Function Compute:Asynchronous tasks

Limits

• Scenario limits

  Asynchronous tasks offer more features but create more system overhead. You should disable task mode in the following scenarios:

  • You are highly sensitive to request processing latency and require an average latency of less than 100 ms.

  • You require thousands or more asynchronous invocations per second.

• Region limits

  Asynchronous tasks are supported in the following regions: China (Hangzhou), China (Shanghai), China (Qingdao), China (Beijing), China (Zhangjiakou), China (Ulanqab), China (Shenzhen), China (Chengdu), China (Hong Kong), Singapore, UK (London), US (Silicon Valley), US (Virginia), Germany (Frankfurt), Malaysia (Kuala Lumpur), Indonesia (Jakarta), Thailand (Bangkok), Japan (Tokyo), and South Korea (Seoul).

• Time limits

  You can query task status information only for the last 7 days.

Comparison between asynchronous tasks and Kubernetes Jobs

To run asynchronous tasks, you can use the asynchronous task feature of Function Compute or the Jobs feature of Kubernetes. Function Compute asynchronous tasks provide an out-of-the-box platform for running asynchronous tasks that is more efficient, controllable, and observable. The following table compares the two features.

Task management

Asynchronous task statuses

For each task invocation, Function Compute records the status change process and provides a real-time status query feature. You can view the specific status of a task using the SDK or in the Function Compute console. The following task statuses are available:

You can call the GetAsyncTask - Get an asynchronous task API operation to retrieve the details of a task execution. You can also call the ListAsyncTasks - Get a list of asynchronous tasks API operation to filter tasks by a specific status.

Manage tasks

{
  "asyncTask": true
}

Event triggers

You can trigger asynchronous tasks by creating triggers that support asynchronous invocation. The following triggers support asynchronous invocation:

• HTTP trigger

• Time trigger

• OSS trigger

• MNS topic trigger

• Triggers implemented through EventBridge, including the following:

  • Simple Message Queue (formerly MNS) queue trigger

  • RocketMQ trigger

  • RabbitMQ trigger

  • Kafka trigger

  • MQTT trigger

  • DTS trigger

  Important

  Make sure that the Invocation Method for HTTP triggers and triggers implemented through EventBridge is set to Asynchronous Invocation.

Prevent duplicate task submissions

To prevent duplicate task executions, Function Compute lets you set a globally unique ID for each submitted task. If an asynchronous API call to submit a task fails, for example, due to a timeout, you can retry the submission with the same ID. For more information about retry methods, see Retry policy.

Function Compute provides the TaskID concept, which is a globally unique ID. We recommend that you specify this ID every time you submit a task and retry in case of a timeout. Function Compute validates duplicate task submissions. If a task with the same ID is submitted again, the request is considered a duplicate and is rejected with a 409 error.

Set a TaskID

You can submit a task execution in the Function Compute console, using Serverless Devs, or by calling an API operation. To set a TaskID, set the x-fc-async-task-id parameter when you trigger the function execution.

For sample code on how to set a TaskID when triggering a task execution, see Sample code.

Task monitoring

You can use the task monitoring metrics provided by Function Compute to retrieve the real-time status of asynchronous tasks and promptly detect issues such as errors or timeouts.

Prerequisites

A function is created. For more information, see Create a function.

Procedure

1. Log on to the Function Compute console. In the left-side navigation pane, click Functions.

2. In the top navigation bar, select a region. On the Functions page, click the target function.

3. On the details page of the target function, choose the Monitoring tab to view metrics related to asynchronous invocations and the resource usage of asynchronous task instances. For more information about monitoring metrics, see Monitoring metrics.

   • Click the Function Metrics tab to view metrics related to asynchronous invocations, such as Async Invocation Status, Async Latency, Async Event Triggered, and Async Queue Size.

   • Click the Instance Metrics tab to view the resource usage of asynchronous task instances.

     Note

     Before you can enable instance-level metrics, you must first enable the logging feature. For more information, see Configure logging.

4. Set an alert rule for a metric.

   If you want to monitor a metric, such as memory usage or vCPU usage, click the icon in the upper-right corner of the metric. You are redirected to the Create Metric Alert Rule panel. Set the alert conditions and threshold as prompted, and then click OK.

   The following figure shows how to set an alert rule. The parameter settings in the figure indicate that if the number of backlogged asynchronous function invocations is greater than or equal to 5, a medium-level alert is reported to the contact around the clock using DingTalk, email, phone, and webhook.

   

Task orchestration

When integrated with CloudFlow, asynchronous function invocations can be used for task flows in large-scale and complex scenarios. You can use states such as Pass, Map, and Parallel to orchestrate Function Compute asynchronous tasks. CloudFlow reliably coordinates task execution according to the predefined steps, tracks the status transitions of each task, and executes the retry logic that you define when necessary to ensure that the tasks are successfully completed. For more information, see Integrate Function Compute.

Prerequisites

• An asynchronous task is created. For more information, see Task management.

• Function Compute is granted the permissions to access CloudFlow. For more information, see Grant Function Compute permissions to access other Alibaba Cloud services using function roles.

Procedure

1. Log on to the CloudFlow console. In the top navigation bar, select a region.

2. In the left-side navigation pane, click Workflows. On the Workflows page, click Create Workflow.

3. In the Create Workflow dialog box, select a method and a mode to create the workflow.

   CloudFlow supports standard and express workflows. For more information about the two modes, see Standard workflows and express workflows. For more information about the operations, see Create a workflow based on a blank canvas.

4. Edit the workflow that you created in the previous step.

   1. Edit the flow.

      You can edit the flow in CloudFlow Studio or using YAML. This topic uses YAML as an example.

      On the flow details page, click YAML in the upper-right corner. Enter the Flow Definition Language in the code editor on the left and click Save.

      The following example shows the code.

      Type: StateMachine
      Name: MyFlow
      SpecVersion: v1
      StartAt: InvokeFunction
      States:
        - Type: Task
          Name: InvokeFunction
          Action: FC:InvokeFunction
          TaskMode: RequestComplete
          Parameters:
            invocationType: Async
            resourceArn: acs:fc:us-west-1:103435468****:functions/func-i1****/LATEST
          End: true

   2. Configure a flow role.

      On the flow details page, click Workflow Configuration in the upper-right corner. Select an Execution Role and click Save.

      Note

      Make sure that the role configured for the flow is granted the AliyunFCInvocationAccess access policy.

5. On the flow details page, you can click Execute in the upper-right corner to trigger the workflow for testing.