In my project, need to test that Guaranteed Application pods should evict any dummy application pods which are running. How do I achieve this such that application pods are always highest priority.
CodePudding user response：
You can make use of kind: PriorityClass to give your application a higher priority then normal pods.
CodePudding user response：
The eviction is based on the priority of the Pod, QoS, and the actual usage of the Pod. If the Pod belongs to a higher priority pod, its creation will preempt the bestEffort, followed by burstable followed by guaranteed pods.
For example: In my cluster, I have the following priority classes:
kubectl get priorityclasses.scheduling.k8s.io
NAME VALUE GLOBAL-DEFAULT AGE
k8s-cluster-critical 1000000000 false 11d
system-cluster-critical 2000000000 false 11d
system-node-critical 2000001000 false 11d
For the sake of example, I used the system-cluster-critical class. Do not do this, have your priority class. The following Pod would lead to the eviction of other pods.
---
apiVersion: v1
kind: Pod
metadata:
name: guaranteed
spec:
nodeName: kube-worker-1
priorityClassName: system-cluster-critical
containers:
- name: app
image: nginx
resources:
requests:
cpu: 1000m
memory: 300Mi
limits:
cpu: 1000m
memory: 300Mi
In the description of the other pods, you would see the following:
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Pulling 3m19s kubelet Pulling image "nginx"
Normal Pulled 3m19s kubelet Successfully pulled image "nginx" in 495.693296ms
Normal Created 3m19s kubelet Created container app
Normal Started 3m19s kubelet Started container app
Warning Preempting 18s kubelet Preempted in order to admit critical Pod
Normal Killing 18s kubelet Stopping container app
CodePudding user response：
The answer provided by the P.... is very good and useful. By Pod Priority and Preemption you can achieve what you are up to.
However, apart from that, you can use dedicated solutions, for example in the clouds. Look at the Google cloud example:
Before priority and preemption, Kubernetes pods were scheduled purely on a first-come-first-served basis, and ran to completion (or forever, in the case of pods created by something like a Deployment or StatefulSet). This meant less important workloads could block more important, later-arriving, workloads from running—not the desired effect. Priority and preemption solves this problem.
Priority and preemption is valuable in a number of scenarios. For example, imagine you want to cap autoscaling to a maximum cluster size to control costs, or you have clusters that you can’t grow in real-time (e.g., because they are on-premises and you need to buy and install additional hardware). Or you have high-priority cloud workloads that need to scale up faster than the cluster autoscaler can add nodes. In short, priority and preemption lead to better resource utilization, lower costs and better service levels for critical applications.
Additional guides for other clouds:
See also this useful tutorial.