--- title: "Tensorboards" slug: "ai-mlxp-ptensorboards" updated: 2026-09-17T09:37:44Z published: 2026-09-17T09:37:44Z canonical: "guide.ncloud-docs.com/ai-mlxp-ptensorboards" stale: true --- > ## Documentation Index > Fetch the complete documentation index at: https://guide.ncloud-docs.com/llms.txt > Use this file to discover all available pages before exploring further. # Tensorboards Available in VPC This section describes the Tensorboards interface. Use Tensorboards to create and delete Tensorboards or access active Tensorboards to monitor training processes. ## Tensorboards The Tensorboards interface includes the following components: ![mlxp_console_tensorboards01_ko](https://cdn.document360.io/6998976f-9d95-4df8-b847-d375892b92c2/Images/Documentation/mlxp_console_tensorboards01_en.png?sv=2026-02-06&spr=https&st=2026-11-01T21%3A16%3A05Z&se=2026-11-01T22%3A16%3A05Z&sr=c&sp=r&sig=mPOxpxBiXmZ3H%2Byj7eRRhkhPd5YWMQzlA6nVgobO1EE%3D) | Component | Description | | --- | --- | | ① Menu name | Current menu name. | | ② Basic features | Add or delete a Tensorboard. | | ③ Tensorboard list | View active Tensorboards and their information. | ## View Tensorboards list The Tensorboards list includes the following information: - **Status**: Tensorboard status - **Name**: Tensorboard name - **Created At**: Initial creation date and time. - **LogsPath**: Storage path for logs - **CONNECT**: Click to open the Tensorboard in a new window ## Create a Tensorboard To create a new Tensorboard: Note - When using Object Storage or Ncloud Storage, you must create a Secret and PodDefault for each storage type in advance. For details, see [Configure integration settings by storage type](/docs/en/ai-mlxp-ptensorboards#%EC%8A%A4%ED%86%A0%EB%A6%AC%EC%A7%80%EC%9C%A0%ED%98%95%EB%B3%84%EC%97%B0%EB%8F%99%EC%84%A4%EC%A0%95). 1. Click **[Create]**. 2. When the New Tensorboard popup appears, enter a Tensorboard name. - Enter 3-61 characters using lowercase letters (a-z), numbers (0-9), and hyphens (-). - It must start with an English letter and end with an English letter or a number. - Duplicate names are not allowed. - Must be unique across Tensorboards and existing Notebooks. 3. Verify the Project Namespace. 4. Select a storage type for log storage. - **Object Storage/Ncloud Storage**: Use your Object Storage or Ncloud Storage - **Volumes**: Use a volume you created 5. Enter the Mount Path for the selected storage type. Note - If you select Object Storage or Ncloud Storage, enter the endpoint in S3 REST API format: `s3://버킷명/경로`. - Do not enter the full path including the endpoint. 1. Select the configuration for the chosen Storage Type. - If you have chosen Object Storage or Ncloud Storage, select the PodDefault created in advance. - If you have chosen Volumes, select the GPU Zone assigned to your Workspace. For GPU Zone information, see [View available GPU Zones](/docs/en/ai-mlxp-gpuresource#%EC%82%AC%EC%9A%A9%EA%B0%80%EB%8A%A5%ED%95%9CGPUZone%EC%A0%95%EB%B3%B4%EC%A1%B0%ED%9A%8C). 2. Click **[Create]**. ## Delete a Tensorboard You can delete a Tensorboard as follows: 1. Select the Tensorboard you want to delete and click **[Delete]**. 2. When the **Delete Tensorboard** popup appears, enter the Tensorboard name and click **[Delete]**. 3. Verify that the selected Tensorboard has been removed from the list. ## Configure integration settings by storage type You can configure Object Storage and Ncloud Storage on NAVER Cloud Platform for integration with Tensorboard. After creating a Tensorboard, follow the steps below in order. ### 1. Check settings by storage type Object Storage and Ncloud Storage both provide S3-compatible interfaces and can be integrated with Tensorboard. Because endpoint and region settings differ by storage type, refer to the table below when configuring them. Here are the differences in settings by storage type: | Item | Object Storage | Ncloud Storage | | --- | --- | --- | | Endpoint | https://kr.object.ncloudstorage.com/ | https://kr.ncloudstorage.com/ | | Region setting required | Required (kr-standard) | - | | S3-compatible interface support | O | O | Note For more information about Object Storage and Ncloud Storage, see [Object Storage user guide](/docs/en/storage-storage-6-1) and [Ncloud Storage user guide](/docs/en/ncloudstorage-overview). ### 2. Create a Secret Create an appropriate Credential Secret for the storage type you want to use. #### Object Storage Note You can view and create credential information in the NAVER Cloud Platform console. For details, see [Create API authentication keys and integrate with Amazon S3](/docs/en/objectstorage-start#api-%EC%9D%B8%EC%A6%9D%ED%82%A4-%EC%83%9D%EC%84%B1-%EB%B0%8F-amazon-s3-%EC%97%B0%EB%8F%99). ``` kubectl create secret generic ncp-object-storage-credentials \ -n \ --from-literal=AWS_ACCESS_KEY_ID= \ --from-literal=AWS_SECRET_ACCESS_KEY= ``` #### Ncloud Storage Note You can view and create credential information in the NAVER Cloud Platform console. For details, see [Create API authentication keys](/docs/en/ncloudstorage-start#api-%EC%9D%B8%EC%A6%9D%ED%82%A4-%EC%83%9D%EC%84%B1). ``` kubectl create secret generic ncp-ncloud-storage-credentials \ -n \ --from-literal=AWS_ACCESS_KEY_ID= \ --from-literal=AWS_SECRET_ACCESS_KEY= ``` ### 3. Create a PodDefault Create an appropriate PodDefault for the storage type you want to use. #### Object Storage For Object Storage, the region setting is required. Set it to kr-standard. ``` apiVersion: kubeflow.org/v1alpha1 kind: PodDefault metadata: name: tensorboard-ncp-object-storage-config spec: desc: NCP Object Storage config for TensorBoard selector: matchLabels: tb-ncp-object-storage-config: "true" env: - name: AWS_ACCESS_KEY_ID valueFrom: secretKeyRef: name: ncp-object-storage-credentials key: AWS_ACCESS_KEY_ID - name: AWS_SECRET_ACCESS_KEY valueFrom: secretKeyRef: name: ncp-object-storage-credentials key: AWS_SECRET_ACCESS_KEY - name: AWS_REGION value: kr-standard - name: S3_ENDPOINT value: https://kr.object.ncloudstorage.com ``` #### Ncloud Storage ``` apiVersion: kubeflow.org/v1alpha1 kind: PodDefault metadata: name: tensorboard-ncp-ncloud-storage-config spec: desc: NCP NCloud Storage config for TensorBoard selector: matchLabels: tb-ncp-ncloud-storage-config: "true" env: - name: AWS_ACCESS_KEY_ID valueFrom: secretKeyRef: name: ncp-ncloud-storage-credentials key: AWS_ACCESS_KEY_ID - name: AWS_SECRET_ACCESS_KEY valueFrom: secretKeyRef: name: ncp-ncloud-storage-credentials key: AWS_SECRET_ACCESS_KEY - name: S3_ENDPOINT value: https://kr.ncloudstorage.com ```