aws_sdk_mwaaserverless/operation/create_workflow/

builders.rs

// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::create_workflow::_create_workflow_output::CreateWorkflowOutputBuilder;

pub use crate::operation::create_workflow::_create_workflow_input::CreateWorkflowInputBuilder;

impl crate::operation::create_workflow::builders::CreateWorkflowInputBuilder {
    /// Sends a request with this input using the given client.
    pub async fn send_with(
        self,
        client: &crate::Client,
    ) -> ::std::result::Result<
        crate::operation::create_workflow::CreateWorkflowOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_workflow::CreateWorkflowError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let mut fluent_builder = client.create_workflow();
        fluent_builder.inner = self;
        fluent_builder.send().await
    }
}
/// Fluent builder constructing a request to `CreateWorkflow`.
///
/// <p>Creates a new workflow in Amazon Managed Workflows for Apache Airflow Serverless. This operation initializes a workflow with the specified configuration including the workflow definition, execution role, and optional settings for encryption, logging, and networking. You must provide the workflow definition as a YAML file stored in Amazon S3 that defines the DAG structure using supported Amazon Web Services operators. Amazon Managed Workflows for Apache Airflow Serverless automatically creates the first version of the workflow and sets up the necessary execution environment with multi-tenant isolation and security controls.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct CreateWorkflowFluentBuilder {
    handle: ::std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::create_workflow::builders::CreateWorkflowInputBuilder,
    config_override: ::std::option::Option<crate::config::Builder>,
}
impl
    crate::client::customize::internal::CustomizableSend<
        crate::operation::create_workflow::CreateWorkflowOutput,
        crate::operation::create_workflow::CreateWorkflowError,
    > for CreateWorkflowFluentBuilder
{
    fn send(
        self,
        config_override: crate::config::Builder,
    ) -> crate::client::customize::internal::BoxFuture<
        crate::client::customize::internal::SendResult<
            crate::operation::create_workflow::CreateWorkflowOutput,
            crate::operation::create_workflow::CreateWorkflowError,
        >,
    > {
        ::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
    }
}
impl CreateWorkflowFluentBuilder {
    /// Creates a new `CreateWorkflowFluentBuilder`.
    pub(crate) fn new(handle: ::std::sync::Arc<crate::client::Handle>) -> Self {
        Self {
            handle,
            inner: ::std::default::Default::default(),
            config_override: ::std::option::Option::None,
        }
    }
    /// Access the CreateWorkflow as a reference.
    pub fn as_input(&self) -> &crate::operation::create_workflow::builders::CreateWorkflowInputBuilder {
        &self.inner
    }
    /// Sends the request and returns the response.
    ///
    /// If an error occurs, an `SdkError` will be returned with additional details that
    /// can be matched against.
    ///
    /// By default, any retryable failures will be retried twice. Retry behavior
    /// is configurable with the [RetryConfig](aws_smithy_types::retry::RetryConfig), which can be
    /// set when configuring the client.
    pub async fn send(
        self,
    ) -> ::std::result::Result<
        crate::operation::create_workflow::CreateWorkflowOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_workflow::CreateWorkflowError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let input = self
            .inner
            .build()
            .map_err(::aws_smithy_runtime_api::client::result::SdkError::construction_failure)?;
        let runtime_plugins = crate::operation::create_workflow::CreateWorkflow::operation_runtime_plugins(
            self.handle.runtime_plugins.clone(),
            &self.handle.conf,
            self.config_override,
        );
        crate::operation::create_workflow::CreateWorkflow::orchestrate(&runtime_plugins, input).await
    }

    /// Consumes this builder, creating a customizable operation that can be modified before being sent.
    pub fn customize(
        self,
    ) -> crate::client::customize::CustomizableOperation<
        crate::operation::create_workflow::CreateWorkflowOutput,
        crate::operation::create_workflow::CreateWorkflowError,
        Self,
    > {
        crate::client::customize::CustomizableOperation::new(self)
    }
    pub(crate) fn config_override(mut self, config_override: impl ::std::convert::Into<crate::config::Builder>) -> Self {
        self.set_config_override(::std::option::Option::Some(config_override.into()));
        self
    }

    pub(crate) fn set_config_override(&mut self, config_override: ::std::option::Option<crate::config::Builder>) -> &mut Self {
        self.config_override = config_override;
        self
    }
    /// <p>The name of the workflow. You must use unique workflow names within your Amazon Web Services account. The service generates a unique identifier that is appended to ensure temporal uniqueness across the account lifecycle.</p>
    pub fn name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.name(input.into());
        self
    }
    /// <p>The name of the workflow. You must use unique workflow names within your Amazon Web Services account. The service generates a unique identifier that is appended to ensure temporal uniqueness across the account lifecycle.</p>
    pub fn set_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_name(input);
        self
    }
    /// <p>The name of the workflow. You must use unique workflow names within your Amazon Web Services account. The service generates a unique identifier that is appended to ensure temporal uniqueness across the account lifecycle.</p>
    pub fn get_name(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_name()
    }
    /// <p>A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. This token prevents duplicate workflow creation requests.</p>
    pub fn client_token(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.client_token(input.into());
        self
    }
    /// <p>A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. This token prevents duplicate workflow creation requests.</p>
    pub fn set_client_token(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_client_token(input);
        self
    }
    /// <p>A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. This token prevents duplicate workflow creation requests.</p>
    pub fn get_client_token(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_client_token()
    }
    /// <p>The Amazon S3 location where the workflow definition file is stored. This must point to a valid YAML file that defines the workflow structure using supported Amazon Web Services operators and tasks. Amazon Managed Workflows for Apache Airflow Serverless takes a snapshot of the definition at creation time, so subsequent changes to the Amazon S3 object will not affect the workflow unless you create a new version. In your YAML definition, include task dependencies, scheduling information, and operator configurations that are compatible with the Amazon Managed Workflows for Apache Airflow Serverless execution environment.</p>
    pub fn definition_s3_location(mut self, input: crate::types::DefinitionS3Location) -> Self {
        self.inner = self.inner.definition_s3_location(input);
        self
    }
    /// <p>The Amazon S3 location where the workflow definition file is stored. This must point to a valid YAML file that defines the workflow structure using supported Amazon Web Services operators and tasks. Amazon Managed Workflows for Apache Airflow Serverless takes a snapshot of the definition at creation time, so subsequent changes to the Amazon S3 object will not affect the workflow unless you create a new version. In your YAML definition, include task dependencies, scheduling information, and operator configurations that are compatible with the Amazon Managed Workflows for Apache Airflow Serverless execution environment.</p>
    pub fn set_definition_s3_location(mut self, input: ::std::option::Option<crate::types::DefinitionS3Location>) -> Self {
        self.inner = self.inner.set_definition_s3_location(input);
        self
    }
    /// <p>The Amazon S3 location where the workflow definition file is stored. This must point to a valid YAML file that defines the workflow structure using supported Amazon Web Services operators and tasks. Amazon Managed Workflows for Apache Airflow Serverless takes a snapshot of the definition at creation time, so subsequent changes to the Amazon S3 object will not affect the workflow unless you create a new version. In your YAML definition, include task dependencies, scheduling information, and operator configurations that are compatible with the Amazon Managed Workflows for Apache Airflow Serverless execution environment.</p>
    pub fn get_definition_s3_location(&self) -> &::std::option::Option<crate::types::DefinitionS3Location> {
        self.inner.get_definition_s3_location()
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that Amazon Managed Workflows for Apache Airflow Serverless assumes when executing the workflow. This role must have the necessary permissions to access the required Amazon Web Services services and resources that your workflow tasks will interact with. The role is used for task execution in the isolated, multi-tenant environment and should follow the principle of least privilege. Amazon Managed Workflows for Apache Airflow Serverless validates role access during workflow creation but runtime permission checks are performed by the target services.</p>
    pub fn role_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.role_arn(input.into());
        self
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that Amazon Managed Workflows for Apache Airflow Serverless assumes when executing the workflow. This role must have the necessary permissions to access the required Amazon Web Services services and resources that your workflow tasks will interact with. The role is used for task execution in the isolated, multi-tenant environment and should follow the principle of least privilege. Amazon Managed Workflows for Apache Airflow Serverless validates role access during workflow creation but runtime permission checks are performed by the target services.</p>
    pub fn set_role_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_role_arn(input);
        self
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that Amazon Managed Workflows for Apache Airflow Serverless assumes when executing the workflow. This role must have the necessary permissions to access the required Amazon Web Services services and resources that your workflow tasks will interact with. The role is used for task execution in the isolated, multi-tenant environment and should follow the principle of least privilege. Amazon Managed Workflows for Apache Airflow Serverless validates role access during workflow creation but runtime permission checks are performed by the target services.</p>
    pub fn get_role_arn(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_role_arn()
    }
    /// <p>An optional description of the workflow that you can use to provide additional context about the workflow's purpose and functionality.</p>
    pub fn description(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.description(input.into());
        self
    }
    /// <p>An optional description of the workflow that you can use to provide additional context about the workflow's purpose and functionality.</p>
    pub fn set_description(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_description(input);
        self
    }
    /// <p>An optional description of the workflow that you can use to provide additional context about the workflow's purpose and functionality.</p>
    pub fn get_description(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_description()
    }
    /// <p>The configuration for encrypting workflow data at rest and in transit. Specifies the encryption type and optional KMS key for customer-managed encryption.</p>
    pub fn encryption_configuration(mut self, input: crate::types::EncryptionConfiguration) -> Self {
        self.inner = self.inner.encryption_configuration(input);
        self
    }
    /// <p>The configuration for encrypting workflow data at rest and in transit. Specifies the encryption type and optional KMS key for customer-managed encryption.</p>
    pub fn set_encryption_configuration(mut self, input: ::std::option::Option<crate::types::EncryptionConfiguration>) -> Self {
        self.inner = self.inner.set_encryption_configuration(input);
        self
    }
    /// <p>The configuration for encrypting workflow data at rest and in transit. Specifies the encryption type and optional KMS key for customer-managed encryption.</p>
    pub fn get_encryption_configuration(&self) -> &::std::option::Option<crate::types::EncryptionConfiguration> {
        self.inner.get_encryption_configuration()
    }
    /// <p>The configuration for workflow logging. Specifies the CloudWatch log group where workflow execution logs are stored. Amazon Managed Workflows for Apache Airflow Serverless automatically exports worker logs and task-level information to the specified log group in your account using remote logging functionality. This provides comprehensive observability for debugging and monitoring workflow execution across the distributed, serverless environment.</p>
    pub fn logging_configuration(mut self, input: crate::types::LoggingConfiguration) -> Self {
        self.inner = self.inner.logging_configuration(input);
        self
    }
    /// <p>The configuration for workflow logging. Specifies the CloudWatch log group where workflow execution logs are stored. Amazon Managed Workflows for Apache Airflow Serverless automatically exports worker logs and task-level information to the specified log group in your account using remote logging functionality. This provides comprehensive observability for debugging and monitoring workflow execution across the distributed, serverless environment.</p>
    pub fn set_logging_configuration(mut self, input: ::std::option::Option<crate::types::LoggingConfiguration>) -> Self {
        self.inner = self.inner.set_logging_configuration(input);
        self
    }
    /// <p>The configuration for workflow logging. Specifies the CloudWatch log group where workflow execution logs are stored. Amazon Managed Workflows for Apache Airflow Serverless automatically exports worker logs and task-level information to the specified log group in your account using remote logging functionality. This provides comprehensive observability for debugging and monitoring workflow execution across the distributed, serverless environment.</p>
    pub fn get_logging_configuration(&self) -> &::std::option::Option<crate::types::LoggingConfiguration> {
        self.inner.get_logging_configuration()
    }
    /// <p>The version of the Amazon Managed Workflows for Apache Airflow Serverless engine that you want to use for this workflow. This determines the feature set, supported operators, and execution environment capabilities available to your workflow. Amazon Managed Workflows for Apache Airflow Serverless maintains backward compatibility across versions while introducing new features and improvements. Currently supports version 1 with plans for additional versions as the service evolves.</p>
    pub fn engine_version(mut self, input: i32) -> Self {
        self.inner = self.inner.engine_version(input);
        self
    }
    /// <p>The version of the Amazon Managed Workflows for Apache Airflow Serverless engine that you want to use for this workflow. This determines the feature set, supported operators, and execution environment capabilities available to your workflow. Amazon Managed Workflows for Apache Airflow Serverless maintains backward compatibility across versions while introducing new features and improvements. Currently supports version 1 with plans for additional versions as the service evolves.</p>
    pub fn set_engine_version(mut self, input: ::std::option::Option<i32>) -> Self {
        self.inner = self.inner.set_engine_version(input);
        self
    }
    /// <p>The version of the Amazon Managed Workflows for Apache Airflow Serverless engine that you want to use for this workflow. This determines the feature set, supported operators, and execution environment capabilities available to your workflow. Amazon Managed Workflows for Apache Airflow Serverless maintains backward compatibility across versions while introducing new features and improvements. Currently supports version 1 with plans for additional versions as the service evolves.</p>
    pub fn get_engine_version(&self) -> &::std::option::Option<i32> {
        self.inner.get_engine_version()
    }
    /// <p>Network configuration for the workflow execution environment, including VPC security groups and subnets for secure network access. When specified, Amazon Managed Workflows for Apache Airflow Serverless deploys ECS worker tasks in your customer VPC to provide secure connectivity to your resources. If not specified, tasks run in the service's default worker VPC with network isolation from other customers. This configuration enables secure access to VPC-only resources like RDS databases or private endpoints.</p>
    pub fn network_configuration(mut self, input: crate::types::NetworkConfiguration) -> Self {
        self.inner = self.inner.network_configuration(input);
        self
    }
    /// <p>Network configuration for the workflow execution environment, including VPC security groups and subnets for secure network access. When specified, Amazon Managed Workflows for Apache Airflow Serverless deploys ECS worker tasks in your customer VPC to provide secure connectivity to your resources. If not specified, tasks run in the service's default worker VPC with network isolation from other customers. This configuration enables secure access to VPC-only resources like RDS databases or private endpoints.</p>
    pub fn set_network_configuration(mut self, input: ::std::option::Option<crate::types::NetworkConfiguration>) -> Self {
        self.inner = self.inner.set_network_configuration(input);
        self
    }
    /// <p>Network configuration for the workflow execution environment, including VPC security groups and subnets for secure network access. When specified, Amazon Managed Workflows for Apache Airflow Serverless deploys ECS worker tasks in your customer VPC to provide secure connectivity to your resources. If not specified, tasks run in the service's default worker VPC with network isolation from other customers. This configuration enables secure access to VPC-only resources like RDS databases or private endpoints.</p>
    pub fn get_network_configuration(&self) -> &::std::option::Option<crate::types::NetworkConfiguration> {
        self.inner.get_network_configuration()
    }
    ///
    /// Adds a key-value pair to `Tags`.
    ///
    /// To override the contents of this collection use [`set_tags`](Self::set_tags).
    ///
    /// <p>A map of tags to assign to the workflow resource. Tags are key-value pairs that are used for resource organization and cost allocation.</p>
    pub fn tags(mut self, k: impl ::std::convert::Into<::std::string::String>, v: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.tags(k.into(), v.into());
        self
    }
    /// <p>A map of tags to assign to the workflow resource. Tags are key-value pairs that are used for resource organization and cost allocation.</p>
    pub fn set_tags(mut self, input: ::std::option::Option<::std::collections::HashMap<::std::string::String, ::std::string::String>>) -> Self {
        self.inner = self.inner.set_tags(input);
        self
    }
    /// <p>A map of tags to assign to the workflow resource. Tags are key-value pairs that are used for resource organization and cost allocation.</p>
    pub fn get_tags(&self) -> &::std::option::Option<::std::collections::HashMap<::std::string::String, ::std::string::String>> {
        self.inner.get_tags()
    }
    /// <p>The trigger mode for the workflow execution.</p>
    pub fn trigger_mode(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.trigger_mode(input.into());
        self
    }
    /// <p>The trigger mode for the workflow execution.</p>
    pub fn set_trigger_mode(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_trigger_mode(input);
        self
    }
    /// <p>The trigger mode for the workflow execution.</p>
    pub fn get_trigger_mode(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_trigger_mode()
    }
}