The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". The cookie is used to store the user consent for the cookies in the category "Analytics". This cookie is set by GDPR Cookie Consent plugin. These cookies ensure basic functionalities and security features of the website, anonymously. Necessary cookies are absolutely essential for the website to function properly. If you keep the application idle for a while, you will see that the Autoscaler will downscale your Pods back to 1. See as an example the following limits.json file: do curl done Īs you can see, the Autoscaler has created two additional Pods to meet the number of requests: Ok, now in order to configure an autoscaler mechanism, we need to define a limit range, which is a mechanism for specifying default project CPU and memory limits and requests. Now wait for the application pod to be available: $ oc get pods In order to test autoscaling we will create an application based on WildFly image that will be requested in a loop so that the autoscaler will be able to scale up the number of pods: $ oc new-app wildfly~ -context-dir=wildfly-basic -name=wildfly-basicĪnd expose the service through the router with: $ oc expose service wildfly-basic Start Openshift using the –metrics option as described in detail in this tutorial: Configuring metrics on Openshift $ oc cluster up -metrics Some steps are however necessary: At first you need to enable metrics One key aspect of Openshift Paas is the ability to provide an automatic mechanism to scale Pods. However the number of Pods, out of the box, is a static value which can be changed manually with: oc scale -replicas= Out of the box when you create a new application with Openshift, a Pod will be automatically deployed with that application and the Replication Controller ensures that the configured number of Pods will remain available.
Ocp cpu stress test how to#
This tutorial will demonstrate how to use the Autoscaling feature to let Openshift automatically scale the number of Pods based on the amount of resources required by the Pod, up to a certain limit.
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