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Viewing docs for Google Cloud v9.32.1
published on Wednesday, Jul 29, 2026 by Pulumi
Schema (JSON)
pulumi/pulumi-gcp

gcp.vectorsearch.Index

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Viewing docs for Google Cloud v9.32.1
published on Wednesday, Jul 29, 2026 by Pulumi
Schema (JSON)
pulumi/pulumi-gcp

    An Index defines an approximate nearest-neighbor search structure over a field of a Vector Search Collection.

    Example Usage

    Vectorsearch Index Basic

    import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

// NOTE: For most workloads we recommend creating the Collection and the Index
// in *separate* Terraform configurations (i.e. create and apply the Collection
// first, ingest data via importDataObjects, and only then create the Index in a
// second configuration). Once an Index exists on a Collection you can no longer
// run importDataObjects for bulk ingestion of data objects on that Collection --
// you are limited to creating data objects one at a time or in small online
// batches. Defining both resources in the same Terraform file (as shown below)
// is convenient for a quick start, but locks you into the online / batched
// create path for any subsequent data ingestion.
const parent = new gcp.vectorsearch.Collection("parent", {
    location: "us-central1",
    collectionId: "example-collection",
    displayName: "My Awesome Collection",
    description: "This collection stores important data.",
    dataSchema: `{
  \\"type\\": \\"object\\",
  \\"properties\\": {
    \\"title\\": {
      \\"type\\": \\"string\\"
    },
    \\"plot\\": {
      \\"type\\": \\"string\\"
    }
  }
}
`,
    vectorSchemas: [{
        fieldName: "text_embedding",
        denseVector: {
            dimensions: 768,
            vertexEmbeddingConfig: {
                modelId: "textembedding-gecko@003",
                taskType: "RETRIEVAL_DOCUMENT",
                textTemplate: "Title: {title} ---- Plot: {plot}",
            },
        },
    }],
});
const example_index = new gcp.vectorsearch.Index("example-index", {
    location: "us-central1",
    collectionId: parent.collectionId,
    indexId: "example-index",
    displayName: "My Awesome Index",
    description: "ScaNN index over text_embedding.",
    indexField: "text_embedding",
    distanceMetric: "DOT_PRODUCT",
    denseScann: {
        featureNormType: "UNIT_L2_NORM",
    },
});

    import pulumi
import pulumi_gcp as gcp

# NOTE: For most workloads we recommend creating the Collection and the Index
# in *separate* Terraform configurations (i.e. create and apply the Collection
# first, ingest data via importDataObjects, and only then create the Index in a
# second configuration). Once an Index exists on a Collection you can no longer
# run importDataObjects for bulk ingestion of data objects on that Collection --
# you are limited to creating data objects one at a time or in small online
# batches. Defining both resources in the same Terraform file (as shown below)
# is convenient for a quick start, but locks you into the online / batched
# create path for any subsequent data ingestion.
parent = gcp.vectorsearch.Collection("parent",
    location="us-central1",
    collection_id="example-collection",
    display_name="My Awesome Collection",
    description="This collection stores important data.",
    data_schema="""{
  \"type\": \"object\",
  \"properties\": {
    \"title\": {
      \"type\": \"string\"
    },
    \"plot\": {
      \"type\": \"string\"
    }
  }
}
""",
    vector_schemas=[{
        "field_name": "text_embedding",
        "dense_vector": {
            "dimensions": 768,
            "vertex_embedding_config": {
                "model_id": "textembedding-gecko@003",
                "task_type": "RETRIEVAL_DOCUMENT",
                "text_template": "Title: {title} ---- Plot: {plot}",
            },
        },
    }])
example_index = gcp.vectorsearch.Index("example-index",
    location="us-central1",
    collection_id=parent.collection_id,
    index_id="example-index",
    display_name="My Awesome Index",
    description="ScaNN index over text_embedding.",
    index_field="text_embedding",
    distance_metric="DOT_PRODUCT",
    dense_scann={
        "feature_norm_type": "UNIT_L2_NORM",
    })

    package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v9/go/gcp/vectorsearch"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		// NOTE: For most workloads we recommend creating the Collection and the Index
		// in *separate* Terraform configurations (i.e. create and apply the Collection
		// first, ingest data via importDataObjects, and only then create the Index in a
		// second configuration). Once an Index exists on a Collection you can no longer
		// run importDataObjects for bulk ingestion of data objects on that Collection --
		// you are limited to creating data objects one at a time or in small online
		// batches. Defining both resources in the same Terraform file (as shown below)
		// is convenient for a quick start, but locks you into the online / batched
		// create path for any subsequent data ingestion.
		parent, err := vectorsearch.NewCollection(ctx, "parent", &vectorsearch.CollectionArgs{
			Location:     pulumi.String("us-central1"),
			CollectionId: pulumi.String("example-collection"),
			DisplayName:  pulumi.String("My Awesome Collection"),
			Description:  pulumi.String("This collection stores important data."),
			DataSchema: pulumi.String(`{
  \"type\": \"object\",
  \"properties\": {
    \"title\": {
      \"type\": \"string\"
    },
    \"plot\": {
      \"type\": \"string\"
    }
  }
}
`),
			VectorSchemas: vectorsearch.CollectionVectorSchemaArray{
				&vectorsearch.CollectionVectorSchemaArgs{
					FieldName: pulumi.String("text_embedding"),
					DenseVector: &vectorsearch.CollectionVectorSchemaDenseVectorArgs{
						Dimensions: pulumi.Int(768),
						VertexEmbeddingConfig: &vectorsearch.CollectionVectorSchemaDenseVectorVertexEmbeddingConfigArgs{
							ModelId:      pulumi.String("textembedding-gecko@003"),
							TaskType:     pulumi.String("RETRIEVAL_DOCUMENT"),
							TextTemplate: pulumi.String("Title: {title} ---- Plot: {plot}"),
						},
					},
				},
			},
		})
		if err != nil {
			return err
		}
		_, err = vectorsearch.NewIndex(ctx, "example-index", &vectorsearch.IndexArgs{
			Location:       pulumi.String("us-central1"),
			CollectionId:   parent.CollectionId,
			IndexId:        pulumi.String("example-index"),
			DisplayName:    pulumi.String("My Awesome Index"),
			Description:    pulumi.String("ScaNN index over text_embedding."),
			IndexField:     pulumi.String("text_embedding"),
			DistanceMetric: pulumi.String("DOT_PRODUCT"),
			DenseScann: &vectorsearch.IndexDenseScannArgs{
				FeatureNormType: pulumi.String("UNIT_L2_NORM"),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    // NOTE: For most workloads we recommend creating the Collection and the Index
    // in *separate* Terraform configurations (i.e. create and apply the Collection
    // first, ingest data via importDataObjects, and only then create the Index in a
    // second configuration). Once an Index exists on a Collection you can no longer
    // run importDataObjects for bulk ingestion of data objects on that Collection --
    // you are limited to creating data objects one at a time or in small online
    // batches. Defining both resources in the same Terraform file (as shown below)
    // is convenient for a quick start, but locks you into the online / batched
    // create path for any subsequent data ingestion.
    var parent = new Gcp.VectorSearch.Collection("parent", new()
    {
        Location = "us-central1",
        CollectionId = "example-collection",
        DisplayName = "My Awesome Collection",
        Description = "This collection stores important data.",
        DataSchema = @"{
  \""type\"": \""object\"",
  \""properties\"": {
    \""title\"": {
      \""type\"": \""string\""
    },
    \""plot\"": {
      \""type\"": \""string\""
    }
  }
}
",
        VectorSchemas = new[]
        {
            new Gcp.VectorSearch.Inputs.CollectionVectorSchemaArgs
            {
                FieldName = "text_embedding",
                DenseVector = new Gcp.VectorSearch.Inputs.CollectionVectorSchemaDenseVectorArgs
                {
                    Dimensions = 768,
                    VertexEmbeddingConfig = new Gcp.VectorSearch.Inputs.CollectionVectorSchemaDenseVectorVertexEmbeddingConfigArgs
                    {
                        ModelId = "textembedding-gecko@003",
                        TaskType = "RETRIEVAL_DOCUMENT",
                        TextTemplate = "Title: {title} ---- Plot: {plot}",
                    },
                },
            },
        },
    });

    var example_index = new Gcp.VectorSearch.Index("example-index", new()
    {
        Location = "us-central1",
        CollectionId = parent.CollectionId,
        IndexId = "example-index",
        DisplayName = "My Awesome Index",
        Description = "ScaNN index over text_embedding.",
        IndexField = "text_embedding",
        DistanceMetric = "DOT_PRODUCT",
        DenseScann = new Gcp.VectorSearch.Inputs.IndexDenseScannArgs
        {
            FeatureNormType = "UNIT_L2_NORM",
        },
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vectorsearch.Collection;
import com.pulumi.gcp.vectorsearch.CollectionArgs;
import com.pulumi.gcp.vectorsearch.inputs.CollectionVectorSchemaArgs;
import com.pulumi.gcp.vectorsearch.inputs.CollectionVectorSchemaDenseVectorArgs;
import com.pulumi.gcp.vectorsearch.inputs.CollectionVectorSchemaDenseVectorVertexEmbeddingConfigArgs;
import com.pulumi.gcp.vectorsearch.Index;
import com.pulumi.gcp.vectorsearch.IndexArgs;
import com.pulumi.gcp.vectorsearch.inputs.IndexDenseScannArgs;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        // NOTE: For most workloads we recommend creating the Collection and the Index
        // in *separate* Terraform configurations (i.e. create and apply the Collection
        // first, ingest data via importDataObjects, and only then create the Index in a
        // second configuration). Once an Index exists on a Collection you can no longer
        // run importDataObjects for bulk ingestion of data objects on that Collection --
        // you are limited to creating data objects one at a time or in small online
        // batches. Defining both resources in the same Terraform file (as shown below)
        // is convenient for a quick start, but locks you into the online / batched
        // create path for any subsequent data ingestion.
        var parent = new Collection("parent", CollectionArgs.builder()
            .location("us-central1")
            .collectionId("example-collection")
            .displayName("My Awesome Collection")
            .description("This collection stores important data.")
            .dataSchema("""
{
  \"type\": \"object\",
  \"properties\": {
    \"title\": {
      \"type\": \"string\"
    },
    \"plot\": {
      \"type\": \"string\"
    }
  }
}
            """)
            .vectorSchemas(CollectionVectorSchemaArgs.builder()
                .fieldName("text_embedding")
                .denseVector(CollectionVectorSchemaDenseVectorArgs.builder()
                    .dimensions(768)
                    .vertexEmbeddingConfig(CollectionVectorSchemaDenseVectorVertexEmbeddingConfigArgs.builder()
                        .modelId("textembedding-gecko@003")
                        .taskType("RETRIEVAL_DOCUMENT")
                        .textTemplate("Title: {title} ---- Plot: {plot}")
                        .build())
                    .build())
                .build())
            .build());

        var example_index = new Index("example-index", IndexArgs.builder()
            .location("us-central1")
            .collectionId(parent.collectionId())
            .indexId("example-index")
            .displayName("My Awesome Index")
            .description("ScaNN index over text_embedding.")
            .indexField("text_embedding")
            .distanceMetric("DOT_PRODUCT")
            .denseScann(IndexDenseScannArgs.builder()
                .featureNormType("UNIT_L2_NORM")
                .build())
            .build());

    }
}

    resources:
  # NOTE: For most workloads we recommend creating the Collection and the Index
  # in *separate* Terraform configurations (i.e. create and apply the Collection
  # first, ingest data via importDataObjects, and only then create the Index in a
  # second configuration). Once an Index exists on a Collection you can no longer
  # run importDataObjects for bulk ingestion of data objects on that Collection --
  # you are limited to creating data objects one at a time or in small online
  # batches. Defining both resources in the same Terraform file (as shown below)
  # is convenient for a quick start, but locks you into the online / batched
  # create path for any subsequent data ingestion.
  parent:
    type: gcp:vectorsearch:Collection
    properties:
      location: us-central1
      collectionId: example-collection
      displayName: My Awesome Collection
      description: This collection stores important data.
      dataSchema: |
        {
          \"type\": \"object\",
          \"properties\": {
            \"title\": {
              \"type\": \"string\"
            },
            \"plot\": {
              \"type\": \"string\"
            }
          }
        }
      vectorSchemas:
        - fieldName: text_embedding
          denseVector:
            dimensions: 768
            vertexEmbeddingConfig:
              modelId: textembedding-gecko@003
              taskType: RETRIEVAL_DOCUMENT
              textTemplate: 'Title: {title} ---- Plot: {plot}'
  example-index:
    type: gcp:vectorsearch:Index
    properties:
      location: us-central1
      collectionId: ${parent.collectionId}
      indexId: example-index
      displayName: My Awesome Index
      description: ScaNN index over text_embedding.
      indexField: text_embedding
      distanceMetric: DOT_PRODUCT
      denseScann:
        featureNormType: UNIT_L2_NORM

    pulumi {
  required_providers {
    gcp = {
      source = "pulumi/gcp"
    }
  }
}

# NOTE: For most workloads we recommend creating the Collection and the Index
# in *separate* Terraform configurations (i.e. create and apply the Collection
# first, ingest data via importDataObjects, and only then create the Index in a
# second configuration). Once an Index exists on a Collection you can no longer
# run importDataObjects for bulk ingestion of data objects on that Collection --
# you are limited to creating data objects one at a time or in small online
# batches. Defining both resources in the same Terraform file (as shown below)
# is convenient for a quick start, but locks you into the online / batched
# create path for any subsequent data ingestion.
resource "gcp_vectorsearch_collection" "parent" {
  location      = "us-central1"
  collection_id = "example-collection"
  display_name  = "My Awesome Collection"
  description   = "This collection stores important data."
  data_schema   = "{\n  \\\"type\\\": \\\"object\\\",\n  \\\"properties\\\": {\n    \\\"title\\\": {\n      \\\"type\\\": \\\"string\\\"\n    },\n    \\\"plot\\\": {\n      \\\"type\\\": \\\"string\\\"\n    }\n  }\n}\n"
  vector_schemas {
    field_name = "text_embedding"
    dense_vector = {
      dimensions = 768
      vertex_embedding_config = {
        model_id      = "textembedding-gecko@003"
        task_type     = "RETRIEVAL_DOCUMENT"
        text_template = "Title: {title} ---- Plot: {plot}"
      }
    }
  }
}
resource "gcp_vectorsearch_index" "example-index" {
  location        = "us-central1"
  collection_id   = gcp_vectorsearch_collection.parent.collection_id
  index_id        = "example-index"
  display_name    = "My Awesome Index"
  description     = "ScaNN index over text_embedding."
  index_field     = "text_embedding"
  distance_metric = "DOT_PRODUCT"
  dense_scann = {
    feature_norm_type = "UNIT_L2_NORM"
  }
}

    Vectorsearch Index Dedicated

    import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

// NOTE: For most workloads we recommend creating the Collection and the Index
// in *separate* Terraform configurations (i.e. create and apply the Collection
// first, ingest data via importDataObjects, and only then create the Index in a
// second configuration). Once an Index exists on a Collection you can no longer
// run importDataObjects for bulk ingestion of data objects on that Collection --
// you are limited to creating data objects one at a time or in small online
// batches. Defining both resources in the same Terraform file (as shown below)
// is convenient for a quick start, but locks you into the online / batched
// create path for any subsequent data ingestion.
const parent = new gcp.vectorsearch.Collection("parent", {
    location: "us-central1",
    collectionId: "example-dedicated-collection",
    displayName: "My Awesome Collection",
    description: "Parent collection for a dedicated-infrastructure index.",
    dataSchema: `{
  \\"type\\": \\"object\\",
  \\"properties\\": {
    \\"title\\": {
      \\"type\\": \\"string\\"
    },
    \\"category\\": {
      \\"type\\": \\"string\\"
    }
  }
}
`,
    vectorSchemas: [{
        fieldName: "text_embedding",
        denseVector: {
            dimensions: 768,
            vertexEmbeddingConfig: {
                modelId: "textembedding-gecko@003",
                taskType: "RETRIEVAL_DOCUMENT",
                textTemplate: "Title: {title}",
            },
        },
    }],
});
const example_dedicated_index = new gcp.vectorsearch.Index("example-dedicated-index", {
    location: "us-central1",
    collectionId: parent.collectionId,
    indexId: "example-dedicated-index",
    displayName: "My Dedicated Index",
    description: "Index served on dedicated infrastructure with autoscaling.",
    indexField: "text_embedding",
    distanceMetric: "COSINE_DISTANCE",
    filterFields: ["category"],
    storeFields: ["title"],
    denseScann: {
        featureNormType: "UNIT_L2_NORM",
    },
    dedicatedInfrastructure: {
        mode: "PERFORMANCE_OPTIMIZED",
        autoscalingSpec: {
            minReplicaCount: 2,
            maxReplicaCount: 5,
        },
    },
});

    import pulumi
import pulumi_gcp as gcp

# NOTE: For most workloads we recommend creating the Collection and the Index
# in *separate* Terraform configurations (i.e. create and apply the Collection
# first, ingest data via importDataObjects, and only then create the Index in a
# second configuration). Once an Index exists on a Collection you can no longer
# run importDataObjects for bulk ingestion of data objects on that Collection --
# you are limited to creating data objects one at a time or in small online
# batches. Defining both resources in the same Terraform file (as shown below)
# is convenient for a quick start, but locks you into the online / batched
# create path for any subsequent data ingestion.
parent = gcp.vectorsearch.Collection("parent",
    location="us-central1",
    collection_id="example-dedicated-collection",
    display_name="My Awesome Collection",
    description="Parent collection for a dedicated-infrastructure index.",
    data_schema="""{
  \"type\": \"object\",
  \"properties\": {
    \"title\": {
      \"type\": \"string\"
    },
    \"category\": {
      \"type\": \"string\"
    }
  }
}
""",
    vector_schemas=[{
        "field_name": "text_embedding",
        "dense_vector": {
            "dimensions": 768,
            "vertex_embedding_config": {
                "model_id": "textembedding-gecko@003",
                "task_type": "RETRIEVAL_DOCUMENT",
                "text_template": "Title: {title}",
            },
        },
    }])
example_dedicated_index = gcp.vectorsearch.Index("example-dedicated-index",
    location="us-central1",
    collection_id=parent.collection_id,
    index_id="example-dedicated-index",
    display_name="My Dedicated Index",
    description="Index served on dedicated infrastructure with autoscaling.",
    index_field="text_embedding",
    distance_metric="COSINE_DISTANCE",
    filter_fields=["category"],
    store_fields=["title"],
    dense_scann={
        "feature_norm_type": "UNIT_L2_NORM",
    },
    dedicated_infrastructure={
        "mode": "PERFORMANCE_OPTIMIZED",
        "autoscaling_spec": {
            "min_replica_count": 2,
            "max_replica_count": 5,
        },
    })

    package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v9/go/gcp/vectorsearch"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		// NOTE: For most workloads we recommend creating the Collection and the Index
		// in *separate* Terraform configurations (i.e. create and apply the Collection
		// first, ingest data via importDataObjects, and only then create the Index in a
		// second configuration). Once an Index exists on a Collection you can no longer
		// run importDataObjects for bulk ingestion of data objects on that Collection --
		// you are limited to creating data objects one at a time or in small online
		// batches. Defining both resources in the same Terraform file (as shown below)
		// is convenient for a quick start, but locks you into the online / batched
		// create path for any subsequent data ingestion.
		parent, err := vectorsearch.NewCollection(ctx, "parent", &vectorsearch.CollectionArgs{
			Location:     pulumi.String("us-central1"),
			CollectionId: pulumi.String("example-dedicated-collection"),
			DisplayName:  pulumi.String("My Awesome Collection"),
			Description:  pulumi.String("Parent collection for a dedicated-infrastructure index."),
			DataSchema: pulumi.String(`{
  \"type\": \"object\",
  \"properties\": {
    \"title\": {
      \"type\": \"string\"
    },
    \"category\": {
      \"type\": \"string\"
    }
  }
}
`),
			VectorSchemas: vectorsearch.CollectionVectorSchemaArray{
				&vectorsearch.CollectionVectorSchemaArgs{
					FieldName: pulumi.String("text_embedding"),
					DenseVector: &vectorsearch.CollectionVectorSchemaDenseVectorArgs{
						Dimensions: pulumi.Int(768),
						VertexEmbeddingConfig: &vectorsearch.CollectionVectorSchemaDenseVectorVertexEmbeddingConfigArgs{
							ModelId:      pulumi.String("textembedding-gecko@003"),
							TaskType:     pulumi.String("RETRIEVAL_DOCUMENT"),
							TextTemplate: pulumi.String("Title: {title}"),
						},
					},
				},
			},
		})
		if err != nil {
			return err
		}
		_, err = vectorsearch.NewIndex(ctx, "example-dedicated-index", &vectorsearch.IndexArgs{
			Location:       pulumi.String("us-central1"),
			CollectionId:   parent.CollectionId,
			IndexId:        pulumi.String("example-dedicated-index"),
			DisplayName:    pulumi.String("My Dedicated Index"),
			Description:    pulumi.String("Index served on dedicated infrastructure with autoscaling."),
			IndexField:     pulumi.String("text_embedding"),
			DistanceMetric: pulumi.String("COSINE_DISTANCE"),
			FilterFields: pulumi.StringArray{
				pulumi.String("category"),
			},
			StoreFields: pulumi.StringArray{
				pulumi.String("title"),
			},
			DenseScann: &vectorsearch.IndexDenseScannArgs{
				FeatureNormType: pulumi.String("UNIT_L2_NORM"),
			},
			DedicatedInfrastructure: &vectorsearch.IndexDedicatedInfrastructureArgs{
				Mode: pulumi.String("PERFORMANCE_OPTIMIZED"),
				AutoscalingSpec: &vectorsearch.IndexDedicatedInfrastructureAutoscalingSpecArgs{
					MinReplicaCount: pulumi.Int(2),
					MaxReplicaCount: pulumi.Int(5),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    // NOTE: For most workloads we recommend creating the Collection and the Index
    // in *separate* Terraform configurations (i.e. create and apply the Collection
    // first, ingest data via importDataObjects, and only then create the Index in a
    // second configuration). Once an Index exists on a Collection you can no longer
    // run importDataObjects for bulk ingestion of data objects on that Collection --
    // you are limited to creating data objects one at a time or in small online
    // batches. Defining both resources in the same Terraform file (as shown below)
    // is convenient for a quick start, but locks you into the online / batched
    // create path for any subsequent data ingestion.
    var parent = new Gcp.VectorSearch.Collection("parent", new()
    {
        Location = "us-central1",
        CollectionId = "example-dedicated-collection",
        DisplayName = "My Awesome Collection",
        Description = "Parent collection for a dedicated-infrastructure index.",
        DataSchema = @"{
  \""type\"": \""object\"",
  \""properties\"": {
    \""title\"": {
      \""type\"": \""string\""
    },
    \""category\"": {
      \""type\"": \""string\""
    }
  }
}
",
        VectorSchemas = new[]
        {
            new Gcp.VectorSearch.Inputs.CollectionVectorSchemaArgs
            {
                FieldName = "text_embedding",
                DenseVector = new Gcp.VectorSearch.Inputs.CollectionVectorSchemaDenseVectorArgs
                {
                    Dimensions = 768,
                    VertexEmbeddingConfig = new Gcp.VectorSearch.Inputs.CollectionVectorSchemaDenseVectorVertexEmbeddingConfigArgs
                    {
                        ModelId = "textembedding-gecko@003",
                        TaskType = "RETRIEVAL_DOCUMENT",
                        TextTemplate = "Title: {title}",
                    },
                },
            },
        },
    });

    var example_dedicated_index = new Gcp.VectorSearch.Index("example-dedicated-index", new()
    {
        Location = "us-central1",
        CollectionId = parent.CollectionId,
        IndexId = "example-dedicated-index",
        DisplayName = "My Dedicated Index",
        Description = "Index served on dedicated infrastructure with autoscaling.",
        IndexField = "text_embedding",
        DistanceMetric = "COSINE_DISTANCE",
        FilterFields = new[]
        {
            "category",
        },
        StoreFields = new[]
        {
            "title",
        },
        DenseScann = new Gcp.VectorSearch.Inputs.IndexDenseScannArgs
        {
            FeatureNormType = "UNIT_L2_NORM",
        },
        DedicatedInfrastructure = new Gcp.VectorSearch.Inputs.IndexDedicatedInfrastructureArgs
        {
            Mode = "PERFORMANCE_OPTIMIZED",
            AutoscalingSpec = new Gcp.VectorSearch.Inputs.IndexDedicatedInfrastructureAutoscalingSpecArgs
            {
                MinReplicaCount = 2,
                MaxReplicaCount = 5,
            },
        },
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vectorsearch.Collection;
import com.pulumi.gcp.vectorsearch.CollectionArgs;
import com.pulumi.gcp.vectorsearch.inputs.CollectionVectorSchemaArgs;
import com.pulumi.gcp.vectorsearch.inputs.CollectionVectorSchemaDenseVectorArgs;
import com.pulumi.gcp.vectorsearch.inputs.CollectionVectorSchemaDenseVectorVertexEmbeddingConfigArgs;
import com.pulumi.gcp.vectorsearch.Index;
import com.pulumi.gcp.vectorsearch.IndexArgs;
import com.pulumi.gcp.vectorsearch.inputs.IndexDenseScannArgs;
import com.pulumi.gcp.vectorsearch.inputs.IndexDedicatedInfrastructureArgs;
import com.pulumi.gcp.vectorsearch.inputs.IndexDedicatedInfrastructureAutoscalingSpecArgs;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        // NOTE: For most workloads we recommend creating the Collection and the Index
        // in *separate* Terraform configurations (i.e. create and apply the Collection
        // first, ingest data via importDataObjects, and only then create the Index in a
        // second configuration). Once an Index exists on a Collection you can no longer
        // run importDataObjects for bulk ingestion of data objects on that Collection --
        // you are limited to creating data objects one at a time or in small online
        // batches. Defining both resources in the same Terraform file (as shown below)
        // is convenient for a quick start, but locks you into the online / batched
        // create path for any subsequent data ingestion.
        var parent = new Collection("parent", CollectionArgs.builder()
            .location("us-central1")
            .collectionId("example-dedicated-collection")
            .displayName("My Awesome Collection")
            .description("Parent collection for a dedicated-infrastructure index.")
            .dataSchema("""
{
  \"type\": \"object\",
  \"properties\": {
    \"title\": {
      \"type\": \"string\"
    },
    \"category\": {
      \"type\": \"string\"
    }
  }
}
            """)
            .vectorSchemas(CollectionVectorSchemaArgs.builder()
                .fieldName("text_embedding")
                .denseVector(CollectionVectorSchemaDenseVectorArgs.builder()
                    .dimensions(768)
                    .vertexEmbeddingConfig(CollectionVectorSchemaDenseVectorVertexEmbeddingConfigArgs.builder()
                        .modelId("textembedding-gecko@003")
                        .taskType("RETRIEVAL_DOCUMENT")
                        .textTemplate("Title: {title}")
                        .build())
                    .build())
                .build())
            .build());

        var example_dedicated_index = new Index("example-dedicated-index", IndexArgs.builder()
            .location("us-central1")
            .collectionId(parent.collectionId())
            .indexId("example-dedicated-index")
            .displayName("My Dedicated Index")
            .description("Index served on dedicated infrastructure with autoscaling.")
            .indexField("text_embedding")
            .distanceMetric("COSINE_DISTANCE")
            .filterFields("category")
            .storeFields("title")
            .denseScann(IndexDenseScannArgs.builder()
                .featureNormType("UNIT_L2_NORM")
                .build())
            .dedicatedInfrastructure(IndexDedicatedInfrastructureArgs.builder()
                .mode("PERFORMANCE_OPTIMIZED")
                .autoscalingSpec(IndexDedicatedInfrastructureAutoscalingSpecArgs.builder()
                    .minReplicaCount(2)
                    .maxReplicaCount(5)
                    .build())
                .build())
            .build());

    }
}

    resources:
  # NOTE: For most workloads we recommend creating the Collection and the Index
  # in *separate* Terraform configurations (i.e. create and apply the Collection
  # first, ingest data via importDataObjects, and only then create the Index in a
  # second configuration). Once an Index exists on a Collection you can no longer
  # run importDataObjects for bulk ingestion of data objects on that Collection --
  # you are limited to creating data objects one at a time or in small online
  # batches. Defining both resources in the same Terraform file (as shown below)
  # is convenient for a quick start, but locks you into the online / batched
  # create path for any subsequent data ingestion.
  parent:
    type: gcp:vectorsearch:Collection
    properties:
      location: us-central1
      collectionId: example-dedicated-collection
      displayName: My Awesome Collection
      description: Parent collection for a dedicated-infrastructure index.
      dataSchema: |
        {
          \"type\": \"object\",
          \"properties\": {
            \"title\": {
              \"type\": \"string\"
            },
            \"category\": {
              \"type\": \"string\"
            }
          }
        }
      vectorSchemas:
        - fieldName: text_embedding
          denseVector:
            dimensions: 768
            vertexEmbeddingConfig:
              modelId: textembedding-gecko@003
              taskType: RETRIEVAL_DOCUMENT
              textTemplate: 'Title: {title}'
  example-dedicated-index:
    type: gcp:vectorsearch:Index
    properties:
      location: us-central1
      collectionId: ${parent.collectionId}
      indexId: example-dedicated-index
      displayName: My Dedicated Index
      description: Index served on dedicated infrastructure with autoscaling.
      indexField: text_embedding
      distanceMetric: COSINE_DISTANCE
      filterFields:
        - category
      storeFields:
        - title
      denseScann:
        featureNormType: UNIT_L2_NORM
      dedicatedInfrastructure:
        mode: PERFORMANCE_OPTIMIZED
        autoscalingSpec:
          minReplicaCount: 2
          maxReplicaCount: 5

    pulumi {
  required_providers {
    gcp = {
      source = "pulumi/gcp"
    }
  }
}

# NOTE: For most workloads we recommend creating the Collection and the Index
# in *separate* Terraform configurations (i.e. create and apply the Collection
# first, ingest data via importDataObjects, and only then create the Index in a
# second configuration). Once an Index exists on a Collection you can no longer
# run importDataObjects for bulk ingestion of data objects on that Collection --
# you are limited to creating data objects one at a time or in small online
# batches. Defining both resources in the same Terraform file (as shown below)
# is convenient for a quick start, but locks you into the online / batched
# create path for any subsequent data ingestion.
resource "gcp_vectorsearch_collection" "parent" {
  location      = "us-central1"
  collection_id = "example-dedicated-collection"
  display_name  = "My Awesome Collection"
  description   = "Parent collection for a dedicated-infrastructure index."
  data_schema   = "{\n  \\\"type\\\": \\\"object\\\",\n  \\\"properties\\\": {\n    \\\"title\\\": {\n      \\\"type\\\": \\\"string\\\"\n    },\n    \\\"category\\\": {\n      \\\"type\\\": \\\"string\\\"\n    }\n  }\n}\n"
  vector_schemas {
    field_name = "text_embedding"
    dense_vector = {
      dimensions = 768
      vertex_embedding_config = {
        model_id      = "textembedding-gecko@003"
        task_type     = "RETRIEVAL_DOCUMENT"
        text_template = "Title: {title}"
      }
    }
  }
}
resource "gcp_vectorsearch_index" "example-dedicated-index" {
  location        = "us-central1"
  collection_id   = gcp_vectorsearch_collection.parent.collection_id
  index_id        = "example-dedicated-index"
  display_name    = "My Dedicated Index"
  description     = "Index served on dedicated infrastructure with autoscaling."
  index_field     = "text_embedding"
  distance_metric = "COSINE_DISTANCE"
  filter_fields   = ["category"]
  store_fields    = ["title"]
  dense_scann = {
    feature_norm_type = "UNIT_L2_NORM"
  }
  dedicated_infrastructure = {
    mode = "PERFORMANCE_OPTIMIZED"
    autoscaling_spec = {
      min_replica_count = 2
      max_replica_count = 5
    }
  }
}

    Create Index Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new Index(name: string, args: IndexArgs, opts?: CustomResourceOptions);
    @overload
def Index(resource_name: str,
          args: IndexArgs,
          opts: Optional[ResourceOptions] = None)

@overload
def Index(resource_name: str,
          opts: Optional[ResourceOptions] = None,
          index_field: Optional[str] = None,
          location: Optional[str] = None,
          index_id: Optional[str] = None,
          collection_id: Optional[str] = None,
          dense_scann: Optional[IndexDenseScannArgs] = None,
          display_name: Optional[str] = None,
          distance_metric: Optional[str] = None,
          filter_fields: Optional[Sequence[str]] = None,
          description: Optional[str] = None,
          deletion_policy: Optional[str] = None,
          labels: Optional[Mapping[str, str]] = None,
          dedicated_infrastructure: Optional[IndexDedicatedInfrastructureArgs] = None,
          project: Optional[str] = None,
          store_fields: Optional[Sequence[str]] = None)
    func NewIndex(ctx *Context, name string, args IndexArgs, opts ...ResourceOption) (*Index, error)
    public Index(string name, IndexArgs args, CustomResourceOptions? opts = null)
    public Index(String name, IndexArgs args)
public Index(String name, IndexArgs args, CustomResourceOptions options)

    type: gcp:vectorsearch:Index
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.


    resource "gcp_vectorsearch_index" "name" {
    # resource properties
}

    Parameters

    name string
    The unique name of the resource.
    args IndexArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args IndexArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args IndexArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args IndexArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args IndexArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var gcpIndexResource = new Gcp.VectorSearch.Index("gcpIndexResource", new()
{
    IndexField = "string",
    Location = "string",
    IndexId = "string",
    CollectionId = "string",
    DenseScann = new Gcp.VectorSearch.Inputs.IndexDenseScannArgs
    {
        FeatureNormType = "string",
    },
    DisplayName = "string",
    DistanceMetric = "string",
    FilterFields = new[]
    {
        "string",
    },
    Description = "string",
    DeletionPolicy = "string",
    Labels = 
    {
        { "string", "string" },
    },
    DedicatedInfrastructure = new Gcp.VectorSearch.Inputs.IndexDedicatedInfrastructureArgs
    {
        AutoscalingSpec = new Gcp.VectorSearch.Inputs.IndexDedicatedInfrastructureAutoscalingSpecArgs
        {
            MaxReplicaCount = 0,
            MinReplicaCount = 0,
        },
        Mode = "string",
    },
    Project = "string",
    StoreFields = new[]
    {
        "string",
    },
});

    example, err := vectorsearch.NewIndex(ctx, "gcpIndexResource", &vectorsearch.IndexArgs{
	IndexField:   pulumi.String("string"),
	Location:     pulumi.String("string"),
	IndexId:      pulumi.String("string"),
	CollectionId: pulumi.String("string"),
	DenseScann: &vectorsearch.IndexDenseScannArgs{
		FeatureNormType: pulumi.String("string"),
	},
	DisplayName:    pulumi.String("string"),
	DistanceMetric: pulumi.String("string"),
	FilterFields: pulumi.StringArray{
		pulumi.String("string"),
	},
	Description:    pulumi.String("string"),
	DeletionPolicy: pulumi.String("string"),
	Labels: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	DedicatedInfrastructure: &vectorsearch.IndexDedicatedInfrastructureArgs{
		AutoscalingSpec: &vectorsearch.IndexDedicatedInfrastructureAutoscalingSpecArgs{
			MaxReplicaCount: pulumi.Int(0),
			MinReplicaCount: pulumi.Int(0),
		},
		Mode: pulumi.String("string"),
	},
	Project: pulumi.String("string"),
	StoreFields: pulumi.StringArray{
		pulumi.String("string"),
	},
})

    resource "gcp_vectorsearch_index" "gcpIndexResource" {
  lifecycle {
    create_before_destroy = true
  }
  index_field   = "string"
  location      = "string"
  index_id      = "string"
  collection_id = "string"
  dense_scann = {
    feature_norm_type = "string"
  }
  display_name    = "string"
  distance_metric = "string"
  filter_fields   = ["string"]
  description     = "string"
  deletion_policy = "string"
  labels = {
    "string" = "string"
  }
  dedicated_infrastructure = {
    autoscaling_spec = {
      max_replica_count = 0
      min_replica_count = 0
    }
    mode = "string"
  }
  project      = "string"
  store_fields = ["string"]
}

    var gcpIndexResource = new com.pulumi.gcp.vectorsearch.Index("gcpIndexResource", com.pulumi.gcp.vectorsearch.IndexArgs.builder()
    .indexField("string")
    .location("string")
    .indexId("string")
    .collectionId("string")
    .denseScann(IndexDenseScannArgs.builder()
        .featureNormType("string")
        .build())
    .displayName("string")
    .distanceMetric("string")
    .filterFields("string")
    .description("string")
    .deletionPolicy("string")
    .labels(Map.of("string", "string"))
    .dedicatedInfrastructure(IndexDedicatedInfrastructureArgs.builder()
        .autoscalingSpec(IndexDedicatedInfrastructureAutoscalingSpecArgs.builder()
            .maxReplicaCount(0)
            .minReplicaCount(0)
            .build())
        .mode("string")
        .build())
    .project("string")
    .storeFields("string")
    .build());

    gcp_index_resource = gcp.vectorsearch.Index("gcpIndexResource",
    index_field="string",
    location="string",
    index_id="string",
    collection_id="string",
    dense_scann={
        "feature_norm_type": "string",
    },
    display_name="string",
    distance_metric="string",
    filter_fields=["string"],
    description="string",
    deletion_policy="string",
    labels={
        "string": "string",
    },
    dedicated_infrastructure={
        "autoscaling_spec": {
            "max_replica_count": 0,
            "min_replica_count": 0,
        },
        "mode": "string",
    },
    project="string",
    store_fields=["string"])

    const gcpIndexResource = new gcp.vectorsearch.Index("gcpIndexResource", {
    indexField: "string",
    location: "string",
    indexId: "string",
    collectionId: "string",
    denseScann: {
        featureNormType: "string",
    },
    displayName: "string",
    distanceMetric: "string",
    filterFields: ["string"],
    description: "string",
    deletionPolicy: "string",
    labels: {
        string: "string",
    },
    dedicatedInfrastructure: {
        autoscalingSpec: {
            maxReplicaCount: 0,
            minReplicaCount: 0,
        },
        mode: "string",
    },
    project: "string",
    storeFields: ["string"],
});

    type: gcp:vectorsearch:Index
properties:
    collectionId: string
    dedicatedInfrastructure:
        autoscalingSpec:
            maxReplicaCount: 0
            minReplicaCount: 0
        mode: string
    deletionPolicy: string
    denseScann:
        featureNormType: string
    description: string
    displayName: string
    distanceMetric: string
    filterFields:
        - string
    indexField: string
    indexId: string
    labels:
        string: string
    location: string
    project: string
    storeFields:
        - string

    Index Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The Index resource accepts the following input properties:

    CollectionId string
    The ID of the parent Collection.
    IndexField string
    The collection schema field to index.
    IndexId string
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    Location string
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    DedicatedInfrastructure IndexDedicatedInfrastructure
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    DeletionPolicy string
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    DenseScann IndexDenseScann
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    Description string
    User-specified description of the index
    DisplayName string
    User-specified display name of the index
    DistanceMetric string
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    FilterFields List<string>
    The fields to push into the index to enable fast ANN inline filtering.
    Labels Dictionary<string, string>
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    StoreFields List<string>
    The fields to push into the index to enable inline data retrieval.
    CollectionId string
    The ID of the parent Collection.
    IndexField string
    The collection schema field to index.
    IndexId string
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    Location string
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    DedicatedInfrastructure IndexDedicatedInfrastructureArgs
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    DeletionPolicy string
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    DenseScann IndexDenseScannArgs
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    Description string
    User-specified description of the index
    DisplayName string
    User-specified display name of the index
    DistanceMetric string
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    FilterFields []string
    The fields to push into the index to enable fast ANN inline filtering.
    Labels map[string]string
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    StoreFields []string
    The fields to push into the index to enable inline data retrieval.
    collection_id string
    The ID of the parent Collection.
    index_field string
    The collection schema field to index.
    index_id string
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    location string
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    dedicated_infrastructure object
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    deletion_policy string
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    dense_scann object
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    description string
    User-specified description of the index
    display_name string
    User-specified display name of the index
    distance_metric string
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    filter_fields list(string)
    The fields to push into the index to enable fast ANN inline filtering.
    labels map(string)
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    store_fields list(string)
    The fields to push into the index to enable inline data retrieval.
    collectionId String
    The ID of the parent Collection.
    indexField String
    The collection schema field to index.
    indexId String
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    location String
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    dedicatedInfrastructure IndexDedicatedInfrastructure
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    deletionPolicy String
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    denseScann IndexDenseScann
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    description String
    User-specified description of the index
    displayName String
    User-specified display name of the index
    distanceMetric String
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    filterFields List<String>
    The fields to push into the index to enable fast ANN inline filtering.
    labels Map<String,String>
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    storeFields List<String>
    The fields to push into the index to enable inline data retrieval.
    collectionId string
    The ID of the parent Collection.
    indexField string
    The collection schema field to index.
    indexId string
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    location string
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    dedicatedInfrastructure IndexDedicatedInfrastructure
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    deletionPolicy string
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    denseScann IndexDenseScann
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    description string
    User-specified description of the index
    displayName string
    User-specified display name of the index
    distanceMetric string
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    filterFields string[]
    The fields to push into the index to enable fast ANN inline filtering.
    labels {[key: string]: string}
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    storeFields string[]
    The fields to push into the index to enable inline data retrieval.
    collection_id str
    The ID of the parent Collection.
    index_field str
    The collection schema field to index.
    index_id str
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    location str
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    dedicated_infrastructure IndexDedicatedInfrastructureArgs
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    deletion_policy str
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    dense_scann IndexDenseScannArgs
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    description str
    User-specified description of the index
    display_name str
    User-specified display name of the index
    distance_metric str
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    filter_fields Sequence[str]
    The fields to push into the index to enable fast ANN inline filtering.
    labels Mapping[str, str]
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    project str
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    store_fields Sequence[str]
    The fields to push into the index to enable inline data retrieval.
    collectionId String
    The ID of the parent Collection.
    indexField String
    The collection schema field to index.
    indexId String
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    location String
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    dedicatedInfrastructure Property Map
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    deletionPolicy String
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    denseScann Property Map
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    description String
    User-specified description of the index
    displayName String
    User-specified display name of the index
    distanceMetric String
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    filterFields List<String>
    The fields to push into the index to enable fast ANN inline filtering.
    labels Map<String>
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    storeFields List<String>
    The fields to push into the index to enable inline data retrieval.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the Index resource produces the following output properties:

    CreateTime string
    [Output only] Create time stamp
    EffectiveLabels Dictionary<string, string>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    Id string
    The provider-assigned unique ID for this managed resource.
    Name string
    Identifier. name of resource
    PulumiLabels Dictionary<string, string>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    UpdateTime string
    [Output only] Update time stamp
    CreateTime string
    [Output only] Create time stamp
    EffectiveLabels map[string]string
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    Id string
    The provider-assigned unique ID for this managed resource.
    Name string
    Identifier. name of resource
    PulumiLabels map[string]string
    The combination of labels configured directly on the resource and default labels configured on the provider.
    UpdateTime string
    [Output only] Update time stamp
    create_time string
    [Output only] Create time stamp
    effective_labels map(string)
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    id string
    The provider-assigned unique ID for this managed resource.
    name string
    Identifier. name of resource
    pulumi_labels map(string)
    The combination of labels configured directly on the resource and default labels configured on the provider.
    update_time string
    [Output only] Update time stamp
    createTime String
    [Output only] Create time stamp
    effectiveLabels Map<String,String>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    id String
    The provider-assigned unique ID for this managed resource.
    name String
    Identifier. name of resource
    pulumiLabels Map<String,String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    updateTime String
    [Output only] Update time stamp
    createTime string
    [Output only] Create time stamp
    effectiveLabels {[key: string]: string}
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    id string
    The provider-assigned unique ID for this managed resource.
    name string
    Identifier. name of resource
    pulumiLabels {[key: string]: string}
    The combination of labels configured directly on the resource and default labels configured on the provider.
    updateTime string
    [Output only] Update time stamp
    create_time str
    [Output only] Create time stamp
    effective_labels Mapping[str, str]
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    id str
    The provider-assigned unique ID for this managed resource.
    name str
    Identifier. name of resource
    pulumi_labels Mapping[str, str]
    The combination of labels configured directly on the resource and default labels configured on the provider.
    update_time str
    [Output only] Update time stamp
    createTime String
    [Output only] Create time stamp
    effectiveLabels Map<String>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    id String
    The provider-assigned unique ID for this managed resource.
    name String
    Identifier. name of resource
    pulumiLabels Map<String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    updateTime String
    [Output only] Update time stamp

    Look up Existing Index Resource

    Get an existing Index resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

    public static get(name: string, id: Input<ID>, state?: IndexState, opts?: CustomResourceOptions): Index
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        collection_id: Optional[str] = None,
        create_time: Optional[str] = None,
        dedicated_infrastructure: Optional[IndexDedicatedInfrastructureArgs] = None,
        deletion_policy: Optional[str] = None,
        dense_scann: Optional[IndexDenseScannArgs] = None,
        description: Optional[str] = None,
        display_name: Optional[str] = None,
        distance_metric: Optional[str] = None,
        effective_labels: Optional[Mapping[str, str]] = None,
        filter_fields: Optional[Sequence[str]] = None,
        index_field: Optional[str] = None,
        index_id: Optional[str] = None,
        labels: Optional[Mapping[str, str]] = None,
        location: Optional[str] = None,
        name: Optional[str] = None,
        project: Optional[str] = None,
        pulumi_labels: Optional[Mapping[str, str]] = None,
        store_fields: Optional[Sequence[str]] = None,
        update_time: Optional[str] = None) -> Index
    func GetIndex(ctx *Context, name string, id IDInput, state *IndexState, opts ...ResourceOption) (*Index, error)
    public static Index Get(string name, Input<string> id, IndexState? state, CustomResourceOptions? opts = null)
    public static Index get(String name, Output<String> id, IndexState state, CustomResourceOptions options)
    resources:  _:    type: gcp:vectorsearch:Index    get:      id: ${id}
    import {
  to = gcp_vectorsearch_index.example
  id = "${id}"
}
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    resource_name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    The following state arguments are supported:
    CollectionId string
    The ID of the parent Collection.
    CreateTime string
    [Output only] Create time stamp
    DedicatedInfrastructure IndexDedicatedInfrastructure
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    DeletionPolicy string
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    DenseScann IndexDenseScann
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    Description string
    User-specified description of the index
    DisplayName string
    User-specified display name of the index
    DistanceMetric string
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    EffectiveLabels Dictionary<string, string>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    FilterFields List<string>
    The fields to push into the index to enable fast ANN inline filtering.
    IndexField string
    The collection schema field to index.
    IndexId string
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    Labels Dictionary<string, string>
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    Location string
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    Name string
    Identifier. name of resource
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    PulumiLabels Dictionary<string, string>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    StoreFields List<string>
    The fields to push into the index to enable inline data retrieval.
    UpdateTime string
    [Output only] Update time stamp
    CollectionId string
    The ID of the parent Collection.
    CreateTime string
    [Output only] Create time stamp
    DedicatedInfrastructure IndexDedicatedInfrastructureArgs
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    DeletionPolicy string
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    DenseScann IndexDenseScannArgs
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    Description string
    User-specified description of the index
    DisplayName string
    User-specified display name of the index
    DistanceMetric string
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    EffectiveLabels map[string]string
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    FilterFields []string
    The fields to push into the index to enable fast ANN inline filtering.
    IndexField string
    The collection schema field to index.
    IndexId string
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    Labels map[string]string
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    Location string
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    Name string
    Identifier. name of resource
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    PulumiLabels map[string]string
    The combination of labels configured directly on the resource and default labels configured on the provider.
    StoreFields []string
    The fields to push into the index to enable inline data retrieval.
    UpdateTime string
    [Output only] Update time stamp
    collection_id string
    The ID of the parent Collection.
    create_time string
    [Output only] Create time stamp
    dedicated_infrastructure object
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    deletion_policy string
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    dense_scann object
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    description string
    User-specified description of the index
    display_name string
    User-specified display name of the index
    distance_metric string
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    effective_labels map(string)
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    filter_fields list(string)
    The fields to push into the index to enable fast ANN inline filtering.
    index_field string
    The collection schema field to index.
    index_id string
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    labels map(string)
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    location string
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    name string
    Identifier. name of resource
    project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumi_labels map(string)
    The combination of labels configured directly on the resource and default labels configured on the provider.
    store_fields list(string)
    The fields to push into the index to enable inline data retrieval.
    update_time string
    [Output only] Update time stamp
    collectionId String
    The ID of the parent Collection.
    createTime String
    [Output only] Create time stamp
    dedicatedInfrastructure IndexDedicatedInfrastructure
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    deletionPolicy String
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    denseScann IndexDenseScann
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    description String
    User-specified description of the index
    displayName String
    User-specified display name of the index
    distanceMetric String
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    effectiveLabels Map<String,String>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    filterFields List<String>
    The fields to push into the index to enable fast ANN inline filtering.
    indexField String
    The collection schema field to index.
    indexId String
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    labels Map<String,String>
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    location String
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    name String
    Identifier. name of resource
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumiLabels Map<String,String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    storeFields List<String>
    The fields to push into the index to enable inline data retrieval.
    updateTime String
    [Output only] Update time stamp
    collectionId string
    The ID of the parent Collection.
    createTime string
    [Output only] Create time stamp
    dedicatedInfrastructure IndexDedicatedInfrastructure
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    deletionPolicy string
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    denseScann IndexDenseScann
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    description string
    User-specified description of the index
    displayName string
    User-specified display name of the index
    distanceMetric string
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    effectiveLabels {[key: string]: string}
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    filterFields string[]
    The fields to push into the index to enable fast ANN inline filtering.
    indexField string
    The collection schema field to index.
    indexId string
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    labels {[key: string]: string}
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    location string
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    name string
    Identifier. name of resource
    project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumiLabels {[key: string]: string}
    The combination of labels configured directly on the resource and default labels configured on the provider.
    storeFields string[]
    The fields to push into the index to enable inline data retrieval.
    updateTime string
    [Output only] Update time stamp
    collection_id str
    The ID of the parent Collection.
    create_time str
    [Output only] Create time stamp
    dedicated_infrastructure IndexDedicatedInfrastructureArgs
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    deletion_policy str
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    dense_scann IndexDenseScannArgs
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    description str
    User-specified description of the index
    display_name str
    User-specified display name of the index
    distance_metric str
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    effective_labels Mapping[str, str]
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    filter_fields Sequence[str]
    The fields to push into the index to enable fast ANN inline filtering.
    index_field str
    The collection schema field to index.
    index_id str
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    labels Mapping[str, str]
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    location str
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    name str
    Identifier. name of resource
    project str
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumi_labels Mapping[str, str]
    The combination of labels configured directly on the resource and default labels configured on the provider.
    store_fields Sequence[str]
    The fields to push into the index to enable inline data retrieval.
    update_time str
    [Output only] Update time stamp
    collectionId String
    The ID of the parent Collection.
    createTime String
    [Output only] Create time stamp
    dedicatedInfrastructure Property Map
    Dedicated infrastructure for the index. This field belongs to the infraType oneof; if omitted, the server populates it with the default PERFORMANCE_OPTIMIZED mode and an autoscaling spec of min_replica_count=2, max_replica_count=2. Structure is documented below.
    deletionPolicy String
    Whether Terraform will be prevented from destroying the resource. Defaults to DELETE. When a 'terraform destroy' or 'pulumi up' would delete the resource, the command will fail if this field is set to "PREVENT" in Terraform state. When set to "ABANDON", the command will remove the resource from Terraform management without updating or deleting the resource in the API. When set to "DELETE", deleting the resource is allowed.
    denseScann Property Map
    Dense ScaNN index configuration. This field belongs to the indexType oneof; if omitted, the server populates it with default ScaNN settings. Structure is documented below.
    description String
    User-specified description of the index
    displayName String
    User-specified display name of the index
    distanceMetric String
    Distance metric used for indexing. If not specified, will default to DOT_PRODUCT. Possible values are: DOT_PRODUCT, COSINE_DISTANCE.
    effectiveLabels Map<String>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    filterFields List<String>
    The fields to push into the index to enable fast ANN inline filtering.
    indexField String
    The collection schema field to index.
    indexId String
    ID of the Index to create. The id must be 1-63 characters long, and comply with RFC1035. Specifically, it must be 1-63 characters long and match the regular expression a-z?.
    labels Map<String>
    Labels as key value pairs. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effectiveLabels for all of the labels present on the resource.
    location String
    Resource ID segment making up resource name. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
    name String
    Identifier. name of resource
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumiLabels Map<String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    storeFields List<String>
    The fields to push into the index to enable inline data retrieval.
    updateTime String
    [Output only] Update time stamp

    Supporting Types

    IndexDedicatedInfrastructure, IndexDedicatedInfrastructureArgs

    AutoscalingSpec IndexDedicatedInfrastructureAutoscalingSpec
    Autoscaling specification. Structure is documented below.
    Mode string
    Mode of the dedicated infrastructure. Defaults to PERFORMANCE_OPTIMIZED. Possible values are: MODE_UNSPECIFIED, STORAGE_OPTIMIZED, PERFORMANCE_OPTIMIZED.
    AutoscalingSpec IndexDedicatedInfrastructureAutoscalingSpec
    Autoscaling specification. Structure is documented below.
    Mode string
    Mode of the dedicated infrastructure. Defaults to PERFORMANCE_OPTIMIZED. Possible values are: MODE_UNSPECIFIED, STORAGE_OPTIMIZED, PERFORMANCE_OPTIMIZED.
    autoscaling_spec object
    Autoscaling specification. Structure is documented below.
    mode string
    Mode of the dedicated infrastructure. Defaults to PERFORMANCE_OPTIMIZED. Possible values are: MODE_UNSPECIFIED, STORAGE_OPTIMIZED, PERFORMANCE_OPTIMIZED.
    autoscalingSpec IndexDedicatedInfrastructureAutoscalingSpec
    Autoscaling specification. Structure is documented below.
    mode String
    Mode of the dedicated infrastructure. Defaults to PERFORMANCE_OPTIMIZED. Possible values are: MODE_UNSPECIFIED, STORAGE_OPTIMIZED, PERFORMANCE_OPTIMIZED.
    autoscalingSpec IndexDedicatedInfrastructureAutoscalingSpec
    Autoscaling specification. Structure is documented below.
    mode string
    Mode of the dedicated infrastructure. Defaults to PERFORMANCE_OPTIMIZED. Possible values are: MODE_UNSPECIFIED, STORAGE_OPTIMIZED, PERFORMANCE_OPTIMIZED.
    autoscaling_spec IndexDedicatedInfrastructureAutoscalingSpec
    Autoscaling specification. Structure is documented below.
    mode str
    Mode of the dedicated infrastructure. Defaults to PERFORMANCE_OPTIMIZED. Possible values are: MODE_UNSPECIFIED, STORAGE_OPTIMIZED, PERFORMANCE_OPTIMIZED.
    autoscalingSpec Property Map
    Autoscaling specification. Structure is documented below.
    mode String
    Mode of the dedicated infrastructure. Defaults to PERFORMANCE_OPTIMIZED. Possible values are: MODE_UNSPECIFIED, STORAGE_OPTIMIZED, PERFORMANCE_OPTIMIZED.

    IndexDedicatedInfrastructureAutoscalingSpec, IndexDedicatedInfrastructureAutoscalingSpecArgs

    MaxReplicaCount int
    The maximum number of replicas. Must be >= minReplicaCount and <= 1000. If not set or set to 0, defaults to the greater of minReplicaCount and 2 (or 5 for the v1beta version).
    MinReplicaCount int
    The minimum number of replicas. If not set or set to 0, defaults to 2. Must be >= 1 and <= 1000.
    MaxReplicaCount int
    The maximum number of replicas. Must be >= minReplicaCount and <= 1000. If not set or set to 0, defaults to the greater of minReplicaCount and 2 (or 5 for the v1beta version).
    MinReplicaCount int
    The minimum number of replicas. If not set or set to 0, defaults to 2. Must be >= 1 and <= 1000.
    max_replica_count number
    The maximum number of replicas. Must be >= minReplicaCount and <= 1000. If not set or set to 0, defaults to the greater of minReplicaCount and 2 (or 5 for the v1beta version).
    min_replica_count number
    The minimum number of replicas. If not set or set to 0, defaults to 2. Must be >= 1 and <= 1000.
    maxReplicaCount Integer
    The maximum number of replicas. Must be >= minReplicaCount and <= 1000. If not set or set to 0, defaults to the greater of minReplicaCount and 2 (or 5 for the v1beta version).
    minReplicaCount Integer
    The minimum number of replicas. If not set or set to 0, defaults to 2. Must be >= 1 and <= 1000.
    maxReplicaCount number
    The maximum number of replicas. Must be >= minReplicaCount and <= 1000. If not set or set to 0, defaults to the greater of minReplicaCount and 2 (or 5 for the v1beta version).
    minReplicaCount number
    The minimum number of replicas. If not set or set to 0, defaults to 2. Must be >= 1 and <= 1000.
    max_replica_count int
    The maximum number of replicas. Must be >= minReplicaCount and <= 1000. If not set or set to 0, defaults to the greater of minReplicaCount and 2 (or 5 for the v1beta version).
    min_replica_count int
    The minimum number of replicas. If not set or set to 0, defaults to 2. Must be >= 1 and <= 1000.
    maxReplicaCount Number
    The maximum number of replicas. Must be >= minReplicaCount and <= 1000. If not set or set to 0, defaults to the greater of minReplicaCount and 2 (or 5 for the v1beta version).
    minReplicaCount Number
    The minimum number of replicas. If not set or set to 0, defaults to 2. Must be >= 1 and <= 1000.

    IndexDenseScann, IndexDenseScannArgs

    FeatureNormType string
    Feature norm type for the ScaNN index. Possible values are: FEATURE_NORM_TYPE_UNSPECIFIED, NONE, UNIT_L2_NORM.
    FeatureNormType string
    Feature norm type for the ScaNN index. Possible values are: FEATURE_NORM_TYPE_UNSPECIFIED, NONE, UNIT_L2_NORM.
    feature_norm_type string
    Feature norm type for the ScaNN index. Possible values are: FEATURE_NORM_TYPE_UNSPECIFIED, NONE, UNIT_L2_NORM.
    featureNormType String
    Feature norm type for the ScaNN index. Possible values are: FEATURE_NORM_TYPE_UNSPECIFIED, NONE, UNIT_L2_NORM.
    featureNormType string
    Feature norm type for the ScaNN index. Possible values are: FEATURE_NORM_TYPE_UNSPECIFIED, NONE, UNIT_L2_NORM.
    feature_norm_type str
    Feature norm type for the ScaNN index. Possible values are: FEATURE_NORM_TYPE_UNSPECIFIED, NONE, UNIT_L2_NORM.
    featureNormType String
    Feature norm type for the ScaNN index. Possible values are: FEATURE_NORM_TYPE_UNSPECIFIED, NONE, UNIT_L2_NORM.

    Import

    Index can be imported using any of these accepted formats:

    • projects/{{project}}/locations/{{location}}/collections/{{collection_id}}/indexes/{{index_id}}
    • {{project}}/{{location}}/{{collection_id}}/{{index_id}}
    • {{location}}/{{collection_id}}/{{index_id}}

    When using the pulumi import command, Index can be imported using one of the formats above. For example:

    $ pulumi import gcp:vectorsearch/index:Index default projects/{{project}}/locations/{{location}}/collections/{{collection_id}}/indexes/{{index_id}}
$ pulumi import gcp:vectorsearch/index:Index default {{project}}/{{location}}/{{collection_id}}/{{index_id}}
$ pulumi import gcp:vectorsearch/index:Index default {{location}}/{{collection_id}}/{{index_id}}

    To learn more about importing existing cloud resources, see Importing resources.

    Package Details

    Repository
    Google Cloud (GCP) Classic pulumi/pulumi-gcp
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the google-beta Terraform Provider.
    gcp logo
    Viewing docs for Google Cloud v9.32.1
    published on Wednesday, Jul 29, 2026 by Pulumi
    Schema (JSON)
    pulumi/pulumi-gcp

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