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Read this on the main serverless docs site

AWS - Invoke

Invokes deployed function. It allows to send event data to the function, read logs and display other important information of the function invocation.

serverless invoke [local] --function functionName

Note: Please refer to this guide for event data passing when your function uses the http event with a Lambda Proxy integration.

Options

  • --function or -f The name of the function in your service that you want to invoke. Required.
  • --stage or -s The stage in your service you want to invoke your function in.
  • --region or -r The region in your stage that you want to invoke your function in.
  • --data or -d String data to be passed as an event to your function. By default data is read from standard input.
  • --raw Pass data as a raw string even if it is JSON. If not set, JSON data are parsed and passed as an object.
  • --path or -p The path to a json file with input data to be passed to the invoked function. This path is relative to the root directory of the service.
  • --type or -t The type of invocation. Either RequestResponse, Event or DryRun. Default is RequestResponse.
  • --log or -l If set to true and invocation type is RequestResponse, it will output logging data of the invocation. Default is false.

Provided lifecycle events

  • invoke:invoke

Invoke Local

Invokes a function locally for testing and logs the output. Keep in mind that we mock the context with simple mock data.

serverless invoke local --function functionName

Options

  • --function or -f The name of the function in your service that you want to invoke locally. Required.
  • --path or -p The path to a json file holding input data to be passed to the invoked function as the event. This path is relative to the root directory of the service.
  • --data or -d String data to be passed as an event to your function. Keep in mind that if you pass both --path and --data, the data included in the --path file will overwrite the data you passed with the --data flag.
  • --raw Pass data as a raw string even if it is JSON. If not set, JSON data are parsed and passed as an object.
  • --contextPath or -x, The path to a json file holding input context to be passed to the invoked function. This path is relative to the root directory of the service.
  • --context or -c, String data to be passed as a context to your function. Same like with --data, context included in --contextPath will overwrite the context you passed with --context flag.

Examples

AWS

serverless invoke --function functionName --stage dev --region us-east-1

This example will invoke your deployed function named functionName in region us-east-1 in stage dev. This will output the result of the invocation in your terminal.

Function invocation with data

serverless invoke --function functionName --stage dev --region us-east-1 --data "hello world"

Function invocation with data from standard input

node dataGenerator.js | serverless invoke --function functionName --stage dev --region us-east-1

Function invocation with logging

serverless invoke --function functionName --stage dev --region us-east-1 --log

Just like the first example, but will also outputs logging information about your invocation.

Function invocation with data passing

serverless invoke --function functionName --stage dev --region us-east-1 --path lib/data.json

This example will pass the json data in the lib/data.json file (relative to the root of the service) while invoking the specified/deployed function.

Example data.json

{
  "resource": "/",
  "path": "/",
  "httpMethod": "GET",
  //  etc. //
}

Local function invocation with custom context

serverless invoke local --function functionName --context "hello world"

Local function invocation with context passing

serverless invoke local --function functionName --contextPath lib/context.json

This example will pass the json context in the lib/context.json file (relative to the root of the service) while invoking the specified/deployed function.

Limitations

Currently, invoke local only supports the NodeJs and Python runtimes.

Resource permissions

Lambda functions assume an IAM role during execution: the framework creates this role, and set all the permission provided in the iamRoleStatements section of serverless.yml.

Unless you explicitly state otherwise, every call to the AWS SDK inside the lambda function is made using this role (a temporary pair of key / secret is generated and set by AWS as environment variables, AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY).

When you use serverless invoke local, the situation is quite different: the role isn't available (the function is executed on your local machine), so unless you set a different user directly in the code (or via a key pair of environment variables), the AWS SDK will use the default profile specified inside you AWS credential configuration file.

Take a look to the official AWS documentation (in this particular instance, for the javascript SDK, but should be similar for all SDKs):

Whatever approach you decide to implement, be aware: the set of permissions might be (and probably is) different, so you won't have an exact simulation of the real IAM policy in place.