Add table gcp_aiplatform_endpoints Closes #470

docs/tables/gcp_vertex_ai_endpoint.md

@@ -0,0 +1,68 @@
+# Table: gcp_vertex_ai_endpoint
+
+AI Platform is a managed service that enables you to easily build machine learning models, that work on any type of data, of any size.
+
+### Basic info
+
+```sql
+select
+  name,
+  display_name,
+  create_time,
+  network
+from
+  gcp_vertex_ai_endpoint;
+```
+
+### List endpoints that are exposed via private service connect
+
+```sql
+select
+  name,
+  display_name,
+  create_time,
+  enable_private_service_connect
+from
+  gcp_vertex_ai_endpoint
+where
+  enable_private_service_connect;
+```
+
+### List endpoints created in the last 30 days
+
+```sql
+select
+  name,
+  display_name,
+  network,
+  create_time,
+  update_time
+from
+  gcp_vertex_ai_endpoint
+where
+  create_time >= now() - interval '30' day;
+```
+
+### Get customer-managed key details of endpoints
+
+```sql
+select
+  name,
+  create_time,
+  encryption_spec ->> 'KmsKeyName' as kms_key_name
+from
+  gcp_vertex_ai_endpoint;
+```
+
+### Get prediction request response config of endpoints
+
+```sql
+select
+  name,
+  network,
+  predict_request_response_logging_config ->> 'Enabled' as enabled,
+  predict_request_response_logging_config ->> 'SamplingRate' as sampling_rate,
+  predict_request_response_logging_config ->> 'BigqueryDestination' as bigquery_destination
+from
+  gcp_vertex_ai_endpoint;
+```

gcp/plugin.go

@@ -126,6 +126,7 @@ func Plugin(ctx context.Context) *plugin.Plugin {
 			"gcp_sql_database_instance_metric_cpu_utilization_hourly": tableGcpSQLDatabaseInstanceMetricCpuUtilizationHourly(ctx),
 			"gcp_storage_bucket":                                      tableGcpStorageBucket(ctx),
 			"gcp_storage_object":                                      tableGcpStorageObject(ctx),
+			"gcp_vertex_ai_endpoint":                                  tableGcpVertexAIEndpoint(ctx),
 			/*
 				https://github.com/turbot/steampipe/issues/108
 				"gcp_compute_route":                   tableGcpComputeRoute(ctx),

gcp/service.go

@@ -3,7 +3,8 @@ package gcp
 import (
 	"context"
 
-	"cloud.google.com/go/redis/apiv1"
+	aiplatform "cloud.google.com/go/aiplatform/apiv1"
+	redis "cloud.google.com/go/redis/apiv1"
 	"github.com/turbot/steampipe-plugin-sdk/v5/plugin"
 	"google.golang.org/api/accessapproval/v1"
 	"google.golang.org/api/apikeys/v2"
@@ -24,6 +25,7 @@ import (
 	"google.golang.org/api/iam/v1"
 	"google.golang.org/api/logging/v2"
 	"google.golang.org/api/monitoring/v3"
+	"google.golang.org/api/option"
 	"google.golang.org/api/pubsub/v1"
 	"google.golang.org/api/run/v2"
 	"google.golang.org/api/serviceusage/v1"
@@ -54,6 +56,68 @@ func AccessApprovalService(ctx context.Context, d *plugin.QueryData) (*accessapp
 	return svc, nil
 }
 
+type AIplatfromServiceClients struct {
+	Endpoint *aiplatform.EndpointClient
+	Dataset  *aiplatform.DatasetClient
+	Index    *aiplatform.IndexClient
+	Job      *aiplatform.JobClient
+}
+
+func AIService(ctx context.Context, d *plugin.QueryData, clientType string) (*AIplatfromServiceClients, error) {
+	// have we already created and cached the service?
+	matrixLocation := d.EqualsQualString(matrixKeyLocation)
+
+	// Default to us-central1 for building the supported locations for the resources like Endpoint, Dataset, Index, Job etc...
+	if matrixLocation == "" {
+		matrixLocation = "us-central1"
+	}
+
+	serviceCacheKey := "AIService" + matrixLocation + clientType
+	if cachedData, ok := d.ConnectionManager.Cache.Get(serviceCacheKey); ok {
+		return cachedData.(*AIplatfromServiceClients), nil
+	}
+
+	// To get config arguments from plugin config file
+	opts := setSessionConfig(ctx, d.Connection)
+	opts = append(opts, option.WithEndpoint(matrixLocation+"-aiplatform.googleapis.com:443"))
+
+	clients := &AIplatfromServiceClients{}
+
+	switch clientType {
+	case "Endpoint":
+		svc, err := aiplatform.NewEndpointClient(ctx, opts...)
+		if err != nil {
+			return nil, err
+		}
+		clients.Endpoint = svc
+		return clients, nil
+	case "Dataset":
+		svc, err := aiplatform.NewDatasetClient(ctx, opts...)
+		if err != nil {
+			return nil, err
+		}
+		clients.Dataset = svc
+		return clients, nil
+	case "Index":
+		svc, err := aiplatform.NewIndexClient(ctx, opts...)
+		if err != nil {
+			return nil, err
+		}
+		clients.Index = svc
+		return clients, nil
+	case "Job":
+		svc, err := aiplatform.NewJobClient(ctx, opts...)
+		if err != nil {
+			return nil, err
+		}
+		clients.Job = svc
+		return clients, nil
+	}
+
+	d.ConnectionManager.Cache.Set(serviceCacheKey, clients)
+	return clients, nil
+}
+
 func APIKeysService(ctx context.Context, d *plugin.QueryData) (*apikeys.Service, error) {
 	// have we already created and cached the service?
 	serviceCacheKey := "APIKeysService"