feat(sources): update documentation

[aws-cdk-automation]

⚠️ This Pull Request updates daily and will overwrite all manual changes pushed to the branch

Updates the documentation source from upstream. See details in workflow run.

---

Automatically created by projen via the "update-source-documentation" workflow

[github-actions]

To work on this Pull Request, please create a new branch and PR. This prevents your work from being deleted by the automation.

Run the following commands inside the repo:

gh co 1215
git switch -c fix-pr-1215 && git push -u origin HEAD
gh pr create -t "fix: PR #1215" --body "Fixes https://github.com/cdklabs/awscdk-service-spec/pull/1215"

[github-actions]

@aws-cdk/aws-service-spec: Model database diff detected

├[~] service aws-codecommit
│ └ resources
│    └[~] resource AWS::CodeCommit::Repository
│      └  - documentation: Creates a new, empty repository.
│         + documentation: Creates a new, empty repository.
│         > AWS CodeCommit is no longer available to new customers. Existing customers of AWS CodeCommit can continue to use the service as normal. [Learn more"](https://docs.aws.amazon.com/devops/how-to-migrate-your-aws-codecommit-repository-to-another-git-provider)
├[~] service aws-datapipeline
│ └ resources
│    └[~] resource AWS::DataPipeline::Pipeline
│      └  - documentation: The AWS::DataPipeline::Pipeline resource specifies a data pipeline that you can use to automate the movement and transformation of data. In each pipeline, you define pipeline objects, such as activities, schedules, data nodes, and resources. For information about pipeline objects and components that you can use, see [Pipeline Object Reference](https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-pipeline-objects.html) in the *AWS Data Pipeline Developer Guide* .
│         The `AWS::DataPipeline::Pipeline` resource adds tasks, schedules, and preconditions to the specified pipeline. You can use `PutPipelineDefinition` to populate a new pipeline.
│         `PutPipelineDefinition` also validates the configuration as it adds it to the pipeline. Changes to the pipeline are saved unless one of the following validation errors exist in the pipeline.
│         - An object is missing a name or identifier field.
│         - A string or reference field is empty.
│         - The number of objects in the pipeline exceeds the allowed maximum number of objects.
│         - The pipeline is in a FINISHED state.
│         Pipeline object definitions are passed to the [PutPipelineDefinition](https://docs.aws.amazon.com/datapipeline/latest/APIReference/API_PutPipelineDefinition.html) action and returned by the [GetPipelineDefinition](https://docs.aws.amazon.com/datapipeline/latest/APIReference/API_GetPipelineDefinition.html) action.
│         + documentation: The AWS::DataPipeline::Pipeline resource specifies a data pipeline that you can use to automate the movement and transformation of data.
│         > AWS Data Pipeline is no longer available to new customers. Existing customers of AWS Data Pipeline can continue to use the service as normal. [Learn more](https://docs.aws.amazon.com/big-data/migrate-workloads-from-aws-data-pipeline/) 
│         In each pipeline, you define pipeline objects, such as activities, schedules, data nodes, and resources.
│         The `AWS::DataPipeline::Pipeline` resource adds tasks, schedules, and preconditions to the specified pipeline. You can use `PutPipelineDefinition` to populate a new pipeline.
│         `PutPipelineDefinition` also validates the configuration as it adds it to the pipeline. Changes to the pipeline are saved unless one of the following validation errors exist in the pipeline.
│         - An object is missing a name or identifier field.
│         - A string or reference field is empty.
│         - The number of objects in the pipeline exceeds the allowed maximum number of objects.
│         - The pipeline is in a FINISHED state.
│         Pipeline object definitions are passed to the [PutPipelineDefinition](https://docs.aws.amazon.com/datapipeline/latest/APIReference/API_PutPipelineDefinition.html) action and returned by the [GetPipelineDefinition](https://docs.aws.amazon.com/datapipeline/latest/APIReference/API_GetPipelineDefinition.html) action.
├[~] service aws-ecs
│ └ resources
│    ├[~] resource AWS::ECS::Service
│    │ └ types
│    │    └[~] type AwsVpcConfiguration
│    │      └  - documentation: An object representing the networking details for a task or service. For example `awsvpcConfiguration={subnets=["subnet-12344321"],securityGroups=["sg-12344321"]}`
│    │         + documentation: An object representing the networking details for a task or service. For example `awsVpcConfiguration={subnets=["subnet-12344321"],securityGroups=["sg-12344321"]}` .
│    └[~] resource AWS::ECS::TaskSet
│      └ types
│         └[~] type AwsVpcConfiguration
│           └  - documentation: An object representing the networking details for a task or service. For example `awsvpcConfiguration={subnets=["subnet-12344321"],securityGroups=["sg-12344321"]}`
│              + documentation: An object representing the networking details for a task or service. For example `awsVpcConfiguration={subnets=["subnet-12344321"],securityGroups=["sg-12344321"]}` .
├[~] service aws-elasticloadbalancingv2
│ └ resources
│    └[~] resource AWS::ElasticLoadBalancingV2::TargetGroup
│      └ types
│         └[~] type TargetGroupAttribute
│           └ properties
│              └ Key: (documentation changed)
├[~] service aws-forecast
│ └ resources
│    ├[~] resource AWS::Forecast::Dataset
│    │ └  - documentation: Creates an Amazon Forecast dataset. The information about the dataset that you provide helps Forecast understand how to consume the data for model training. This includes the following:
│    │    - *`DataFrequency`* - How frequently your historical time-series data is collected.
│    │    - *`Domain`* and *`DatasetType`* - Each dataset has an associated dataset domain and a type within the domain. Amazon Forecast provides a list of predefined domains and types within each domain. For each unique dataset domain and type within the domain, Amazon Forecast requires your data to include a minimum set of predefined fields.
│    │    - *`Schema`* - A schema specifies the fields in the dataset, including the field name and data type.
│    │    After creating a dataset, you import your training data into it and add the dataset to a dataset group. You use the dataset group to create a predictor. For more information, see [Importing datasets](https://docs.aws.amazon.com/forecast/latest/dg/howitworks-datasets-groups.html) .
│    │    To get a list of all your datasets, use the [ListDatasets](https://docs.aws.amazon.com/forecast/latest/dg/API_ListDatasets.html) operation.
│    │    For example Forecast datasets, see the [Amazon Forecast Sample GitHub repository](https://docs.aws.amazon.com/https://github.com/aws-samples/amazon-forecast-samples) .
│    │    > The `Status` of a dataset must be `ACTIVE` before you can import training data. Use the [DescribeDataset](https://docs.aws.amazon.com/forecast/latest/dg/API_DescribeDataset.html) operation to get the status.
│    │    + documentation: Creates an Amazon Forecast dataset.
│    │    > Amazon Forecast is no longer available to new customers. Existing customers of Amazon Forecast can continue to use the service as normal. [Learn more"](https://docs.aws.amazon.com/machine-learning/transition-your-amazon-forecast-usage-to-amazon-sagemaker-canvas/) 
│    │    The information about the dataset that you provide helps Forecast understand how to consume the data for model training. This includes the following:
│    │    - *`DataFrequency`* - How frequently your historical time-series data is collected.
│    │    - *`Domain`* and *`DatasetType`* - Each dataset has an associated dataset domain and a type within the domain. Amazon Forecast provides a list of predefined domains and types within each domain. For each unique dataset domain and type within the domain, Amazon Forecast requires your data to include a minimum set of predefined fields.
│    │    - *`Schema`* - A schema specifies the fields in the dataset, including the field name and data type.
│    │    After creating a dataset, you import your training data into it and add the dataset to a dataset group. You use the dataset group to create a predictor. For more information, see [Importing datasets](https://docs.aws.amazon.com/forecast/latest/dg/howitworks-datasets-groups.html) .
│    │    To get a list of all your datasets, use the [ListDatasets](https://docs.aws.amazon.com/forecast/latest/dg/API_ListDatasets.html) operation.
│    │    For example Forecast datasets, see the [Amazon Forecast Sample GitHub repository](https://docs.aws.amazon.com/https://github.com/aws-samples/amazon-forecast-samples) .
│    │    > The `Status` of a dataset must be `ACTIVE` before you can import training data. Use the [DescribeDataset](https://docs.aws.amazon.com/forecast/latest/dg/API_DescribeDataset.html) operation to get the status.
│    └[~] resource AWS::Forecast::DatasetGroup
│      └  - documentation: Creates a dataset group, which holds a collection of related datasets. You can add datasets to the dataset group when you create the dataset group, or later by using the [UpdateDatasetGroup](https://docs.aws.amazon.com/forecast/latest/dg/API_UpdateDatasetGroup.html) operation.
│         After creating a dataset group and adding datasets, you use the dataset group when you create a predictor. For more information, see [Dataset groups](https://docs.aws.amazon.com/forecast/latest/dg/howitworks-datasets-groups.html) .
│         To get a list of all your datasets groups, use the [ListDatasetGroups](https://docs.aws.amazon.com/forecast/latest/dg/API_ListDatasetGroups.html) operation.
│         > The `Status` of a dataset group must be `ACTIVE` before you can use the dataset group to create a predictor. To get the status, use the [DescribeDatasetGroup](https://docs.aws.amazon.com/forecast/latest/dg/API_DescribeDatasetGroup.html) operation.
│         + documentation: Creates a dataset group, which holds a collection of related datasets. You can add datasets to the dataset group when you create the dataset group, or later by using the [UpdateDatasetGroup](https://docs.aws.amazon.com/forecast/latest/dg/API_UpdateDatasetGroup.html) operation.
│         > Amazon Forecast is no longer available to new customers. Existing customers of Amazon Forecast can continue to use the service as normal. [Learn more"](https://docs.aws.amazon.com/machine-learning/transition-your-amazon-forecast-usage-to-amazon-sagemaker-canvas/) 
│         After creating a dataset group and adding datasets, you use the dataset group when you create a predictor. For more information, see [Dataset groups](https://docs.aws.amazon.com/forecast/latest/dg/howitworks-datasets-groups.html) .
│         To get a list of all your datasets groups, use the [ListDatasetGroups](https://docs.aws.amazon.com/forecast/latest/dg/API_ListDatasetGroups.html) operation.
│         > The `Status` of a dataset group must be `ACTIVE` before you can use the dataset group to create a predictor. To get the status, use the [DescribeDatasetGroup](https://docs.aws.amazon.com/forecast/latest/dg/API_DescribeDatasetGroup.html) operation.
└[~] service aws-osis
  └ resources
     └[~] resource AWS::OSIS::Pipeline
       └ types
          ├[~] type VpcAttachmentOptions
          │ ├  - documentation: Options for attaching a VPC to the pipeline.
          │ │  + documentation: Options for attaching a VPC to pipeline.
          │ └ properties
          │    └ AttachToVpc: (documentation changed)
          └[~] type VpcOptions
            └ properties
               └ VpcAttachmentOptions: (documentation changed)