docs(client-personalize): Documentation updates for Amazon Personalize.

Author: awstools

clients/client-personalize/src/commands/CreateCampaignCommand.ts

@@ -37,27 +37,26 @@ export interface CreateCampaignCommandOutput extends CreateCampaignResponse, __M
  *             <b>Minimum Provisioned TPS and Auto-Scaling</b>
  *          </p>
  *          <important>
- *             <p> A high <code>minProvisionedTPS</code> will increase your bill. We recommend starting with 1 for <code>minProvisionedTPS</code> (the default). Track
+ *             <p> A high <code>minProvisionedTPS</code> will increase your cost. We recommend starting with 1 for <code>minProvisionedTPS</code> (the default). Track
  *         your usage using Amazon CloudWatch metrics, and increase the <code>minProvisionedTPS</code>
  *         as necessary.</p>
  *          </important>
- *          <p>A transaction is a single <code>GetRecommendations</code> or
- *       <code>GetPersonalizedRanking</code> call. Transactions per second (TPS) is the throughput
- *       and unit of billing for Amazon Personalize. The minimum provisioned TPS
- *       (<code>minProvisionedTPS</code>) specifies the baseline throughput provisioned by
- *       Amazon Personalize, and thus, the minimum billing charge.
- *     </p>
  *          <p>
- *       If your TPS increases beyond
- *       <code>minProvisionedTPS</code>, Amazon Personalize auto-scales the provisioned capacity up and down,
- *       but never below <code>minProvisionedTPS</code>.
- *       There's a short time delay while the capacity is increased that might cause loss of
- *       transactions.</p>
- *          <p>The actual TPS used is calculated as the average requests/second within a 5-minute window.
- *       You pay for maximum of either the minimum provisioned TPS or the actual TPS.
+ *       When you create an Amazon Personalize campaign, you can specify the minimum provisioned transactions per second
+ *       (<code>minProvisionedTPS</code>) for the campaign. This is the baseline transaction throughput for the campaign provisioned by
+ *       Amazon Personalize. It sets the minimum billing charge for the campaign while it is active. A transaction is a single <code>GetRecommendations</code> or
+ *       <code>GetPersonalizedRanking</code> request. The default <code>minProvisionedTPS</code> is 1.</p>
+ *          <p> If your TPS increases beyond the <code>minProvisionedTPS</code>, Amazon Personalize auto-scales the provisioned capacity up
+ *       and down, but never below <code>minProvisionedTPS</code>.
+ *       There's a short time delay while the capacity is increased
+ *       that might cause loss of transactions. When your traffic reduces, capacity returns to the <code>minProvisionedTPS</code>.
+ *     </p>
+ *          <p>You are charged for the
+ *       the minimum provisioned TPS or, if your requests exceed the <code>minProvisionedTPS</code>, the actual TPS.
+ *       The actual TPS is the total number of recommendation requests you make.
  *       We recommend starting with a low <code>minProvisionedTPS</code>, track
- *       your usage using Amazon CloudWatch metrics, and then increase the <code>minProvisionedTPS</code>
- *       as necessary.</p>
+ *       your usage using Amazon CloudWatch metrics, and then increase the <code>minProvisionedTPS</code> as necessary.</p>
+ *          <p>For more information about campaign costs, see <a href="https://aws.amazon.com/personalize/pricing/">Amazon Personalize pricing</a>.</p>
  *          <p>
  *             <b>Status</b>
  *          </p>

clients/client-personalize/src/models/models_0.ts

@@ -641,7 +641,8 @@ export interface CampaignConfig {
   /**
    * @public
    * <p>Whether metadata with recommendations is enabled for the campaign.
-   *       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. </p>
+   *       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 campaign, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/campaigns.html#create-campaign-return-metadata">Enabling metadata in recommendations for a campaign</a>.</p>
    *          <p>
    *       If you enable metadata in recommendations, you will incur additional costs. For more information, see <a href="https://aws.amazon.com/personalize/pricing/">Amazon Personalize pricing</a>.
    *     </p>
@@ -1243,7 +1244,8 @@ export interface RecommenderConfig {
   /**
    * @public
    * <p>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. </p>
+   *       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 <a href="https://docs.aws.amazon.com/personalize/latest/dg/creating-recommenders.html#create-recommender-return-metadata">Enabling metadata in recommendations for a recommender</a>.</p>
    *          <p>
    *       If you enable metadata in recommendations, you will incur additional costs. For more information, see <a href="https://aws.amazon.com/personalize/pricing/">Amazon Personalize pricing</a>.
    *     </p>
@@ -1641,8 +1643,7 @@ export interface CreateSolutionRequest {
    * @public
    * <important>
    *             <p>We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize
-   *         recipes. For more information, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/determining-use-case.html">Determining your use case.</a>
-   *             </p>
+   *         recipes. For more information, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/working-with-predefined-recipes.html">Choosing a recipe</a>.</p>
    *          </important>
    *          <p>Whether to perform automated machine learning (AutoML). The default is <code>false</code>.
    *       For this case, you must specify <code>recipeArn</code>.</p>
@@ -1656,8 +1657,11 @@ export interface CreateSolutionRequest {
 
   /**
    * @public
-   * <p>The ARN of the recipe to use for model training. This is required when
-   *       <code>performAutoML</code> is false.</p>
+   * <p>The Amazon Resource Name (ARN) of the recipe to use for model training. This is required when
+   *       <code>performAutoML</code> is false. For information about different Amazon Personalize recipes and their ARNs,
+   *       see <a href="https://docs.aws.amazon.com/personalize/latest/dg/working-with-predefined-recipes.html">Choosing a recipe</a>.
+   *
+   *     </p>
    */
   recipeArn?: string;