This project is a fork of OpenAI's Kubernetes-ec2-autoscaler

If you need autoscaling for VMSS instead, check out OpenAI/kubernetes-ec2-autoscaler:azure or cluster-autoscaler

kubernetes-acs-autoscaler

kubernetes-acs-autoscaler is a node-level autoscaler for Kubernetes on Azure Container Services. Kubernetes is a container orchestration framework that schedules Docker containers on a cluster, and kubernetes-acs-autoscaler can scale based on the pending job queue.

Architecture

Setup

The autoscaler can be run anywhere as long as it can access the Azure and Kubernetes APIs, but the recommended way is to set it up as a Kubernetes Pod.

Credentials

You need to provide a Service Principal to the autoscaler. You can create one using Azure CLI:
az ad sp create-for-rbac

The best way to use the access key in Kubernetes is with a secret.

Here is a sample format for secret.yaml:

apiVersion: v1
kind: Secret
metadata:
  name: autoscaler
data:
  azure-sp-app-id: [base64 encoded app id]
  azure-sp-secret: [base64 encoded secret access key]
  azure-sp-tenant-id: [base64 encoded tenand id]

You can then save it in Kubernetes:

$ kubectl create -f secret.yaml

Configuration

$ python main.py [options]

• --container-service-name: Name of ACS cluster.
• --resource-group: Name of the resource group containing the cluster
• --template-file: [acs-engine only] Full path to the ARM template file.
• --template-file-url: [acs-engine only] URL to the ARM template file.
• --parameters-file: [acs-engine only] Full path to the ARM parameters file.
• --parameters-file-url: [acs-engine only] URL to the ARM parameters file.
• --kubeconfig: Path to kubeconfig YAML file. Leave blank if running in Kubernetes to use service account.
• --idle-threshold: This defines the maximum duration (in seconds) for an instance to be kept idle.
• --service-principal-app-id: Azure service principal id. Can also be specified in environment variable AZURE_SP_APP_ID
• --service-principal-secret: Azure service principal secret. Can also be specified in environment variable AZURE_SP_SECRET
• --service-principal-tenant-id: Azure service princiap tenant id. Can also be specified in environment variable AZURE_SP_TENANT_ID
• --instance-init-time: Maximum duration (in seconds) after an instance is launched before being considered unhealthy (running in EC2 but not joining the Kubernetes cluster)
• --sleep: Time (in seconds) to sleep between scaling loops (to be careful not to run into AWS API limits)
• --slack-hook: Optional Slack incoming webhook for scaling notifications
• --dry-run: Flag for testing so resources aren't actually modified. Actions will instead be logged only.
• -v: Sets the verbosity. Specify multiple times for more log output, e.g. -vvv
• --debug: Do not catch errors. Explicitly crash.

Autoscaling ACS

Pass the name of your container service to --container-service-name.

Autoscaling acs-engine

Pass the template (azuredeploy.json) and parameter (azuredeploy.parameters.json) files that you generated with acs-engine to the autoscaler through --template-file and --parameters-file or --template-file-url and --parameters-file-url --container-service-name should be left empty as it is reserved for ACS.

Run in-cluster

scaling-controller.yaml has an example Replication Controller that will set up Kubernetes to always run exactly one copy of the autoscaler. To create the Replication Controller:

$ kubectl create -f scaling-controller.yaml

You should then be able to inspect the pod's status and logs:

$ kubectl get pods --namespace system -l app=autoscaler
NAME               READY     STATUS    RESTARTS   AGE
autoscaler-opnax   1/1       Running   0          3s

$ kubectl logs autoscaler-opnax --namespace system
2016-08-25 20:36:45,985 - autoscaler.cluster - DEBUG - Using kube service account
2016-08-25 20:36:45,987 - autoscaler.cluster - INFO - ++++++++++++++ Running Scaling Loop ++++++++++++++++
2016-08-25 20:37:04,221 - autoscaler.cluster - INFO - ++++++++++++++ Scaling Up Begins ++++++++++++++++
...

Running locally

$ docker build -t autoscaler .
$ ./devenvh.sh
$ python main.py --resource-group k8s --container-service-name containerservice-k8s --service-principal-app-id 'XXXXXXXXX' --service-principal-secret 'XXXXXXXXXXXXX' service-principal-tenant-id 'XXXXXX' --dry-run -vvv --kubeconfig /root/.kube/config