Awso_mwaa_serverless_eioSourceval create_workflow :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.CreateWorkflowRequest.t ->
(Awso_mwaa_serverless.Values.CreateWorkflowResponse.t,
Awso_mwaa_serverless.Values.CreateWorkflowResponse.error)
Result.tval delete_workflow :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.DeleteWorkflowRequest.t ->
(Awso_mwaa_serverless.Values.DeleteWorkflowResponse.t,
Awso_mwaa_serverless.Values.DeleteWorkflowResponse.error)
Result.tval get_task_instance :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.GetTaskInstanceRequest.t ->
(Awso_mwaa_serverless.Values.GetTaskInstanceResponse.t,
Awso_mwaa_serverless.Values.GetTaskInstanceResponse.error)
Result.tval get_workflow :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.GetWorkflowRequest.t ->
(Awso_mwaa_serverless.Values.GetWorkflowResponse.t,
Awso_mwaa_serverless.Values.GetWorkflowResponse.error)
Result.tval get_workflow_run :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.GetWorkflowRunRequest.t ->
(Awso_mwaa_serverless.Values.GetWorkflowRunResponse.t,
Awso_mwaa_serverless.Values.GetWorkflowRunResponse.error)
Result.tval list_tags_for_resource :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.ListTagsForResourceRequest.t ->
(Awso_mwaa_serverless.Values.ListTagsForResourceResponse.t,
Awso_mwaa_serverless.Values.ListTagsForResourceResponse.error)
Result.tval list_task_instances :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.ListTaskInstancesRequest.t ->
(Awso_mwaa_serverless.Values.ListTaskInstancesResponse.t,
Awso_mwaa_serverless.Values.ListTaskInstancesResponse.error)
Result.tval list_workflow_runs :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.ListWorkflowRunsRequest.t ->
(Awso_mwaa_serverless.Values.ListWorkflowRunsResponse.t,
Awso_mwaa_serverless.Values.ListWorkflowRunsResponse.error)
Result.tval list_workflow_versions :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.ListWorkflowVersionsRequest.t ->
(Awso_mwaa_serverless.Values.ListWorkflowVersionsResponse.t,
Awso_mwaa_serverless.Values.ListWorkflowVersionsResponse.error)
Result.tval list_workflows :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.ListWorkflowsRequest.t ->
(Awso_mwaa_serverless.Values.ListWorkflowsResponse.t,
Awso_mwaa_serverless.Values.ListWorkflowsResponse.error)
Result.tval start_workflow_run :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.StartWorkflowRunRequest.t ->
(Awso_mwaa_serverless.Values.StartWorkflowRunResponse.t,
Awso_mwaa_serverless.Values.StartWorkflowRunResponse.error)
Result.tval stop_workflow_run :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.StopWorkflowRunRequest.t ->
(Awso_mwaa_serverless.Values.StopWorkflowRunResponse.t,
Awso_mwaa_serverless.Values.StopWorkflowRunResponse.error)
Result.tval tag_resource :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.TagResourceRequest.t ->
(Awso_mwaa_serverless.Values.TagResourceResponse.t,
Awso_mwaa_serverless.Values.TagResourceResponse.error)
Result.tval untag_resource :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.UntagResourceRequest.t ->
(Awso_mwaa_serverless.Values.UntagResourceResponse.t,
Awso_mwaa_serverless.Values.UntagResourceResponse.error)
Result.tval update_workflow :
?endpoint_url:string ->
?cfg:Awso_eio.Cfg.t ->
Awso_mwaa_serverless.Values.UpdateWorkflowRequest.t ->
(Awso_mwaa_serverless.Values.UpdateWorkflowResponse.t,
Awso_mwaa_serverless.Values.UpdateWorkflowResponse.error)
Result.tinclude module type of struct include Awso_mwaa_serverless.Values endval structure_to_value_aux :
('a * 'b option) list ->
f:(('a * 'b) list -> 'c) ->
[> `Structure of 'c ]val structure_to_wrapped_value :
wrapper:'a ->
response:'a ->
('b * 'c option) list ->
[> `Structure of ('a * [> `Structure of ('b * 'c) list ]) list ]Contains information about a field that failed validation, including the field name and a descriptive error message.
Specifies the Amazon S3 location of a workflow definition file. This structure contains the bucket name, object key, and optional version ID for the workflow definition. Amazon Managed Workflows for Apache Airflow Serverless takes a snapshot of the definition file at the time of workflow creation or update, ensuring that the workflow behavior remains consistent even if the source file is modified. The definition must be a valid YAML file that uses supported Amazon Web Services operators and Amazon Managed Workflows for Apache Airflow Serverless syntax.
The configuration to use to schedule automated workflow execution using cron expressions. Amazon Managed Workflows for Apache Airflow Serverless integrates with EventBridge Scheduler to provide cost-effective, timezone-aware scheduling capabilities. The service supports both time-based and event-based scheduling (event-based scheduling available post-GA). When a workflow definition includes scheduling information, Amazon Managed Workflows for Apache Airflow Serverless automatically configures the appropriate triggers and ensures only one version of a workflow has an active schedule at any time.
Summary information about a workflow run's execution details, including status and timing information.
Summary information about a workflow, including basic identification and metadata.
Summary information about a workflow version, including identification and configuration details.
Summary information about a workflow run, including basic identification and status information.
Summary information about a task instance within a workflow run, including its status and execution details.
You do not have sufficient permission to perform this action.
You cannot create a resource that already exists, or the resource is in a state that prevents the requested operation.
An unexpected server-side error occurred during request processing.
The operation timed out.
The specified resource was not found. You can only access or modify a resource that already exists.
module ServiceQuotaExceededException =
Awso_mwaa_serverless.Values.ServiceQuotaExceededExceptionThe request exceeds the service quota for Amazon Managed Workflows for Apache Airflow Serverless resources. This can occur when you attempt to create more workflows than allowed, exceed concurrent workflow run limits, or surpass task execution limits. Amazon Managed Workflows for Apache Airflow Serverless implements admission control using DynamoDB-based counters to manage resource utilization across the multi-tenant environment. Contact Amazon Web Services Support to request quota increases if you need higher limits for your use case.
The request was denied because too many requests were made in a short period, exceeding the service rate limits. Amazon Managed Workflows for Apache Airflow Serverless implements throttling controls to ensure fair resource allocation across all customers in the multi-tenant environment. This helps maintain service stability and performance. If you encounter throttling, implement exponential backoff and retry logic in your applications, or consider distributing your API calls over a longer time period.
The specified request parameters are invalid, missing, or inconsistent with Amazon Managed Workflows for Apache Airflow Serverless service requirements. This can occur when workflow definitions contain unsupported operators, when required IAM permissions are missing, when S3 locations are inaccessible, or when network configurations are invalid. The service validates workflow definitions, execution roles, and resource configurations to ensure compatibility with the managed Airflow environment and security requirements.
Configuration for workflow logging that specifies where you should store your workflow execution logs. Amazon Managed Workflows for Apache Airflow Serverless provides comprehensive logging capabilities that capture workflow execution details, task-level information, and system events. Logs are automatically exported to your specified CloudWatch log group using remote logging functionality, providing centralized observability across the distributed, multi-tenant execution environment. This enables effective debugging, monitoring, and compliance auditing of workflow executions.
Network configuration for workflow execution. Specifies VPC security groups and subnets for secure network access. When provided, Amazon Managed Workflows for Apache Airflow Serverless deploys ECS worker tasks in your specified VPC configuration, enabling secure access to VPC-only resources. The service uses a proxy API container architecture where one container handles external communication while the worker container connects to your VPC for task execution. This design provides both security isolation and connectivity flexibility.
module ListWorkflowsRequestMaxResultsInteger =
Awso_mwaa_serverless.Values.ListWorkflowsRequestMaxResultsIntegermodule ListWorkflowVersionsRequestMaxResultsInteger =
Awso_mwaa_serverless.Values.ListWorkflowVersionsRequestMaxResultsIntegermodule ListWorkflowRunsRequestMaxResultsInteger =
Awso_mwaa_serverless.Values.ListWorkflowRunsRequestMaxResultsIntegermodule ListTaskInstancesRequestMaxResultsInteger =
Awso_mwaa_serverless.Values.ListTaskInstancesRequestMaxResultsIntegerDetailed information about a workflow run execution, including timing, status, error information, and associated task instances. This structure provides comprehensive visibility into the workflow execution lifecycle within the Amazon Managed Workflows for Apache Airflow Serverless serverless environment. The service tracks execution across distributed ECS worker tasks and provides detailed timing information, error diagnostics, and task instance relationships to support effective monitoring and troubleshooting of complex workflow executions.
Configuration for encrypting workflow data at rest and in transit. Amazon Managed Workflows for Apache Airflow Serverless provides comprehensive encryption capabilities to protect sensitive workflow data, parameters, and execution logs. When using customer-managed keys, the service integrates with Amazon Web Services KMS to provide fine-grained access control and audit capabilities. Encryption is applied consistently across the distributed execution environment including task containers, metadata storage, and log streams.
Updates an existing workflow with new configuration settings. This operation allows you to modify the workflow definition, role, and other settings. When you update a workflow, Amazon Managed Workflows for Apache Airflow Serverless automatically creates a new version with the updated configuration and disables scheduling on all previous versions to ensure only one version is actively scheduled at a time. The update operation maintains workflow history while providing a clean transition to the new configuration.
Updates an existing workflow with new configuration settings. This operation allows you to modify the workflow definition, role, and other settings. When you update a workflow, Amazon Managed Workflows for Apache Airflow Serverless automatically creates a new version with the updated configuration and disables scheduling on all previous versions to ensure only one version is actively scheduled at a time. The update operation maintains workflow history while providing a clean transition to the new configuration.
Removes tags from an Amazon Managed Workflows for Apache Airflow Serverless resource. This operation removes the specified tags from the resource.
Removes tags from an Amazon Managed Workflows for Apache Airflow Serverless resource. This operation removes the specified tags from the resource.
Adds tags to an Amazon Managed Workflows for Apache Airflow Serverless resource. Tags are key-value pairs that help you organize and categorize your resources.
Adds tags to an Amazon Managed Workflows for Apache Airflow Serverless resource. Tags are key-value pairs that help you organize and categorize your resources.
Stops a running workflow execution. This operation terminates all running tasks and prevents new tasks from starting. Amazon Managed Workflows for Apache Airflow Serverless gracefully shuts down the workflow execution by stopping task scheduling and terminating active ECS worker containers. The operation transitions the workflow run to a STOPPING state and then to STOPPED once all cleanup is complete. In-flight tasks may complete or be terminated depending on their current execution state.
Stops a running workflow execution. This operation terminates all running tasks and prevents new tasks from starting. Amazon Managed Workflows for Apache Airflow Serverless gracefully shuts down the workflow execution by stopping task scheduling and terminating active ECS worker containers. The operation transitions the workflow run to a STOPPING state and then to STOPPED once all cleanup is complete. In-flight tasks may complete or be terminated depending on their current execution state.
Starts a new execution of a workflow. This operation creates a workflow run that executes the tasks that are defined in the workflow. Amazon Managed Workflows for Apache Airflow Serverless schedules the workflow execution across its managed Airflow environment, automatically scaling ECS worker tasks based on the workload. The service handles task isolation, dependency resolution, and provides comprehensive monitoring and logging throughout the execution lifecycle.
Starts a new execution of a workflow. This operation creates a workflow run that executes the tasks that are defined in the workflow. Amazon Managed Workflows for Apache Airflow Serverless schedules the workflow execution across its managed Airflow environment, automatically scaling ECS worker tasks based on the workload. The service handles task isolation, dependency resolution, and provides comprehensive monitoring and logging throughout the execution lifecycle.
Lists all workflows in your account, with optional pagination support. This operation returns summary information for workflows, showing only the most recently created version of each workflow. Amazon Managed Workflows for Apache Airflow Serverless maintains workflow metadata in a highly available, distributed storage system that enables efficient querying and filtering. The service implements proper access controls to ensure you can only view workflows that you have permissions to access, supporting both individual and team-based workflow management scenarios.
Lists all workflows in your account, with optional pagination support. This operation returns summary information for workflows, showing only the most recently created version of each workflow. Amazon Managed Workflows for Apache Airflow Serverless maintains workflow metadata in a highly available, distributed storage system that enables efficient querying and filtering. The service implements proper access controls to ensure you can only view workflows that you have permissions to access, supporting both individual and team-based workflow management scenarios.
module ListWorkflowVersionsResponse =
Awso_mwaa_serverless.Values.ListWorkflowVersionsResponseLists all versions of a specified workflow, with optional pagination support.
Lists all versions of a specified workflow, with optional pagination support.
Lists all runs for a specified workflow, with optional pagination and filtering support.
Lists all runs for a specified workflow, with optional pagination and filtering support.
Lists all task instances for a specific workflow run, with optional pagination support.
Lists all task instances for a specific workflow run, with optional pagination support.
Lists all tags that are associated with a specified Amazon Managed Workflows for Apache Airflow Serverless resource.
Lists all tags that are associated with a specified Amazon Managed Workflows for Apache Airflow Serverless resource.
Retrieves detailed information about a specific workflow run, including its status, execution details, and task instances.
Retrieves detailed information about a specific workflow run, including its status, execution details, and task instances.
Retrieves detailed information about a workflow, including its configuration, status, and metadata.
Retrieves detailed information about a workflow, including its configuration, status, and metadata.
Retrieves detailed information about a specific task instance within a workflow run. Task instances represent individual tasks that are executed as part of a workflow in the Amazon Managed Workflows for Apache Airflow Serverless environment. Each task instance runs in an isolated ECS container with dedicated resources and security boundaries. The service tracks task execution state, retry attempts, and provides detailed timing and error information for troubleshooting and monitoring purposes.
Retrieves detailed information about a specific task instance within a workflow run. Task instances represent individual tasks that are executed as part of a workflow in the Amazon Managed Workflows for Apache Airflow Serverless environment. Each task instance runs in an isolated ECS container with dedicated resources and security boundaries. The service tracks task execution state, retry attempts, and provides detailed timing and error information for troubleshooting and monitoring purposes.
Deletes a workflow and all its versions. This operation permanently removes the workflow and cannot be undone. Amazon Managed Workflows for Apache Airflow Serverless ensures that all associated resources are properly cleaned up, including stopping any running executions, removing scheduled triggers, and cleaning up execution history. The deletion process respects the multi-tenant isolation boundaries and ensures that no residual data or configurations remain that could affect other customers or workflows.
Deletes a workflow and all its versions. This operation permanently removes the workflow and cannot be undone. Amazon Managed Workflows for Apache Airflow Serverless ensures that all associated resources are properly cleaned up, including stopping any running executions, removing scheduled triggers, and cleaning up execution history. The deletion process respects the multi-tenant isolation boundaries and ensures that no residual data or configurations remain that could affect other customers or workflows.
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.
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.