feat: add RaySepc to ResourceRuntimeSpec, and add ResourceRuntime to PersistentResource (#4470)

* feat: add RaySepc to ResourceRuntimeSpec, and add ResourceRuntime to PersistentResource

PiperOrigin-RevId: 551874408

Source-Link: googleapis/googleapis@4d230dd

Source-Link: googleapis/googleapis-gen@9e603a7
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Co-authored-by: Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>
Co-authored-by: Alexander Fenster <fenster@google.com>

Author: gcf-owl-bot[bot]

packages/google-cloud-aiplatform/README.md

@@ -561,7 +561,7 @@ also contains samples.
 
 ## Supported Node.js Versions
 
-Our client libraries follow the [Node.js release schedule](https://nodejs.org/en/about/releases/).
+Our client libraries follow the [Node.js release schedule](https://github.com/nodejs/release#release-schedule).
 Libraries are compatible with all current _active_ and _maintenance_ versions of
 Node.js.
 If you are using an end-of-life version of Node.js, we recommend that you update

packages/google-cloud-aiplatform/protos/google/cloud/aiplatform/v1beta1/persistent_resource.proto

@@ -62,8 +62,8 @@ message PersistentResource {
     ERROR = 5;
   }
 
-  // Output only. Resource name of a PersistentResource.
-  string name = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
+  // Immutable. Resource name of a PersistentResource.
+  string name = 1 [(google.api.field_behavior) = IMMUTABLE];
 
   // Optional. The display name of the PersistentResource.
   // The name can be up to 128 characters long and can consist of any UTF-8
@@ -134,6 +134,10 @@ message PersistentResource {
   ResourceRuntimeSpec resource_runtime_spec = 13
       [(google.api.field_behavior) = OPTIONAL];
 
+  // Output only. Runtime information of the Persistent Resource.
+  ResourceRuntime resource_runtime = 14
+      [(google.api.field_behavior) = OUTPUT_ONLY];
+
   // Optional. A list of names for the reserved ip ranges under the VPC network
   // that can be used for this persistent resource.
   //
@@ -200,6 +204,36 @@ message ResourceRuntimeSpec {
   // Optional. Configure the use of workload identity on the PersistentResource
   ServiceAccountSpec service_account_spec = 2
       [(google.api.field_behavior) = OPTIONAL];
+
+  // Ray cluster configuration.
+  // Required when creating a dedicated RayCluster on the PersistentResource.
+  RaySpec ray_spec = 1 [(google.api.field_behavior) = OPTIONAL];
+}
+
+// Configuration information for the Ray cluster.
+// For experimental launch, Ray cluster creation and Persistent
+// cluster creation are 1:1 mapping: We will provision all the nodes within the
+// Persistent cluster as Ray nodes.
+message RaySpec {
+  // Optional. Default image for user to choose a preferred ML framework(e.g.
+  // tensorflow or Pytorch) by choosing from Vertex prebuild
+  // images(https://cloud.google.com/vertex-ai/docs/training/pre-built-containers).
+  // Either this or the resource_pool_images is required. Use this field if
+  // you need all the resource pools to have the same Ray image, Otherwise, use
+  // the {@code resource_pool_images} field.
+  string image_uri = 1 [(google.api.field_behavior) = OPTIONAL];
+}
+
+// Persistent Cluster runtime information as output
+message ResourceRuntime {
+  // Output only. URIs for user to connect to the Cluster.
+  // Example:
+  // {
+  //   "RAY_HEAD_NODE_INTERNAL_IP": "head-node-IP:10001"
+  //   "RAY_DASHBOARD_URI": "ray-dashboard-address:8888"
+  // }
+  map<string, string> access_uris = 1
+      [(google.api.field_behavior) = OUTPUT_ONLY];
 }
 
 // Configuration for the use of custom service account to run the workloads.