Scaler Operator is a kubernetes operator that aims to scale your desired pods based on metrics that you can define using the custom resources manifest files. It's purpose is to replace the HPA (Horizontal Pod Autoscaler). I will be releasing in the upcoming releases more features (scaling in, maybe cost calculator, mutli-deployment scaling...).
From the most basic perspective, the HorizontalPodAutoscaler controller operates on the ratio between desired metric value and current metric value:
NOTE: desiredReplicas = ceil[currentReplicas * ( currentMetricValue / desiredMetricValue )]
For example, if the current metric value is 200m, and the desired value is 100m, the number of replicas will be doubled, since 200.0 / 100.0 == 2.0 If the current value is instead 50m, you'll halve the number of replicas, since 50.0 / 100.0 == 0.5. The control plane skips any scaling action if the ratio is sufficiently close to 1.0 (within a globally-configurable tolerance, 0.1 by default).
- Can survive being rescheduled without impacting function outside of being momentarily unavailable.
- Uses more sophisticated control algorithms than just proportional control based on a single measurement.
- Highly configurable.
- Well tested. (not sure)
- go version v1.20.0+
- docker version 17.03+.
- kubectl version v1.11.3+.
- Access to a Kubernetes v1.11.3+ cluster.
Build and push your image to the location specified by IMG:
make docker-build docker-push IMG=<some-registry>/scaleroperator:tagNOTE: This image ought to be published in the personal registry you specified. And it is required to have access to pull the image from the working environment. Make sure you have the proper permission to the registry if the above commands don’t work.
Install the CRDs into the cluster:
make installDeploy the Manager to the cluster with the image specified by IMG:
make deploy IMG=<some-registry>/scaleroperator:tagNOTE: If you encounter RBAC errors, you may need to grant yourself cluster-admin privileges or be logged in as admin.
Create instances of your solution You can apply the samples (examples) from the config/sample:
kubectl apply -k config/samples/NOTE: Ensure that the samples has default values to test it out.
Delete the instances (CRs) from the cluster:
kubectl delete -k config/samples/Delete the APIs(CRDs) from the cluster:
make uninstallUnDeploy the controller from the cluster:
make undeployCopyright 2024 Malek.
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