for i in {1..3};
do
kubectl run \
resource-consumer-$i \
--image=gcr.io/kubernetes-e2e-test-images/resource-consumer:1.4 \
--expose \
--service-overrides='{ "spec": { "type": "LoadBalancer" } }' --port 8080
done
Scale the deployments.
for i in {1..3};
do
kubectl scale deployment --replicas=200 resource-consumer-$i
done
Get the public IPs.
for i in {1..3};
do
kubectl get services resource-consumer-$i
done
Trigger resource usage.
for i in {1..100};
do
curl --data "millicores=4000&durationSec=3600" http://IP.OF.SERVICE-01:8080/ConsumeCPU;
curl --data "millicores=4000&durationSec=3600" http://IP.OF.SERVICE-02:8080/ConsumeCPU;
curl --data "millicores=4000&durationSec=3600" http://IP.OF.SERVICE-03:8080/ConsumeCPU;
done
References
Debug and troubleshoot
Log Analytics
Create a Log Analytics Workspace
.
Add Diagnostic Settings on your AKS Resource Group (not the MC_...)
Go to logs and query.
AzureDiagnostics
| where Category == "cluster-autoscaler"
References
Configmap
Check out autoscaler configmap.
kubectl get configmap -n kube-system cluster-autoscaler-status -o yaml