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

# aws_personalize_recommender{% #aws_personalize_recommender %}

## `account_id`{% #account_id %}

**Type**: `STRING`

## `creation_date_time`{% #creation_date_time %}

**Type**: `TIMESTAMP`**Provider name**: `creationDateTime`**Description**: The date and time (in Unix format) that the recommender was created.

## `dataset_group_arn`{% #dataset_group_arn %}

**Type**: `STRING`**Provider name**: `datasetGroupArn`**Description**: The Amazon Resource Name (ARN) of the Domain dataset group that contains the recommender.

## `failure_reason`{% #failure_reason %}

**Type**: `STRING`**Provider name**: `failureReason`**Description**: If a recommender fails, the reason behind the failure.

## `last_updated_date_time`{% #last_updated_date_time %}

**Type**: `TIMESTAMP`**Provider name**: `lastUpdatedDateTime`**Description**: The date and time (in Unix format) that the recommender was last updated.

## `latest_recommender_update`{% #latest_recommender_update %}

**Type**: `STRUCT`**Provider name**: `latestRecommenderUpdate`**Description**: Provides a summary of the latest updates to the recommender.

- `creation_date_time`**Type**: `TIMESTAMP`**Provider name**: `creationDateTime`**Description**: The date and time (in Unix format) that the recommender update was created.
- `failure_reason`**Type**: `STRING`**Provider name**: `failureReason`**Description**: If a recommender update fails, the reason behind the failure.
- `last_updated_date_time`**Type**: `TIMESTAMP`**Provider name**: `lastUpdatedDateTime`**Description**: The date and time (in Unix time) that the recommender update was last updated.
- `recommender_config`**Type**: `STRUCT`**Provider name**: `recommenderConfig`**Description**: The configuration details of the recommender update.
  - `enable_metadata_with_recommendations`**Type**: `BOOLEAN`**Provider name**: `enableMetadataWithRecommendations`**Description**: Whether metadata with recommendations is enabled for the recommender. If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response. For information about enabling metadata for a recommender, see [Enabling metadata in recommendations for a recommender](https://docs.aws.amazon.com/personalize/latest/dg/creating-recommenders.html#create-recommender-return-metadata). If you enable metadata in recommendations, you will incur additional costs. For more information, see [Amazon Personalize pricing](https://aws.amazon.com/personalize/pricing/).
  - `item_exploration_config`**Type**: `MAP_STRING_STRING`**Provider name**: `itemExplorationConfig`**Description**: Specifies the exploration configuration hyperparameters, including `explorationWeight` and `explorationItemAgeCutOff`, you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide `itemExplorationConfig` data only if your recommenders generate personalized recommendations for a user (not popular items or similar items).
  - `min_recommendation_requests_per_second`**Type**: `INT32`**Provider name**: `minRecommendationRequestsPerSecond`**Description**: Specifies the requested minimum provisioned recommendation requests per second that Amazon Personalize will support. A high `minRecommendationRequestsPerSecond` will increase your bill. We recommend starting with 1 for `minRecommendationRequestsPerSecond` (the default). Track your usage using Amazon CloudWatch metrics, and increase the `minRecommendationRequestsPerSecond` as necessary.
  - `training_data_config`**Type**: `STRUCT`**Provider name**: `trainingDataConfig`**Description**: Specifies the training data configuration to use when creating a domain recommender.
    - `excluded_dataset_columns`**Type**: `STRING`**Provider name**: `excludedDatasetColumns`**Description**: Specifies the columns to exclude from training. Each key is a dataset type, and each value is a list of columns. Exclude columns to control what data Amazon Personalize uses to generate recommendations. For example, you might have a column that you want to use only to filter recommendations. You can exclude this column from training and Amazon Personalize considers it only when filtering.
- `status`**Type**: `STRING`**Provider name**: `status`**Description**: The status of the recommender update. A recommender update can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

## `model_metrics`{% #model_metrics %}

**Type**: `STRING`**Provider name**: `modelMetrics`**Description**: Provides evaluation metrics that help you determine the performance of a recommender. For more information, see [Evaluating a recommender](https://docs.aws.amazon.com/personalize/latest/dg/evaluating-recommenders.html).

## `name`{% #name %}

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

## `recipe_arn`{% #recipe_arn %}

**Type**: `STRING`**Provider name**: `recipeArn`**Description**: The Amazon Resource Name (ARN) of the recipe (Domain dataset group use case) that the recommender was created for.

## `recommender_arn`{% #recommender_arn %}

**Type**: `STRING`**Provider name**: `recommenderArn`**Description**: The Amazon Resource Name (ARN) of the recommender.

## `recommender_config`{% #recommender_config %}

**Type**: `STRUCT`**Provider name**: `recommenderConfig`**Description**: The configuration details of the recommender.

- `enable_metadata_with_recommendations`**Type**: `BOOLEAN`**Provider name**: `enableMetadataWithRecommendations`**Description**: Whether metadata with recommendations is enabled for the recommender. If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response. For information about enabling metadata for a recommender, see [Enabling metadata in recommendations for a recommender](https://docs.aws.amazon.com/personalize/latest/dg/creating-recommenders.html#create-recommender-return-metadata). If you enable metadata in recommendations, you will incur additional costs. For more information, see [Amazon Personalize pricing](https://aws.amazon.com/personalize/pricing/).
- `item_exploration_config`**Type**: `MAP_STRING_STRING`**Provider name**: `itemExplorationConfig`**Description**: Specifies the exploration configuration hyperparameters, including `explorationWeight` and `explorationItemAgeCutOff`, you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide `itemExplorationConfig` data only if your recommenders generate personalized recommendations for a user (not popular items or similar items).
- `min_recommendation_requests_per_second`**Type**: `INT32`**Provider name**: `minRecommendationRequestsPerSecond`**Description**: Specifies the requested minimum provisioned recommendation requests per second that Amazon Personalize will support. A high `minRecommendationRequestsPerSecond` will increase your bill. We recommend starting with 1 for `minRecommendationRequestsPerSecond` (the default). Track your usage using Amazon CloudWatch metrics, and increase the `minRecommendationRequestsPerSecond` as necessary.
- `training_data_config`**Type**: `STRUCT`**Provider name**: `trainingDataConfig`**Description**: Specifies the training data configuration to use when creating a domain recommender.
  - `excluded_dataset_columns`**Type**: `STRING`**Provider name**: `excludedDatasetColumns`**Description**: Specifies the columns to exclude from training. Each key is a dataset type, and each value is a list of columns. Exclude columns to control what data Amazon Personalize uses to generate recommendations. For example, you might have a column that you want to use only to filter recommendations. You can exclude this column from training and Amazon Personalize considers it only when filtering.

## `status`{% #status %}

**Type**: `STRING`**Provider name**: `status`**Description**: The status of the recommender. A recommender can be in one of the following states:

- CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
- STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE
- DELETE PENDING > DELETE IN_PROGRESS



## `tags`{% #tags %}

**Type**: `UNORDERED_LIST_STRING`