---
title: Getting Started with Datadog
description: Datadog, the leading service for cloud-scale monitoring.
breadcrumbs: Docs > Infrastructure > Datadog Resource Catalog
---

# aws_bedrock_knowledge_base{% #aws_bedrock_knowledge_base %}

## `account_id`{% #account_id %}

**Type**: `STRING`

## `created_at`{% #created_at %}

**Type**: `TIMESTAMP`**Provider name**: `createdAt`**Description**: The time the knowledge base was created.

## `description`{% #description %}

**Type**: `STRING`**Provider name**: `description`**Description**: The description of the knowledge base.

## `failure_reasons`{% #failure_reasons %}

**Type**: `UNORDERED_LIST_STRING`**Provider name**: `failureReasons`**Description**: A list of reasons that the API operation on the knowledge base failed.

## `knowledge_base_arn`{% #knowledge_base_arn %}

**Type**: `STRING`**Provider name**: `knowledgeBaseArn`**Description**: The Amazon Resource Name (ARN) of the knowledge base.

## `knowledge_base_configuration`{% #knowledge_base_configuration %}

**Type**: `STRUCT`**Provider name**: `knowledgeBaseConfiguration`**Description**: Contains details about the embeddings configuration of the knowledge base.

- `kendra_knowledge_base_configuration`**Type**: `STRUCT`**Provider name**: `kendraKnowledgeBaseConfiguration`**Description**: Settings for an Amazon Kendra knowledge base.
  - `kendra_index_arn`**Type**: `STRING`**Provider name**: `kendraIndexArn`**Description**: The ARN of the Amazon Kendra index.
- `sql_knowledge_base_configuration`**Type**: `STRUCT`**Provider name**: `sqlKnowledgeBaseConfiguration`**Description**: Specifies configurations for a knowledge base connected to an SQL database.
  - `redshift_configuration`**Type**: `STRUCT`**Provider name**: `redshiftConfiguration`**Description**: Specifies configurations for a knowledge base connected to an Amazon Redshift database.
    - `query_engine_configuration`**Type**: `STRUCT`**Provider name**: `queryEngineConfiguration`**Description**: Specifies configurations for an Amazon Redshift query engine.
      - `provisioned_configuration`**Type**: `STRUCT`**Provider name**: `provisionedConfiguration`**Description**: Specifies configurations for a provisioned Amazon Redshift query engine.
        - `auth_configuration`**Type**: `STRUCT`**Provider name**: `authConfiguration`**Description**: Specifies configurations for authentication to Amazon Redshift.
          - `database_user`**Type**: `STRING`**Provider name**: `databaseUser`**Description**: The database username for authentication to an Amazon Redshift provisioned data warehouse.
          - `type`**Type**: `STRING`**Provider name**: `type`**Description**: The type of authentication to use.
          - `username_password_secret_arn`**Type**: `STRING`**Provider name**: `usernamePasswordSecretArn`**Description**: The ARN of an Secrets Manager secret for authentication.
        - `cluster_identifier`**Type**: `STRING`**Provider name**: `clusterIdentifier`**Description**: The ID of the Amazon Redshift cluster.
      - `serverless_configuration`**Type**: `STRUCT`**Provider name**: `serverlessConfiguration`**Description**: Specifies configurations for a serverless Amazon Redshift query engine.
        - `auth_configuration`**Type**: `STRUCT`**Provider name**: `authConfiguration`**Description**: Specifies configurations for authentication to an Amazon Redshift provisioned data warehouse.
          - `type`**Type**: `STRING`**Provider name**: `type`**Description**: The type of authentication to use.
          - `username_password_secret_arn`**Type**: `STRING`**Provider name**: `usernamePasswordSecretArn`**Description**: The ARN of an Secrets Manager secret for authentication.
        - `workgroup_arn`**Type**: `STRING`**Provider name**: `workgroupArn`**Description**: The ARN of the Amazon Redshift workgroup.
      - `type`**Type**: `STRING`**Provider name**: `type`**Description**: The type of query engine.
    - `query_generation_configuration`**Type**: `STRUCT`**Provider name**: `queryGenerationConfiguration`**Description**: Specifies configurations for generating queries.
      - `execution_timeout_seconds`**Type**: `INT32`**Provider name**: `executionTimeoutSeconds`**Description**: The time after which query generation will time out.
      - `generation_context`**Type**: `STRUCT`**Provider name**: `generationContext`**Description**: Specifies configurations for context to use during query generation.
        - `curated_queries`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `curatedQueries`**Description**: An array of objects, each of which defines information about example queries to help the query engine generate appropriate SQL queries.
          - `natural_language`**Type**: `STRING`**Provider name**: `naturalLanguage`**Description**: An example natural language query.
          - `sql`**Type**: `STRING`**Provider name**: `sql`**Description**: The SQL equivalent of the natural language query.
        - `tables`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `tables`**Description**: An array of objects, each of which defines information about a table in the database.
          - `columns`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `columns`**Description**: An array of objects, each of which defines information about a column in the table.
            - `description`**Type**: `STRING`**Provider name**: `description`**Description**: A description of the column that helps the query engine understand the contents of the column.
            - `inclusion`**Type**: `STRING`**Provider name**: `inclusion`**Description**: Specifies whether to include or exclude the column during query generation. If you specify `EXCLUDE`, the column will be ignored. If you specify `INCLUDE`, all other columns in the table will be ignored.
            - `name`**Type**: `STRING`**Provider name**: `name`**Description**: The name of the column for which the other fields in this object apply.
          - `description`**Type**: `STRING`**Provider name**: `description`**Description**: A description of the table that helps the query engine understand the contents of the table.
          - `inclusion`**Type**: `STRING`**Provider name**: `inclusion`**Description**: Specifies whether to include or exclude the table during query generation. If you specify `EXCLUDE`, the table will be ignored. If you specify `INCLUDE`, all other tables will be ignored.
          - `name`**Type**: `STRING`**Provider name**: `name`**Description**: The name of the table for which the other fields in this object apply.
    - `storage_configurations`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `storageConfigurations`**Description**: Specifies configurations for Amazon Redshift database storage.
      - `aws_data_catalog_configuration`**Type**: `STRUCT`**Provider name**: `awsDataCatalogConfiguration`**Description**: Specifies configurations for storage in Glue Data Catalog.
        - `table_names`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `tableNames`**Description**: A list of names of the tables to use.
      - `redshift_configuration`**Type**: `STRUCT`**Provider name**: `redshiftConfiguration`**Description**: Specifies configurations for storage in Amazon Redshift.
        - `database_name`**Type**: `STRING`**Provider name**: `databaseName`**Description**: The name of the Amazon Redshift database.
      - `type`**Type**: `STRING`**Provider name**: `type`**Description**: The data storage service to use.
  - `type`**Type**: `STRING`**Provider name**: `type`**Description**: The type of SQL database to connect to the knowledge base.
- `type`**Type**: `STRING`**Provider name**: `type`**Description**: The type of data that the data source is converted into for the knowledge base.
- `vector_knowledge_base_configuration`**Type**: `STRUCT`**Provider name**: `vectorKnowledgeBaseConfiguration`**Description**: Contains details about the model that's used to convert the data source into vector embeddings.
  - `embedding_model_arn`**Type**: `STRING`**Provider name**: `embeddingModelArn`**Description**: The Amazon Resource Name (ARN) of the model used to create vector embeddings for the knowledge base.
  - `embedding_model_configuration`**Type**: `STRUCT`**Provider name**: `embeddingModelConfiguration`**Description**: The embeddings model configuration details for the vector model used in Knowledge Base.
    - `bedrock_embedding_model_configuration`**Type**: `STRUCT`**Provider name**: `bedrockEmbeddingModelConfiguration`**Description**: The vector configuration details on the Bedrock embeddings model.
      - `dimensions`**Type**: `INT32`**Provider name**: `dimensions`**Description**: The dimensions details for the vector configuration used on the Bedrock embeddings model.
      - `embedding_data_type`**Type**: `STRING`**Provider name**: `embeddingDataType`**Description**: The data type for the vectors when using a model to convert text into vector embeddings. The model must support the specified data type for vector embeddings. Floating-point (float32) is the default data type, and is supported by most models for vector embeddings. See [Supported embeddings models](https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base-supported.html) for information on the available models and their vector data types.
  - `supplemental_data_storage_configuration`**Type**: `STRUCT`**Provider name**: `supplementalDataStorageConfiguration`**Description**: If you include multimodal data from your data source, use this object to specify configurations for the storage location of the images extracted from your documents. These images can be retrieved and returned to the end user. They can also be used in generation when using [RetrieveAndGenerate](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_agent-runtime_RetrieveAndGenerate.html).
    - `storage_locations`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `storageLocations`**Description**: A list of objects specifying storage locations for images extracted from multimodal documents in your data source.
      - `s3_location`**Type**: `STRUCT`**Provider name**: `s3Location`**Description**: Contains information about the Amazon S3 location for the extracted images.
        - `uri`**Type**: `STRING`**Provider name**: `uri`**Description**: The location's URI. For example, `s3://my-bucket/chunk-processor/`.
      - `type`**Type**: `STRING`**Provider name**: `type`**Description**: Specifies the storage service used for this location.

## `knowledge_base_id`{% #knowledge_base_id %}

**Type**: `STRING`**Provider name**: `knowledgeBaseId`**Description**: The unique identifier of the knowledge base.

## `name`{% #name %}

**Type**: `STRING`**Provider name**: `name`**Description**: The name of the knowledge base.

## `role_arn`{% #role_arn %}

**Type**: `STRING`**Provider name**: `roleArn`**Description**: The Amazon Resource Name (ARN) of the IAM role with permissions to invoke API operations on the knowledge base.

## `status`{% #status %}

**Type**: `STRING`**Provider name**: `status`**Description**: The status of the knowledge base. The following statuses are possible:

- CREATING – The knowledge base is being created.
- ACTIVE – The knowledge base is ready to be queried.
- DELETING – The knowledge base is being deleted.
- UPDATING – The knowledge base is being updated.
- FAILED – The knowledge base API operation failed.



## `storage_configuration`{% #storage_configuration %}

**Type**: `STRUCT`**Provider name**: `storageConfiguration`**Description**: Contains details about the storage configuration of the knowledge base.

- `mongo_db_atlas_configuration`**Type**: `STRUCT`**Provider name**: `mongoDbAtlasConfiguration`**Description**: Contains the storage configuration of the knowledge base in MongoDB Atlas.
  - `collection_name`**Type**: `STRING`**Provider name**: `collectionName`**Description**: The collection name of the knowledge base in MongoDB Atlas.
  - `credentials_secret_arn`**Type**: `STRING`**Provider name**: `credentialsSecretArn`**Description**: The Amazon Resource Name (ARN) of the secret that you created in Secrets Manager that contains user credentials for your MongoDB Atlas cluster.
  - `database_name`**Type**: `STRING`**Provider name**: `databaseName`**Description**: The database name in your MongoDB Atlas cluster for your knowledge base.
  - `endpoint`**Type**: `STRING`**Provider name**: `endpoint`**Description**: The endpoint URL of your MongoDB Atlas cluster for your knowledge base.
  - `endpoint_service_name`**Type**: `STRING`**Provider name**: `endpointServiceName`**Description**: The name of the VPC endpoint service in your account that is connected to your MongoDB Atlas cluster.
  - `field_mapping`**Type**: `STRUCT`**Provider name**: `fieldMapping`**Description**: Contains the names of the fields to which to map information about the vector store.
    - `metadata_field`**Type**: `STRING`**Provider name**: `metadataField`**Description**: The name of the field in which Amazon Bedrock stores metadata about the vector store.
    - `text_field`**Type**: `STRING`**Provider name**: `textField`**Description**: The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.
    - `vector_field`**Type**: `STRING`**Provider name**: `vectorField`**Description**: The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.
  - `text_index_name`**Type**: `STRING`**Provider name**: `textIndexName`**Description**: The name of the text search index in the MongoDB collection. This is required for using the hybrid search feature.
  - `vector_index_name`**Type**: `STRING`**Provider name**: `vectorIndexName`**Description**: The name of the MongoDB Atlas vector search index.
- `neptune_analytics_configuration`**Type**: `STRUCT`**Provider name**: `neptuneAnalyticsConfiguration`**Description**: Contains details about the Neptune Analytics configuration of the knowledge base in Amazon Neptune. For more information, see [Create a vector index in Amazon Neptune Analytics.](https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base-setup-neptune.html).
  - `field_mapping`**Type**: `STRUCT`**Provider name**: `fieldMapping`**Description**: Contains the names of the fields to which to map information about the vector store.
    - `metadata_field`**Type**: `STRING`**Provider name**: `metadataField`**Description**: The name of the field in which Amazon Bedrock stores metadata about the vector store.
    - `text_field`**Type**: `STRING`**Provider name**: `textField`**Description**: The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.
  - `graph_arn`**Type**: `STRING`**Provider name**: `graphArn`**Description**: The Amazon Resource Name (ARN) of the Neptune Analytics vector store.
- `opensearch_managed_cluster_configuration`**Type**: `STRUCT`**Provider name**: `opensearchManagedClusterConfiguration`**Description**: Contains details about the storage configuration of the knowledge base in OpenSearch Managed Cluster. For more information, see [Create a vector index in Amazon OpenSearch Service](https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base-setup-osm.html).
  - `domain_arn`**Type**: `STRING`**Provider name**: `domainArn`**Description**: The Amazon Resource Name (ARN) of the OpenSearch domain.
  - `domain_endpoint`**Type**: `STRING`**Provider name**: `domainEndpoint`**Description**: The endpoint URL the OpenSearch domain.
  - `field_mapping`**Type**: `STRUCT`**Provider name**: `fieldMapping`**Description**: Contains the names of the fields to which to map information about the vector store.
    - `metadata_field`**Type**: `STRING`**Provider name**: `metadataField`**Description**: The name of the field in which Amazon Bedrock stores metadata about the vector store.
    - `text_field`**Type**: `STRING`**Provider name**: `textField`**Description**: The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.
    - `vector_field`**Type**: `STRING`**Provider name**: `vectorField`**Description**: The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.
  - `vector_index_name`**Type**: `STRING`**Provider name**: `vectorIndexName`**Description**: The name of the vector store.
- `opensearch_serverless_configuration`**Type**: `STRUCT`**Provider name**: `opensearchServerlessConfiguration`**Description**: Contains the storage configuration of the knowledge base in Amazon OpenSearch Service.
  - `collection_arn`**Type**: `STRING`**Provider name**: `collectionArn`**Description**: The Amazon Resource Name (ARN) of the OpenSearch Service vector store.
  - `field_mapping`**Type**: `STRUCT`**Provider name**: `fieldMapping`**Description**: Contains the names of the fields to which to map information about the vector store.
    - `metadata_field`**Type**: `STRING`**Provider name**: `metadataField`**Description**: The name of the field in which Amazon Bedrock stores metadata about the vector store.
    - `text_field`**Type**: `STRING`**Provider name**: `textField`**Description**: The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.
    - `vector_field`**Type**: `STRING`**Provider name**: `vectorField`**Description**: The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.
  - `vector_index_name`**Type**: `STRING`**Provider name**: `vectorIndexName`**Description**: The name of the vector store.
- `pinecone_configuration`**Type**: `STRUCT`**Provider name**: `pineconeConfiguration`**Description**: Contains the storage configuration of the knowledge base in Pinecone.
  - `connection_string`**Type**: `STRING`**Provider name**: `connectionString`**Description**: The endpoint URL for your index management page.
  - `credentials_secret_arn`**Type**: `STRING`**Provider name**: `credentialsSecretArn`**Description**: The Amazon Resource Name (ARN) of the secret that you created in Secrets Manager that is linked to your Pinecone API key.
  - `field_mapping`**Type**: `STRUCT`**Provider name**: `fieldMapping`**Description**: Contains the names of the fields to which to map information about the vector store.
    - `metadata_field`**Type**: `STRING`**Provider name**: `metadataField`**Description**: The name of the field in which Amazon Bedrock stores metadata about the vector store.
    - `text_field`**Type**: `STRING`**Provider name**: `textField`**Description**: The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.
  - `namespace`**Type**: `STRING`**Provider name**: `namespace`**Description**: The namespace to be used to write new data to your database.
- `rds_configuration`**Type**: `STRUCT`**Provider name**: `rdsConfiguration`**Description**: Contains details about the storage configuration of the knowledge base in Amazon RDS. For more information, see [Create a vector index in Amazon RDS](https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base-setup-rds.html).
  - `credentials_secret_arn`**Type**: `STRING`**Provider name**: `credentialsSecretArn`**Description**: The Amazon Resource Name (ARN) of the secret that you created in Secrets Manager that is linked to your Amazon RDS database.
  - `database_name`**Type**: `STRING`**Provider name**: `databaseName`**Description**: The name of your Amazon RDS database.
  - `field_mapping`**Type**: `STRUCT`**Provider name**: `fieldMapping`**Description**: Contains the names of the fields to which to map information about the vector store.
    - `custom_metadata_field`**Type**: `STRING`**Provider name**: `customMetadataField`**Description**: Provide a name for the universal metadata field where Amazon Bedrock will store any custom metadata from your data source.
    - `metadata_field`**Type**: `STRING`**Provider name**: `metadataField`**Description**: The name of the field in which Amazon Bedrock stores metadata about the vector store.
    - `primary_key_field`**Type**: `STRING`**Provider name**: `primaryKeyField`**Description**: The name of the field in which Amazon Bedrock stores the ID for each entry.
    - `text_field`**Type**: `STRING`**Provider name**: `textField`**Description**: The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.
    - `vector_field`**Type**: `STRING`**Provider name**: `vectorField`**Description**: The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.
  - `resource_arn`**Type**: `STRING`**Provider name**: `resourceArn`**Description**: The Amazon Resource Name (ARN) of the vector store.
  - `table_name`**Type**: `STRING`**Provider name**: `tableName`**Description**: The name of the table in the database.
- `redis_enterprise_cloud_configuration`**Type**: `STRUCT`**Provider name**: `redisEnterpriseCloudConfiguration`**Description**: Contains the storage configuration of the knowledge base in Redis Enterprise Cloud.
  - `credentials_secret_arn`**Type**: `STRING`**Provider name**: `credentialsSecretArn`**Description**: The Amazon Resource Name (ARN) of the secret that you created in Secrets Manager that is linked to your Redis Enterprise Cloud database.
  - `endpoint`**Type**: `STRING`**Provider name**: `endpoint`**Description**: The endpoint URL of the Redis Enterprise Cloud database.
  - `field_mapping`**Type**: `STRUCT`**Provider name**: `fieldMapping`**Description**: Contains the names of the fields to which to map information about the vector store.
    - `metadata_field`**Type**: `STRING`**Provider name**: `metadataField`**Description**: The name of the field in which Amazon Bedrock stores metadata about the vector store.
    - `text_field`**Type**: `STRING`**Provider name**: `textField`**Description**: The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.
    - `vector_field`**Type**: `STRING`**Provider name**: `vectorField`**Description**: The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.
  - `vector_index_name`**Type**: `STRING`**Provider name**: `vectorIndexName`**Description**: The name of the vector index.
- `type`**Type**: `STRING`**Provider name**: `type`**Description**: The vector store service in which the knowledge base is stored.

## `tags`{% #tags %}

**Type**: `UNORDERED_LIST_STRING`

## `updated_at`{% #updated_at %}

**Type**: `TIMESTAMP`**Provider name**: `updatedAt`**Description**: The time the knowledge base was last updated.