How to scale operationalization on your ACS cluster
Operationalized models, deployed on ACS clusters on which Kubernetes has been installed, can be scaled in two ways:
- You can scale the number of agent nodes in the cluster.
- You can scale the number of Kubernetes pods.
For information on scaling the number of nodes in the cluster, see Scale agent nodes in a Container Service cluster.
Using the -k parameter when setting up the operationalization environment, configures one pod and installs the Kubernetes CLI. You can use Azure Machine Learning CLI or the Kubernetes dashboard to scale the number of pods assigned to the cluster.
To scale the number pods in the Kubernetes service, use the az ml scale command.
az ml scale realtime -n <service name> -z <number of pods>
For more information on Kubernetes pods, see the Kubernetes Pods documentation.
The command to start the Kubernetes dashboard web interface is the same on both Windows and Linux:
kubectl proxy
On Windows, the Kubernetes install location is not automatically added to the path. You must first navigate the install folder:
c:\users\<user name>\bin
Once you run the command, you should see the following informational message:
Starting to serve on 127.0.0.1:8001
If the port is already in use, you see a message similar to the following example:
F0612 21:49:22.459111 59621 proxy.go:137] listen tcp 127.0.0.1:8001: bind: address already in use
You can specify an alternate port number using the --port parameter.
kubectl proxy --port=8010
Starting to serve on 127.0.0.1:8010
Once you have started the dashboard server, open a browser and enter the following URL:
127.0.0.1:<port number>/ui
From the dashboard main screen, click Deployments on the left navigation bar. If the navigation pane does not display, select this icon 
on the upper left.
Locate the deployment to modify and click this icon 
on the right and then click View/edi YAML.
On the Edit deployment screen, locate the spec node and modify the replicas value and click Update.