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Upgrade a directly connected Azure Arc data controller using the CLI

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This article describes how to upgrade a directly connected Azure Arc-enabled data controller using the Azure CLI (az).

During a data controller upgrade, portions of the data control plane such as Custom Resource Definitions (CRDs) and containers may be upgraded. An upgrade of the data controller won't cause downtime for the data services (SQL Managed Instance or PostgreSQL server).

Prerequisites

You'll need a directly connected data controller with the imageTag v1.0.0_2021-07-30 or later.

To check the version, run:

kubectl get datacontrollers -n <namespace> -o custom-columns=BUILD:.spec.docker.imageTag

Install tools

Before you can proceed with the tasks in this article, you need to install:

Examples in this article use angle brackets < ... > to identify values that you need to replace before you run the script. Replace the brackets and the values inside the brackets.

The arcdata extension version and the image version are related. Check that you have the correct arcdata extension version that corresponds to the image version you want to upgrade to in the Version log.

View available images and chose a version

Pull the list of available images for the data controller with the following command:

az arcdata dc list-upgrades --k8s-namespace <namespace>

The command above returns output like the following example:

Found 2 valid versions.  The current datacontroller version is v1.0.0_2021-07-30.
v1.1.0_2021-11-02
v1.0.0_2021-07-30

Upgrade data controller

This section shows how to upgrade a directly connected data controller.

Note

Some of the data services tiers and modes are generally available and some are in preview. If you install GA and preview services on the same data controller, you can't upgrade in place. To upgrade, delete all non-GA database instances. You can find the list of generally available and preview services in the Release Notes.

For supported upgrade paths, see Upgrade Azure Arc-enabled data services.

Authenticate

You'll need to connect and authenticate to a Kubernetes cluster and have an existing Kubernetes context selected prior to beginning the upgrade of the Azure Arc data controller.

kubectl config use-context <Kubernetes cluster name>

Upgrade data controller

You can perform a dry run first. The dry run validates the registry exists, the version schema, and the private repository authorization token (if used). To perform a dry run, use the --dry-run parameter in the az arcdata dc upgrade command. For example:

az arcdata dc upgrade --resource-group <resource group> --name <data controller name> --desired-version <version> --dry-run [--no-wait]

The output for the preceding command is:

Preparing to upgrade dc arcdc in namespace arc to version <version-tag>.
****Dry Run****
Arcdata Control Plane would be upgraded to: <version-tag>

After the Arc data controller extension has been upgraded, run the az arcdata dc upgrade command, specifying the image tag with --desired-version.

az arcdata dc upgrade --resource-group <resource group> --name <data controller name> --desired-version <version> [--no-wait]

Example:

az arcdata dc upgrade --resource-group rg-arcds --name dc01 --desired-version v1.7.0_2022-05-24 [--no-wait]

Monitor the upgrade status

You can monitor the progress of the upgrade with CLI.

CLI

 az arcdata dc status show --resource-group <resource group>

The upgrade is a two-part process. First the controller is upgraded, then the monitoring stack is upgraded. When the upgrade is complete, the output will be:

Ready

Troubleshooting

When the desired version is set to a specific version, the bootstrapper job will attempt to upgrade to that version until it succeeds. If the upgrade is successful, the RunningVersion property of the spec is updated to the new version. Upgrades could fail for scenarios such as an incorrect image tag, unable to connect to registry or repository, insufficient CPU or memory allocated to the containers, or insufficient storage.

  1. Run the below command to see if any of the pods show an Error status or have high number of restarts:

    kubectl get pods --namespace <namespace>

  2. To look at Events to see if there is an error, run

    kubectl describe pod <pod name> --namespace <namespace>

  3. To get a list of the containers in the pods, run

    kubectl get pods <pod name> --namespace <namespace> -o jsonpath='{.spec.containers[*].name}*'

  4. To get the logs for a container, run

    kubectl logs <pod name> <container name> --namespace <namespace>

To view common errors and how to troubleshoot them go to Troubleshooting resources.