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

# aws_personalize_solution{% #aws_personalize_solution %}

## `account_id`{% #account_id %}

**Type**: `STRING`

## `auto_ml_result`{% #auto_ml_result %}

**Type**: `STRUCT`**Provider name**: `autoMLResult`**Description**: When `performAutoML` is true, specifies the best recipe found.

- `best_recipe_arn`**Type**: `STRING`**Provider name**: `bestRecipeArn`**Description**: The Amazon Resource Name (ARN) of the best recipe.

## `creation_date_time`{% #creation_date_time %}

**Type**: `TIMESTAMP`**Provider name**: `creationDateTime`**Description**: The creation date and time (in Unix time) of the solution.

## `dataset_group_arn`{% #dataset_group_arn %}

**Type**: `STRING`**Provider name**: `datasetGroupArn`**Description**: The Amazon Resource Name (ARN) of the dataset group that provides the training data.

## `event_type`{% #event_type %}

**Type**: `STRING`**Provider name**: `eventType`**Description**: The event type (for example, 'click' or 'like') that is used for training the model. If no `eventType` is provided, Amazon Personalize uses all interactions for training with equal weight regardless of type.

## `last_updated_date_time`{% #last_updated_date_time %}

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

## `latest_solution_update`{% #latest_solution_update %}

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

- `creation_date_time`**Type**: `TIMESTAMP`**Provider name**: `creationDateTime`**Description**: The date and time (in Unix format) that the solution update was created.
- `failure_reason`**Type**: `STRING`**Provider name**: `failureReason`**Description**: If a solution 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 solution update was last updated.
- `perform_auto_training`**Type**: `BOOLEAN`**Provider name**: `performAutoTraining`**Description**: Whether the solution automatically creates solution versions.
- `solution_update_config`**Type**: `STRUCT`**Provider name**: `solutionUpdateConfig`**Description**: The configuration details of the solution.
  - `auto_training_config`**Type**: `STRUCT`**Provider name**: `autoTrainingConfig`
    - `scheduling_expression`**Type**: `STRING`**Provider name**: `schedulingExpression`**Description**: Specifies how often to automatically train new solution versions. Specify a rate expression in rate(value unit) format. For value, specify a number between 1 and 30. For unit, specify `day` or `days`. For example, to automatically create a new solution version every 5 days, specify `rate(5 days)`. The default is every 7 days. For more information about auto training, see [Creating and configuring a solution](https://docs.aws.amazon.com/personalize/latest/dg/customizing-solution-config.html).
  - `events_config`**Type**: `STRUCT`**Provider name**: `eventsConfig`**Description**: Describes the configuration of an event, which includes a list of event parameters. You can specify up to 10 event parameters. Events are used in solution creation.
    - `event_parameters_list`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `eventParametersList`**Description**: A list of event parameters, which includes event types and their event value thresholds and weights.
      - `event_type`**Type**: `STRING`**Provider name**: `eventType`**Description**: The name of the event type to be considered for solution creation.
      - `event_value_threshold`**Type**: `DOUBLE`**Provider name**: `eventValueThreshold`**Description**: The threshold of the event type. Only events with a value greater or equal to this threshold will be considered for solution creation.
      - `weight`**Type**: `DOUBLE`**Provider name**: `weight`**Description**: The weight of the event type. A higher weight means higher importance of the event type for the created solution.
- `status`**Type**: `STRING`**Provider name**: `status`**Description**: The status of the solution update. A solution update can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

## `latest_solution_version`{% #latest_solution_version %}

**Type**: `STRUCT`**Provider name**: `latestSolutionVersion`**Description**: Describes the latest version of the solution, including the status and the ARN.

- `creation_date_time`**Type**: `TIMESTAMP`**Provider name**: `creationDateTime`**Description**: The date and time (in Unix time) that this version of a solution was created.
- `failure_reason`**Type**: `STRING`**Provider name**: `failureReason`**Description**: If a solution version 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 solution version was last updated.
- `solution_version_arn`**Type**: `STRING`**Provider name**: `solutionVersionArn`**Description**: The Amazon Resource Name (ARN) of the solution version.
- `status`**Type**: `STRING`**Provider name**: `status`**Description**: The status of the solution version. A solution version can be in one of the following states:
  - CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
- `training_mode`**Type**: `STRING`**Provider name**: `trainingMode`**Description**: The scope of training to be performed when creating the solution version. A `FULL` training considers all of the data in your dataset group. An `UPDATE` processes only the data that has changed since the latest training. Only solution versions created with the User-Personalization recipe can use `UPDATE`.
- `training_type`**Type**: `STRING`**Provider name**: `trainingType`**Description**: Whether the solution version was created automatically or manually.

## `name`{% #name %}

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

## `perform_auto_ml`{% #perform_auto_ml %}

**Type**: `BOOLEAN`**Provider name**: `performAutoML`**Description**:We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize recipes. For more information, see [Determining your use case.](https://docs.aws.amazon.com/personalize/latest/dg/determining-use-case.html)When true, Amazon Personalize performs a search for the best USER_PERSONALIZATION recipe from the list specified in the solution configuration (`recipeArn` must not be specified). When false (the default), Amazon Personalize uses `recipeArn` for training.

## `perform_auto_training`{% #perform_auto_training %}

**Type**: `BOOLEAN`**Provider name**: `performAutoTraining`**Description**: Specifies whether the solution automatically creates solution versions. The default is `True` and the solution automatically creates new solution versions every 7 days. For more information about auto training, see [Creating and configuring a solution](https://docs.aws.amazon.com/personalize/latest/dg/customizing-solution-config.html).

## `perform_hpo`{% #perform_hpo %}

**Type**: `BOOLEAN`**Provider name**: `performHPO`**Description**: Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is `false`.

## `recipe_arn`{% #recipe_arn %}

**Type**: `STRING`**Provider name**: `recipeArn`**Description**: The ARN of the recipe used to create the solution. This is required when `performAutoML` is false.

## `solution_arn`{% #solution_arn %}

**Type**: `STRING`**Provider name**: `solutionArn`**Description**: The ARN of the solution.

## `solution_config`{% #solution_config %}

**Type**: `STRUCT`**Provider name**: `solutionConfig`**Description**: Describes the configuration properties for the solution.

- `algorithm_hyper_parameters`**Type**: `MAP_STRING_STRING`**Provider name**: `algorithmHyperParameters`**Description**: Lists the algorithm hyperparameters and their values.
- `auto_ml_config`**Type**: `STRUCT`**Provider name**: `autoMLConfig`**Description**: The [AutoMLConfig](https://docs.aws.amazon.com/personalize/latest/dg/API_AutoMLConfig.html) object containing a list of recipes to search when AutoML is performed.
  - `metric_name`**Type**: `STRING`**Provider name**: `metricName`**Description**: The metric to optimize.
  - `recipe_list`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `recipeList`**Description**: The list of candidate recipes.
- `auto_training_config`**Type**: `STRUCT`**Provider name**: `autoTrainingConfig`**Description**: Specifies the automatic training configuration to use.
  - `scheduling_expression`**Type**: `STRING`**Provider name**: `schedulingExpression`**Description**: Specifies how often to automatically train new solution versions. Specify a rate expression in rate(value unit) format. For value, specify a number between 1 and 30. For unit, specify `day` or `days`. For example, to automatically create a new solution version every 5 days, specify `rate(5 days)`. The default is every 7 days. For more information about auto training, see [Creating and configuring a solution](https://docs.aws.amazon.com/personalize/latest/dg/customizing-solution-config.html).
- `event_value_threshold`**Type**: `STRING`**Provider name**: `eventValueThreshold`**Description**: Only events with a value greater than or equal to this threshold are used for training a model.
- `events_config`**Type**: `STRUCT`**Provider name**: `eventsConfig`**Description**: Describes the configuration of an event, which includes a list of event parameters. You can specify up to 10 event parameters. Events are used in solution creation.
  - `event_parameters_list`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `eventParametersList`**Description**: A list of event parameters, which includes event types and their event value thresholds and weights.
    - `event_type`**Type**: `STRING`**Provider name**: `eventType`**Description**: The name of the event type to be considered for solution creation.
    - `event_value_threshold`**Type**: `DOUBLE`**Provider name**: `eventValueThreshold`**Description**: The threshold of the event type. Only events with a value greater or equal to this threshold will be considered for solution creation.
    - `weight`**Type**: `DOUBLE`**Provider name**: `weight`**Description**: The weight of the event type. A higher weight means higher importance of the event type for the created solution.
- `feature_transformation_parameters`**Type**: `MAP_STRING_STRING`**Provider name**: `featureTransformationParameters`**Description**: Lists the feature transformation parameters.
- `hpo_config`**Type**: `STRUCT`**Provider name**: `hpoConfig`**Description**: Describes the properties for hyperparameter optimization (HPO).
  - `algorithm_hyper_parameter_ranges`**Type**: `STRUCT`**Provider name**: `algorithmHyperParameterRanges`**Description**: The hyperparameters and their allowable ranges.
    - `categorical_hyper_parameter_ranges`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `categoricalHyperParameterRanges`**Description**: The categorical hyperparameters and their ranges.
      - `name`**Type**: `STRING`**Provider name**: `name`**Description**: The name of the hyperparameter.
      - `values`**Type**: `UNORDERED_LIST_STRING`**Provider name**: `values`**Description**: A list of the categories for the hyperparameter.
    - `continuous_hyper_parameter_ranges`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `continuousHyperParameterRanges`**Description**: The continuous hyperparameters and their ranges.
      - `max_value`**Type**: `DOUBLE`**Provider name**: `maxValue`**Description**: The maximum allowable value for the hyperparameter.
      - `min_value`**Type**: `DOUBLE`**Provider name**: `minValue`**Description**: The minimum allowable value for the hyperparameter.
      - `name`**Type**: `STRING`**Provider name**: `name`**Description**: The name of the hyperparameter.
    - `integer_hyper_parameter_ranges`**Type**: `UNORDERED_LIST_STRUCT`**Provider name**: `integerHyperParameterRanges`**Description**: The integer-valued hyperparameters and their ranges.
      - `max_value`**Type**: `INT32`**Provider name**: `maxValue`**Description**: The maximum allowable value for the hyperparameter.
      - `min_value`**Type**: `INT32`**Provider name**: `minValue`**Description**: The minimum allowable value for the hyperparameter.
      - `name`**Type**: `STRING`**Provider name**: `name`**Description**: The name of the hyperparameter.
  - `hpo_objective`**Type**: `STRUCT`**Provider name**: `hpoObjective`**Description**: The metric to optimize during HPO.Amazon Personalize doesn't support configuring the `hpoObjective` at this time.
    - `metric_name`**Type**: `STRING`**Provider name**: `metricName`**Description**: The name of the metric.
    - `metric_regex`**Type**: `STRING`**Provider name**: `metricRegex`**Description**: A regular expression for finding the metric in the training job logs.
    - `type`**Type**: `STRING`**Provider name**: `type`**Description**: The type of the metric. Valid values are `Maximize` and `Minimize`.
  - `hpo_resource_config`**Type**: `STRUCT`**Provider name**: `hpoResourceConfig`**Description**: Describes the resource configuration for HPO.
    - `max_number_of_training_jobs`**Type**: `STRING`**Provider name**: `maxNumberOfTrainingJobs`**Description**: The maximum number of training jobs when you create a solution version. The maximum value for `maxNumberOfTrainingJobs` is `40`.
    - `max_parallel_training_jobs`**Type**: `STRING`**Provider name**: `maxParallelTrainingJobs`**Description**: The maximum number of parallel training jobs when you create a solution version. The maximum value for `maxParallelTrainingJobs` is `10`.
- `optimization_objective`**Type**: `STRUCT`**Provider name**: `optimizationObjective`**Description**: Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see [Optimizing a solution](https://docs.aws.amazon.com/personalize/latest/dg/optimizing-solution-for-objective.html).
  - `item_attribute`**Type**: `STRING`**Provider name**: `itemAttribute`**Description**: The numerical metadata column in an Items dataset related to the optimization objective. For example, VIDEO_LENGTH (to maximize streaming minutes), or PRICE (to maximize revenue).
  - `objective_sensitivity`**Type**: `STRING`**Provider name**: `objectiveSensitivity`**Description**: Specifies how Amazon Personalize balances the importance of your optimization objective versus relevance.
- `training_data_config`**Type**: `STRUCT`**Provider name**: `trainingDataConfig`**Description**: Specifies the training data configuration to use when creating a custom solution version (trained model).
  - `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 solution. A solution can be in one of the following states:

- CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
- DELETE PENDING > DELETE IN_PROGRESS



## `tags`{% #tags %}

**Type**: `UNORDERED_LIST_STRING`