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add troubleshooting for upgrading (#181)
* add troubleshooting for upgrading * update * update
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docs/en/upgrade/upgrade-from-previous-version.mdx

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---
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export const prevVersion = '1.5'
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export const curVer = '2.2'
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export const curVer = '2.3'
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# Upgrade Alauda AI
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### Upgrading Cluster Plugins
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:::info
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This step is **only required if you have deployed** any of the following cluster plugins: **Alauda AI Workbench**, **Alauda AI MLflow**, or **Alauda AI Volcano**. If you have not deployed any of these plugins, you can skip this step.
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This step is **only required if you have deployed** any of the following cluster plugins: **Alauda AI Workbench**, **MLflow**, or **Volcano**. If you have not deployed any of these plugins, you can skip this step.
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For more information about cluster plugins, refer to <ExternalSiteLink name="acp" href="extend/index.html" children="Alauda Container Platform - Extend" />.
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:::
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The procedure to upgrade cluster plugins involves uploading new version packages and then upgrading them from the Web Console. The following plugins require upgrading:
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- Alauda AI Workbench
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- Alauda AI MLflow
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- Alauda AI Volcano
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- MLflow
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- Volcano
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#### Uploading Cluster Plugins
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Navigate to **Administrator > Marketplace > Upload Packages** and switch to the **Cluster Plugin** tab. Locate each uploaded plugin to verify that the new version is displayed.
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#### Troubleshooting
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##### New version not visible after upload (ACP 4.0.x)
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On **Alauda Container Platform (ACP) 4.0.x**, the Web Console may fail to show a newly uploaded cluster plugin version even though the upload succeeded. This behavior is a known **ACP** limitation; it has been addressed in newer **ACP** releases.
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If the new version does not appear after waiting for synchronization, the following workaround can be used to set the target version on the corresponding `ModuleInfo` and trigger the plugin upgrade directly.
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The following `kubectl` commands must run on the **global** cluster.
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| Plugin (UI / product name) | Plugin Identifier |
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|:---------------------------|:------------------|
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| Alauda AI Workbench | `workbench` |
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| Volcano | `volcano` |
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| MLflow | `mlflow` |
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| Kubeflow Training Operator | `kftraining` |
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1. Resolve the `ModuleInfo` resource name. Replace `<Cluster Name>` with the target cluster name. For `<Plugin Identifier>`, use the value in the **Plugin Identifier** column of the table above:
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```bash
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kubectl get moduleinfoes \
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-l cpaas.io/cluster-name=<Cluster Name>,cpaas.io/module-name=<Plugin Identifier> \
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-o jsonpath='{.items[*].metadata.name}'
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```
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2. Get `<New Version>` from the `ModulePlugin` status, using the same `<Plugin Identifier>` value as in step 1 (see the table above):
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```bash
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kubectl get moduleplugins <Plugin Identifier> -o jsonpath='{.status.latestVersion}'
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```
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3. Patch the `ModuleInfo`. Replace `<ModuleInfo Name>` with the name from step 1 and `<New Version>` with the value from step 2:
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```bash
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kubectl patch moduleinfoes <ModuleInfo Name> --type merge -p '{"spec":{"version":"<New Version>"}}'
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```
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:::warning
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The patch takes effect immediately and **directly triggers the cluster plugin upgrade** to `<New Version>`, bypassing the Web Console upgrade action. Verify the version string before running the command.
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:::
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#### Upgrading from Web Console
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1. Navigate to **Administrator > Clusters > Clusters**.
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In the **Administrator** view, navigate to **Marketplace > Cluster Plugins** and confirm that the following cluster plugins show `Installed` status with the new version:
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- Alauda AI Workbench (if deployed)
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- Alauda AI MLflow (if deployed)
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- Alauda AI Volcano (if deployed)
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- MLflow (if deployed)
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- Volcano (if deployed)
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</Steps>
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