From d699046183b393723b9e6394a28a53264d8fb8aa Mon Sep 17 00:00:00 2001 From: Sherin Date: Fri, 27 Dec 2024 13:36:06 +0200 Subject: [PATCH 1/3] Copied from DOC 360 --- .../workloads/assets/credentials.md | 7 +- .../workloads/assets/datasources.md | 64 ++++++++++++++++++- 2 files changed, 67 insertions(+), 4 deletions(-) diff --git a/docs/platform-admin/workloads/assets/credentials.md b/docs/platform-admin/workloads/assets/credentials.md index e3276e72ca..74548a075d 100644 --- a/docs/platform-admin/workloads/assets/credentials.md +++ b/docs/platform-admin/workloads/assets/credentials.md @@ -22,9 +22,11 @@ The Credentials table comprises the following columns: | Description | A description of the credentials | | Type | The type of credentials, e.g., Docker registry | | Status | The different lifecycle phases and representation of the credentials’ condition | +| Scope | The [scope](./overview.md#asset-scope) of this compute resource within the organizational tree. Click the name of the scope to view the organizational tree diagram | +| Kubernetes name | The unique name of the credentials Kubernetes name as it appears in the cluster | +| Environment(s) | The environment(s) that are associated with the credentials | | Data source(s) | The private data source(s) that are accessed using the credentials | | Created by | The user who created the credentials | -| Scope | The [scope](./overview.md#asset-scope) of this compute resource within the organizational treeClick the name of the scope to view the organizational tree diagram | | Creation time | The timestamp of when the credentials were created | | Cluster | The cluster with which the credentials are associated | @@ -154,7 +156,7 @@ To delete a credential: 1. Select the credential you want to delete 2. Click __DELETE__ -3. In the dialog, click __DELETE__ to confirm the deletion +3. In the dialog, click __DELETE__ to confirm !!! Note Credentials cannot be deleted if they are being used by a workload and template. @@ -173,6 +175,7 @@ To use the secret directly from within the container, you can choose between the 1. Get the secret mounted to the file system by using the [Generic secret](./datasources.md#secret) data source 2. Get the secret as an environment variable injected into the container. There are two equivalent ways to inject the environment variable. + a. By adding it to the Environment asset. b. By adding it ad-hoc as part of the workload. diff --git a/docs/platform-admin/workloads/assets/datasources.md b/docs/platform-admin/workloads/assets/datasources.md index 2d74cb6cdd..94934fb81d 100644 --- a/docs/platform-admin/workloads/assets/datasources.md +++ b/docs/platform-admin/workloads/assets/datasources.md @@ -22,6 +22,7 @@ The data sources table comprises the following columns: | Type | The type of data source connected – e.g., S3 bucket, PVC, or others | | Status | The different lifecycle phases and representation of the data source condition | | Scope | The [scope](./overview.md#asset-scope) of the data source within the organizational tree. Click the scope name to view the organizational tree diagram | +| Kubernetes name | The unique name of the data sources Kubernetes name as it appears in the cluster | | Workload(s) | The list of existing workloads that use the data source | | Template(s) | The list of workload templates that use the data source | | Created by | The user who created the data source | @@ -36,7 +37,7 @@ The following table describes the data sources' condition and whether they were | --- | --- | | No issues found | No issues were found while creating the data source | | Issues found | Issues were found while propagating the data source credentials | -| Issues found | The cluster could not be accessed | +| Issues found | The data source couldn’t be created at the cluster | | Creating… | The data source is being created | | No status / “-” | When the data source’s scope is an account, the current version of the cluster is not up to date, or the asset is not a cluster-syncing entity, the status can’t be displayed | @@ -75,7 +76,7 @@ A Network File System ([NFS](https://kubernetes.io/docs/concepts/storage/volumes ### PVC -A Persistent Volume Claim ([PVC](https://kubernetes.io/docs/concepts/storage/persistent-volumes/){target=_blank}) is a Kubernetes concept used for managing storage in the cluster, which can be provisioned by an administrator or dynamically by Kubernetes using a StorageClass. PVCs allow users to request specific sizes and access modes (read/write once, read-only many). At Run:ai, a PVC-type data source is an abstraction that is mapped directly to a Kubernetes PVC. By leveraging PVCs as data sources, Run:ai enables access to persistent storage for workloads, ensuring that data remains consistent and accessible across various scopes and workloads, beyond the lifecycle of individual pods. This ensures that data generated by AI workloads is not lost when pods are rescheduled or updated, providing a seamless and efficient storage solution that can handle the large datasets typically associated with AI projects. +A Persistent Volume Claim ([PVC](https://kubernetes.io/docs/concepts/storage/persistent-volumes/){target=_blank}) is a Kubernetes concept used for managing storage in the cluster, which can be provisioned by an administrator or dynamically by Kubernetes using a StorageClass. PVCs allow users to request specific sizes and access modes (read/write once, read-only many). Run:ai ensures that data remains consistent and accessible across various scopes and workloads, beyond the lifecycle of individual pods, which is efficient while working with large datasets typically associated with AI projects. 1. Select the __cluster__ under which to create this data source 2. Select a [scope](./overview.md#asset-scope) @@ -97,6 +98,8 @@ A Persistent Volume Claim ([PVC](https://kubernetes.io/docs/concepts/storage/per * __Read-write by many nodes__ - The volume can be mounted as read-write by many nodes. 8. Set the __claim size__ and its __units__ 9. Select the __volume mode__ + * File system (default) - allows the volume to be mounted as a filesystem, enabling the usage of directories and files. + * Block - exposes the volume as a block storage, which can be formatted or used by applications directly without a filesystem. 10. Set the data target location * __container path__ 11. Optional: __Prevent data modification__ - When enabled, the data will be mounted with read-only permission. @@ -214,6 +217,63 @@ To delete a data source: !!! Note It is not possible to delete an environment being used by an existing workload or template. +## Creating PVCs in advance + +Add PVCs in advance to be used when creating a PVC-type data source via the Run:ai UI. + +The actions taken by the admin are based on the scope (cluster, department or project) that the admin wants for data source of type PVC. Follow the steps below for each required scope: + +### Cluster scope + +1. Locate the PVC in the Run:ai namespace (runai) +2. Provide Run:ai with visibility and authorization to share the PVC to your selected scope by implementing the following label: run.ai/cluster-wide: "true” + +!!! Note + This step is also relevant for creating the data source of type PVC via API + +The PVC is now displayed for that scope in the list of existing PVCs. + +### Department scope + +1. Locate the PVC in the Run:ai namespace (runai) +2. To authorize Run:ai to use the PVC, label it: run.ai/department: "id" + +The PVC is now displayed for that scope in the list of existing PVCs. + +### Project scope +Locate the PVC in the project’s namespace + +The PVC is now displayed for that scope in the list of existing PVCs. + + +## Creating ConfigMaps in advance + +Add ConfigMaps in advance to be used when creating a ConfigMap-type data source via the Run:ai UI. + +### Cluster scope + +1. Locate the ConfigMap in the Run:ai namespace (runai) +2. To authorize Run:ai to use the ConfigMap, label it: run.ai/cluster-wide: "true” +3. The ConfigMap must have a label of run.ai/resource: + +The ConfigMap is now displayed for that scope in the list of existing ConfigMaps. + + +### Department scope + +1. Locate the ConfigMap in the Run:ai namespace (runai) +2. To authorize Run:ai to use the ConfigMap, label it: run.ai/department: "" +3. The ConfigMap must have a label of run.ai/resource: + +The ConfigMap is now displayed for that scope in the list of existing ConfigMaps. + +### Project scope + +1. Locate the ConfigMap in the project’s namespace +2. The ConfigMap must have a label of run.ai/resource: + +The ConfigMap is now displayed for that scope in the list of existing ConfigMaps. + ## Using API To view the available actions, go to the [Data sources](https://app.run.ai/api/docs#tag/Datasources) API reference. \ No newline at end of file From 20522edf93109051ca4dcfdc7794f88b1dc75d53 Mon Sep 17 00:00:00 2001 From: Sherin Date: Mon, 30 Dec 2024 19:37:09 +0200 Subject: [PATCH 2/3] Updated and added screenshots --- .../workloads/assets/datasources.md | 55 ------------------ .../assets/img/credentials-table.png | Bin 177112 -> 198403 bytes .../assets/img/data-source-table.png | Bin 247840 -> 295625 bytes 3 files changed, 55 deletions(-) diff --git a/docs/platform-admin/workloads/assets/datasources.md b/docs/platform-admin/workloads/assets/datasources.md index 94934fb81d..1a7c34b516 100644 --- a/docs/platform-admin/workloads/assets/datasources.md +++ b/docs/platform-admin/workloads/assets/datasources.md @@ -217,62 +217,7 @@ To delete a data source: !!! Note It is not possible to delete an environment being used by an existing workload or template. -## Creating PVCs in advance -Add PVCs in advance to be used when creating a PVC-type data source via the Run:ai UI. - -The actions taken by the admin are based on the scope (cluster, department or project) that the admin wants for data source of type PVC. Follow the steps below for each required scope: - -### Cluster scope - -1. Locate the PVC in the Run:ai namespace (runai) -2. Provide Run:ai with visibility and authorization to share the PVC to your selected scope by implementing the following label: run.ai/cluster-wide: "true” - -!!! Note - This step is also relevant for creating the data source of type PVC via API - -The PVC is now displayed for that scope in the list of existing PVCs. - -### Department scope - -1. Locate the PVC in the Run:ai namespace (runai) -2. To authorize Run:ai to use the PVC, label it: run.ai/department: "id" - -The PVC is now displayed for that scope in the list of existing PVCs. - -### Project scope -Locate the PVC in the project’s namespace - -The PVC is now displayed for that scope in the list of existing PVCs. - - -## Creating ConfigMaps in advance - -Add ConfigMaps in advance to be used when creating a ConfigMap-type data source via the Run:ai UI. - -### Cluster scope - -1. Locate the ConfigMap in the Run:ai namespace (runai) -2. To authorize Run:ai to use the ConfigMap, label it: run.ai/cluster-wide: "true” -3. The ConfigMap must have a label of run.ai/resource: - -The ConfigMap is now displayed for that scope in the list of existing ConfigMaps. - - -### Department scope - -1. Locate the ConfigMap in the Run:ai namespace (runai) -2. To authorize Run:ai to use the ConfigMap, label it: run.ai/department: "" -3. The ConfigMap must have a label of run.ai/resource: - -The ConfigMap is now displayed for that scope in the list of existing ConfigMaps. - -### Project scope - -1. Locate the ConfigMap in the project’s namespace -2. 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docs/platform-admin/workloads/assets/datasources.md | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/docs/platform-admin/workloads/assets/credentials.md b/docs/platform-admin/workloads/assets/credentials.md index 74548a075d..c72a6cadd9 100644 --- a/docs/platform-admin/workloads/assets/credentials.md +++ b/docs/platform-admin/workloads/assets/credentials.md @@ -8,7 +8,7 @@ Essentially, credentials enable AI practitioners to access relevant protected re ## Credentials table -The Credentials table can be found under __Credentials__ in the Run:ai User interface. +The Credentials table can be found under __Workload manager__ in the Run:ai User interface. The Credentials table provides a list of all the credentials defined in the platform and allows you to manage them. @@ -49,6 +49,7 @@ The following table describes the credentials’ condition and whether they were * Search - Click SEARCH and type the value to search by * Sort - Click each column header to sort by * Column selection - Click COLUMNS and select the columns to display in the table +* Download table - Click MORE and then click ‘Download as CSV’. Export to CSV is limited to 20,000 rows. * Refresh - Click REFRESH to update the table with the latest data ## Adding new credentials diff --git a/docs/platform-admin/workloads/assets/datasources.md b/docs/platform-admin/workloads/assets/datasources.md index 1a7c34b516..21f90ac386 100644 --- a/docs/platform-admin/workloads/assets/datasources.md +++ b/docs/platform-admin/workloads/assets/datasources.md @@ -7,7 +7,7 @@ This configuration simplifies the mapping of the data into the workload’s file ## Data sources table -The data sources table can be found under __Data sources__ in the Run:ai platform. +The data sources table can be found under __Workload manager__ in the Run:ai platform. The data sources table provides a list of all the data sources defined in the platform and allows you to manage them.