[GCP VertexAI] Add support for different deployment types (elastic#11923

)

* Add PT metrics visualisation to the dashboard and update README

packages/gcp_vertexai/_dev/build/docs/README.md

@@ -38,6 +38,15 @@ These permissions are included in many roles, but here are some of the most comm
 - **More granular roles:** For fine-grained control (recommended for security best practices), consider using a custom role built with the specific permissions needed. This would only include the necessary permissions to view model metrics, rather than broader access to all Vertex AI or Cloud Monitoring resources. This requires expertise in IAM (Identity and Access Management).
 - **Predefined roles with broader access:** These roles provide extensive permissions within the Google Cloud project, giving access to metrics but granting much broader abilities than necessary for just viewing metrics. These are generally too permissive unless necessary for other tasks. Examples are `roles/aiplatform`.user or `roles/editor`.
 
+#### Deployment Types in Vertex AI:
+
+Vertex AI offers two primary deployment types,
+
+- **Provisioned Throughput:** Suitable for high-usage applications with predictable workloads and a premium on guaranteed performance.
+- **Pay-as-you-go:** Ideal for low-usage applications, batch processing, and applications with unpredictable traffic patterns.
+
+Now, you can track and monitor different deployment types (provisioned throughput and pay-as-you-go) in Vertex AI using the Model Garden Publisher resource.
+
 #### Configuration
 
 To fetch the metrics, enter the project_id and the credentials file/json.

packages/gcp_vertexai/changelog.yml

@@ -1,4 +1,9 @@
 # newer versions go on top
+- version: "0.2.0"
+  changes:
+    - description: Add PT deployment metrics to dashboard and update documentation.
+      type: enhancement
+      link: https://github.com/elastic/integrations/pull/11923
 - version: "0.1.0"
   changes:
     - description: Update documentation with roles and permissions.

packages/gcp_vertexai/docs/README.md

@@ -38,6 +38,15 @@ These permissions are included in many roles, but here are some of the most comm
 - **More granular roles:** For fine-grained control (recommended for security best practices), consider using a custom role built with the specific permissions needed. This would only include the necessary permissions to view model metrics, rather than broader access to all Vertex AI or Cloud Monitoring resources. This requires expertise in IAM (Identity and Access Management).
 - **Predefined roles with broader access:** These roles provide extensive permissions within the Google Cloud project, giving access to metrics but granting much broader abilities than necessary for just viewing metrics. These are generally too permissive unless necessary for other tasks. Examples are `roles/aiplatform`.user or `roles/editor`.
 
+#### Deployment Types in Vertex AI:
+
+Vertex AI offers two primary deployment types,
+
+- **Provisioned Throughput:** Suitable for high-usage applications with predictable workloads and a premium on guaranteed performance.
+- **Pay-as-you-go:** Ideal for low-usage applications, batch processing, and applications with unpredictable traffic patterns.
+
+Now, you can track and monitor different deployment types (provisioned throughput and pay-as-you-go) in Vertex AI using the Model Garden Publisher resource.
+
 #### Configuration
 
 To fetch the metrics, enter the project_id and the credentials file/json.