Function Compute (2.0):Configure common layers for a function

Common layers supported by Function Compute

Function Compute supports the following types of common layers. This section lists some common layers. For more information about all the common layers supported by Function Compute, see Common layers.

If you fail to find the layer that you want to use, Contact Us.

Custom Runtime

Custom runtimes, such as Python 3.10 and Node.js 17, are included. In addition, collections of the dependency libraries for some custom runtimes are provided. For example, the common layer Python310-Package-Collection contains some dependency libraries commonly used in Python.

Common dependency libraries

Web framework

Alibaba Cloud SDKs

Configure common layers by using the console

Prerequisites

Procedure

1. Log on to the Function Compute console. In the left-side navigation pane, click Services & Functions.
2. In the top navigation bar, select a region. On the Services page, click the desired service.
3. On the Functions page, find the desired function and click Configure in the Actions column.
4. In the Layers section, click + Add Layer and select Add Official Common Layer from the drop-down list.
5. In the Official Common Layer drop-down list, view the layer description and license information and select a common layer. Select a layer version from the Layer Version drop-down list, and then click Save.

Configure common layers by using Serverless Devs

Prerequisites

• Install Serverless Devs and Docker
• Configure Serverless Devs

Procedure

1. Run the following command to find the custom layers in the specified region:

   s cli fc layer list --official --region cn-hangzhou

   After the execution is successful, return to the list of common layers. Obtain and record the new ARN (arnV2) of the desired layer.

   -
     layerName:         Aliyun-DataX
     arn:
     arnV2:             acs:fc:cn-hangzhou:official:layers/Aliyun-DataX/versions/1
     version:           1
     acl:               1
     description:       Aliyun DataX for python (datax_v202205)
     compatibleRuntime:
       - custom
       - python2.7
       - python3
       - python3.9
   -
     layerName:         Python36-SciPy1x
     arn:
     arnV2:             acs:fc:cn-hangzhou:official:layers/Python36-SciPy1x/versions/1
     version:           1
     acl:               1
     description:       SciPy Layer for python36(scipy-1.5.4,numpy-1.19.5)
     compatibleRuntime:
       - custom
       - python3

   The following content describes the code snippets in the sample code:

   • layerName: the name of the layer.
   • version: the version of the layer.
   • arn: the original ARN of the layer. The original ARN can be used only in custom layers.
   • arnV2: the new ARN of the layer. The new ARN can be used only in public layers.
   • acl: the permissions of the layer. The digit 0 specifies that the layer is private and the digit 1 specifies that the layer is public. By default, the public layers are public. The custom layers can be set to private or public.
   • description: the description of the layer.
   • compatibleRuntime: the list of compatible runtimes.
2. Create the s.yaml file in any directory and enter the new ARN of the layer.
   Example:

   edition: 1.0.0          #  The version of the YAML syntax. The version complies with the semantic versioning specification.
   name: fcDeployApp       #  The name of the project.
   access: "default"  #  The alias of the key.
   
   services:
     fc-deploy-test: #  The name of the service.
       component: fc  # The name of the component.
       props: # The property value of the component.
         region: cn-hangzhou
         service:
           name: fctest
           description: 'test'
           internetAccess: true
         function:
           name: emoji # The name of the function.
           description: this is a layer demo
           runtime: python3.9
           codeUri: ./
           handler: index.handler
           memorySize: 128
           timeout: 6
           layers:    # The layers bound to the function. The values are the ARNs of the layers.
             - acs:fc:cn-hangzhou:official:layers/Aliyun-DataX/versions/1
             - acs:fc:cn-hangzhou:official:layers/Python39-SciPy1x/versions/1

3. Run the following command in the directory in which the s.yaml file is stored to deploy the function and configure the layers for the function:

   s deploy

Additional information

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