feat: support PSC-Interface in Ray on Vertex

feat: support disable Cloud logging in Ray on Vertex

PiperOrigin-RevId: 661019434

Author: yinghsienwu

google/cloud/aiplatform/vertex_ray/__init__.py

@@ -38,6 +38,7 @@
 from google.cloud.aiplatform.vertex_ray.util.resources import (
     Resources,
     NodeImages,
+    PscIConfig,
 )
 
 from google.cloud.aiplatform.vertex_ray.dashboard_sdk import (
@@ -61,4 +62,5 @@
     "update_ray_cluster",
     "Resources",
     "NodeImages",
+    "PscIConfig",
 )

google/cloud/aiplatform/vertex_ray/cluster_init.py

@@ -23,17 +23,20 @@
 from google.cloud.aiplatform import initializer
 from google.cloud.aiplatform import utils
 from google.cloud.aiplatform.utils import resource_manager_utils
-from google.cloud.aiplatform_v1.types import persistent_resource_service
+from google.cloud.aiplatform_v1beta1.types import persistent_resource_service
 
-from google.cloud.aiplatform_v1.types.persistent_resource import (
+from google.cloud.aiplatform_v1beta1.types.persistent_resource import (
     PersistentResource,
+    RayLogsSpec,
     RaySpec,
     RayMetricSpec,
     ResourcePool,
     ResourceRuntimeSpec,
     ServiceAccountSpec,
 )
-
+from google.cloud.aiplatform_v1beta1.types.service_networking import (
+    PscInterfaceConfig,
+)
 from google.cloud.aiplatform.vertex_ray.util import (
     _gapic_utils,
     _validation_utils,
@@ -56,6 +59,8 @@ def create_ray_cluster(
     worker_node_types: Optional[List[resources.Resources]] = [resources.Resources()],
     custom_images: Optional[resources.NodeImages] = None,
     enable_metrics_collection: Optional[bool] = True,
+    enable_logging: Optional[bool] = True,
+    psc_interface_config: Optional[resources.PscIConfig] = None,
     labels: Optional[Dict[str, str]] = None,
 ) -> str:
     """Create a ray cluster on the Vertex AI.
@@ -119,6 +124,8 @@ def create_ray_cluster(
             head/worker_node_type(s). Note that configuring `Resources.custom_image`
             will override `custom_images` here. Allowlist only.
         enable_metrics_collection: Enable Ray metrics collection for visualization.
+        enable_logging: Enable exporting Ray logs to Cloud Logging.
+        psc_interface_config: PSC-I config.
         labels:
             The labels with user-defined metadata to organize Ray cluster.
 
@@ -258,10 +265,17 @@ def create_ray_cluster(
             i += 1
 
     resource_pools = [resource_pool_0] + worker_pools
-    disabled = not enable_metrics_collection
-    ray_metric_spec = RayMetricSpec(disabled=disabled)
+
+    metrics_collection_disabled = not enable_metrics_collection
+    ray_metric_spec = RayMetricSpec(disabled=metrics_collection_disabled)
+
+    logging_disabled = not enable_logging
+    ray_logs_spec = RayLogsSpec(disabled=logging_disabled)
+
     ray_spec = RaySpec(
-        resource_pool_images=resource_pool_images, ray_metric_spec=ray_metric_spec
+        resource_pool_images=resource_pool_images,
+        ray_metric_spec=ray_metric_spec,
+        ray_logs_spec=ray_logs_spec,
     )
     if service_account:
         service_account_spec = ServiceAccountSpec(
@@ -274,11 +288,18 @@ def create_ray_cluster(
         )
     else:
         resource_runtime_spec = ResourceRuntimeSpec(ray_spec=ray_spec)
+    if psc_interface_config:
+        gapic_psc_interface_config = PscInterfaceConfig(
+            network_attachment=psc_interface_config.network_attachment,
+        )
+    else:
+        gapic_psc_interface_config = None
     persistent_resource = PersistentResource(
         resource_pools=resource_pools,
         network=network,
         labels=labels,
         resource_runtime_spec=resource_runtime_spec,
+        psc_interface_config=gapic_psc_interface_config,
     )
 
     location = initializer.global_config.location

google/cloud/aiplatform/vertex_ray/util/_gapic_utils.py

@@ -28,12 +28,13 @@
 from google.cloud.aiplatform.vertex_ray.util import _validation_utils
 from google.cloud.aiplatform.vertex_ray.util.resources import (
     Cluster,
+    PscIConfig,
     Resources,
 )
-from google.cloud.aiplatform_v1.types.persistent_resource import (
+from google.cloud.aiplatform_v1beta1.types.persistent_resource import (
     PersistentResource,
 )
-from google.cloud.aiplatform_v1.types.persistent_resource_service import (
+from google.cloud.aiplatform_v1beta1.types.persistent_resource_service import (
     GetPersistentResourceRequest,
 )
 
@@ -47,7 +48,7 @@ def create_persistent_resource_client():
     return initializer.global_config.create_client(
         client_class=PersistentResourceClientWithOverride,
         appended_gapic_version="vertex_ray",
-    )
+    ).select_version("v1beta1")
 
 
 def polling_delay(num_attempts: int, time_scale: float) -> datetime.timedelta:
@@ -159,6 +160,10 @@ def persistent_resource_to_cluster(
             % persistent_resource.name,
         )
         return
+    if persistent_resource.psc_interface_config:
+        cluster.psc_interface_config = PscIConfig(
+            network_attachment=persistent_resource.psc_interface_config.network_attachment
+        )
     resource_pools = persistent_resource.resource_pools
 
     head_resource_pool = resource_pools[0]
@@ -192,6 +197,12 @@ def persistent_resource_to_cluster(
             ray_version = None
     cluster.python_version = python_version
     cluster.ray_version = ray_version
+    cluster.ray_metric_enabled = not (
+        persistent_resource.resource_runtime_spec.ray_spec.ray_metric_spec.disabled
+    )
+    cluster.ray_logs_enabled = not (
+        persistent_resource.resource_runtime_spec.ray_spec.ray_logs_spec.disabled
+    )
 
     accelerator_type = head_resource_pool.machine_spec.accelerator_type
     if accelerator_type.value != 0:

google/cloud/aiplatform/vertex_ray/util/resources.py

@@ -16,7 +16,7 @@
 #
 import dataclasses
 from typing import Dict, List, Optional
-from google.cloud.aiplatform_v1.types import PersistentResource
+from google.cloud.aiplatform_v1beta1.types import PersistentResource
 
 
 @dataclasses.dataclass
@@ -68,6 +68,27 @@ class NodeImages:
     worker: str = None
 
 
+@dataclasses.dataclass
+class PscIConfig:
+    """PSC-I config.
+
+    Attributes:
+        network_attachment: Optional. The name or full name of the Compute Engine
+            `network attachment <https://cloud.google.com/vpc/docs/about-network-attachments>`
+            to attach to the resource. It has a format:
+            ``projects/{project}/regions/{region}/networkAttachments/{networkAttachment}``.
+            Where {project} is a project number, as in ``12345``, and
+            {networkAttachment} is a network attachment name. To specify
+            this field, you must have already [created a network
+            attachment]
+            (https://cloud.google.com/vpc/docs/create-manage-network-attachments#create-network-attachments).
+            This field is only used for resources using PSC-I. Make sure you do not
+            specify the network here for VPC peering.
+    """
+
+    network_attachment: str = None
+
+
 @dataclasses.dataclass
 class Cluster:
     """Ray cluster (output only).
@@ -111,6 +132,9 @@ class Cluster:
     head_node_type: Resources = None
     worker_node_types: List[Resources] = None
     dashboard_address: str = None
+    ray_metric_enabled: bool = True
+    ray_logs_enabled: bool = True
+    psc_interface_config: PscIConfig = None
     labels: Dict[str, str] = None
 
 

tests/unit/vertex_ray/conftest.py

@@ -19,16 +19,16 @@
 from google.auth import credentials as auth_credentials
 from google.cloud import resourcemanager
 from google.cloud.aiplatform import vertex_ray
-from google.cloud.aiplatform_v1.services.persistent_resource_service import (
+from google.cloud.aiplatform_v1beta1.services.persistent_resource_service import (
     PersistentResourceServiceClient,
 )
-from google.cloud.aiplatform_v1.types.persistent_resource import (
+from google.cloud.aiplatform_v1beta1.types.persistent_resource import (
     PersistentResource,
 )
-from google.cloud.aiplatform_v1.types.persistent_resource import (
+from google.cloud.aiplatform_v1beta1.types.persistent_resource import (
     ResourceRuntime,
 )
-from google.cloud.aiplatform_v1.types.persistent_resource_service import (
+from google.cloud.aiplatform_v1beta1.types.persistent_resource_service import (
     DeletePersistentResourceRequest,
 )
 import test_constants as tc

tests/unit/vertex_ray/test_cluster_init.py

@@ -22,10 +22,10 @@
     Resources,
     NodeImages,
 )
-from google.cloud.aiplatform_v1.services.persistent_resource_service import (
+from google.cloud.aiplatform_v1beta1.services.persistent_resource_service import (
     PersistentResourceServiceClient,
 )
-from google.cloud.aiplatform_v1.types import persistent_resource_service
+from google.cloud.aiplatform_v1beta1.types import persistent_resource_service
 import test_constants as tc
 import mock
 import pytest
@@ -352,13 +352,15 @@ def test_create_ray_cluster_1_pool_gpu_with_labels_success(
         self, create_persistent_resource_1_pool_mock
     ):
         """If head and worker nodes are duplicate, merge to head pool."""
+        # Also test disable logging and metrics collection.
         cluster_name = vertex_ray.create_ray_cluster(
             head_node_type=tc.ClusterConstants.TEST_HEAD_NODE_TYPE_1_POOL,
             worker_node_types=tc.ClusterConstants.TEST_WORKER_NODE_TYPES_1_POOL,
             network=tc.ProjectConstants.TEST_VPC_NETWORK,
             cluster_name=tc.ClusterConstants.TEST_VERTEX_RAY_PR_ID,
             labels=tc.ClusterConstants.TEST_LABELS,
             enable_metrics_collection=False,
+            enable_logging=False,
         )
 
         assert tc.ClusterConstants.TEST_VERTEX_RAY_PR_ADDRESS == cluster_name
@@ -401,11 +403,15 @@ def test_create_ray_cluster_2_pools_success(
         self, create_persistent_resource_2_pools_mock
     ):
         """If head and worker nodes are not duplicate, create separate resource_pools."""
+        # Also test PSC-I.
+        psc_interface_config = vertex_ray.PscIConfig(
+            network_attachment=tc.ClusterConstants.TEST_PSC_NETWORK_ATTACHMENT
+        )
         cluster_name = vertex_ray.create_ray_cluster(
             head_node_type=tc.ClusterConstants.TEST_HEAD_NODE_TYPE_2_POOLS,
             worker_node_types=tc.ClusterConstants.TEST_WORKER_NODE_TYPES_2_POOLS,
-            network=tc.ProjectConstants.TEST_VPC_NETWORK,
             cluster_name=tc.ClusterConstants.TEST_VERTEX_RAY_PR_ID,
+            psc_interface_config=psc_interface_config,
         )
 
         assert tc.ClusterConstants.TEST_VERTEX_RAY_PR_ADDRESS == cluster_name