Table of Contents
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Introduction
The purpose of this test is to demonstrate two scheduling use cases of text sentiment analysis service:
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Test Framework
Hardware:
Control-panalpanel: 192.168.30.12，192.168.30.21
Worker-Cluseter1： Cluster1： 192.168.30.5 、192.168.30.22、192.168.30.20
Worker-Cluseter2： Cluster2： 192.168.30.2、192.168.30.16、192.168.30.25
Software:
Karmada: V1.4.0, Open, Multi-Cloud, Multi-Cluster Kubernetes Orchestration
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2．Create nginx deployment yaml file.
Create a deployment and name it sentiment. Execute commands as follow:
kubectl --kubeconfig /etc/karmada/karmada-apiserver.config create -f deployment.yaml |
3. Create a distribution yaml file, PropagationPolicy.yaml：
apiVersion: policy.karmada.io/v1alpha1 kind: PropagationPolicy metadata: name: sentiment-propagation spec: resourceSelectors: - apiVersion: apps/v1 kind: Deployment name: sentiment placement: clusterAffinity: clusterNames: - member1 - member2 replicaScheduling: replicaDivisionPreference: Weighted replicaSchedulingType: Divided weightPreference: staticWeightList: - targetCluster: clusterNames: - member1 weight: 1 - targetCluster: clusterNames: - member2 weight: 1 |
4.Create PropagationPolicy that will propagate distribute sentiment to worker cluster
We need to create a policy to propagate distribute the deployment to our member worker cluster. Execute commands as follow:
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7.Retry, Check the deployment status
We can check deployment status, don't need to access member cluster. Execute commands as follow:
in In worker cluseter，we can see results the result as follow:
Case 2. Rescheduling
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# get the pod in cluster worker1 $ kubectl --context worker1 get pod No resources found in default namespace. # get a list of pods in cluster worker2 $ kubectl --context worker2 get pod NAME READY STATUS RESTARTS AGE sentiment-6fd4c7867c-hvzfd 1/1 Running 0 6m3s sentiment-6fd4c7867c-vrmnm 1/1 Running 0 4s |
Test Dashboards
N/A
Additional Testing
N/A
Bottlenecks/Errata
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