosted at AWS Route 53. However, any other integration can be easily used.

  • Update Cluster Version using GitOps approach –

    During a GitOps journey at one point, the question arises, how to update a cluster? Nowadays it is very easy to update a cluster using CLI or WebUI, so why bother with GitOps in that case? The reason is simple: Using GitOps you can be sure that all clusters are updated to the correct, required version and the version of each cluster is also managed in Git. All you need is the channel you want to use and the desired cluster version. Optionally, you can define the exact image SHA. This might be required when you are operating in a restricted environment.

  • Multiple Sources for Applications in Argo CD –

    Argo CD or OpenShift GitOps uses Applications or ApplicationSets to define the relationship between a source (Git) and a cluster. Typically, this is a 1:1 link, which means one Application is using one source to compare the cluster status. This can be a limitation. For example, if you are working with Helm Charts and a Helm repository, you do not want to re-build (or re-release) the whole chart just because you made a small change in the values file that is packaged into the repository. You want to separate the configuration of the chart with the Helm package. The most common scenarios for multiple sources are (see: Argo CD documentation): Your organization wants to use an external/public Helm chart You want to override the Helm values with your own local values You don’t want to clone the Helm chart locally as well because that would lead to duplication and you would need to monitor it manually for upstream changes. This small article describes three different ways with a working example and tries to cover the advantages and disadvantages of each of them. They might be opinionated but some of them proved to be easier to use and manage.

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