Amazon OpenSearch Serverless

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Overview

Amazon OpenSearch Serverless is an on-demand serverless configuration for OpenSearch, providing an easy way to query and analyze large volumes of data. OpenSearch Serverless collections provide the same benefits as self-managed clusters, without the added complexity of configuration and tuning.

Vector search collections are specifically designed for high-performance similarity searches in machine learning (ML) and artificial intelligence (AI) applications, and can be used to automatically create knowledge bases on Bedrock.

Setup

Installation

If you haven’t already, set up the Amazon Web Services integration first.

Configuration

In the AWS integration page, ensure that OpenSearch Serverless is enabled under the Metric Collection tab.
Install the Datadog - Amazon OpenSearch Serverless integration.

Data Collected

Metrics

aws.aoss.2xx (count)	The number of 2XX requests to the collection. Shown as request
aws.aoss.3xx (count)	The number of 3XX requests to the collection. Shown as request
aws.aoss.4xx (count)	The number of 4XX requests to the collection. Shown as request
aws.aoss.5xx (count)	The number of 5XX requests to the collection. Shown as request
aws.aoss.active_collection (gauge)	Indicates whether a collection is active. A value of 1 means that the collection is in an ACTIVE state. This value is emitted upon successful creation of a collection and remains 1 until you delete the collection. The metric can't have a value of 0.
aws.aoss.deleted_documents (count)	The total number of deleted documents.
aws.aoss.indexing_ocu (count)	The number of OpenSearch Compute Units (OCUs) used to ingest collection data. This metric applies at the account level.
aws.aoss.ingestion_data_rate (rate)	The indexing rate in GiB per second to a collection or index. This metric only applies to bulk indexing requests. Shown as gibibyte
aws.aoss.ingestion_document_errors (count)	The total number of document errors during ingestion for a collection or index. After a successful bulk indexing request, writers process the request and emit errors for all failed documents within the request. Shown as error
aws.aoss.ingestion_document_rate (rate)	The rate per second at which documents are being ingested to a collection or index. This metric only applies to bulk indexing requests.
aws.aoss.ingestion_request_errors (count)	The total number of bulk indexing request errors to a collection. OpenSearch Serverless emits this metric when a bulk indexing request fails for any reason, such as an authentication or availability issue. Shown as error
aws.aoss.ingestion_request_latency (gauge)	The latency, in seconds, for bulk write operations to a collection. Shown as second
aws.aoss.ingestion_request_rate (count)	The total number of bulk write operations received by a collection. Shown as operation
aws.aoss.ingestion_request_success (count)	The total number of successful indexing operations to a collection. Shown as operation
aws.aoss.search_ocu (count)	The number of OpenSearch Compute Units (OCUs) used to search collection data. This metric applies at the account level.
aws.aoss.search_request_errors (count)	The total number of query errors for a collection. Shown as error
aws.aoss.search_request_latency (gauge)	The average time, in milliseconds, that it takes to complete a search operation against a collection. Shown as millisecond
aws.aoss.search_request_rate (rate)	The total number of search requests per minute to a collection.
aws.aoss.searchable_documents (count)	The total number of searchable documents in a collection or index.
aws.aoss.storage_used_in_s3 (gauge)	The amount, in bytes, of Amazon S3 storage used for indexed data. Shown as byte

Service Checks

Amazon OpenSearch Serverless does not include any service checks.

Events

Amazon OpenSearch Serverless does not include any events.

Troubleshooting

Need help? Contact Datadog support.