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[ aws . appflow ]



Cancels active runs for a flow.

You can cancel all of the active runs for a flow, or you can cancel specific runs by providing their IDs.

You can cancel a flow run only when the run is in progress. You can't cancel a run that has already completed or failed. You also can't cancel a run that's scheduled to occur but hasn't started yet. To prevent a scheduled run, you can deactivate the flow with the StopFlow action.

You cannot resume a run after you cancel it.

When you send your request, the status for each run becomes CancelStarted . When the cancellation completes, the status becomes Canceled .


When you cancel a run, you still incur charges for any data that the run already processed before the cancellation. If the run had already written some data to the flow destination, then that data remains in the destination. If you configured the flow to use a batch API (such as the Salesforce Bulk API 2.0), then the run will finish reading or writing its entire batch of data after the cancellation. For these operations, the data processing charges for Amazon AppFlow apply. For the pricing information, see Amazon AppFlow pricing .

See also: AWS API Documentation


--flow-name <value>
[--execution-ids <value>]
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]
[--endpoint-url <value>]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]


--flow-name (string)

The name of a flow with active runs that you want to cancel.

--execution-ids (list)

The ID of each active run to cancel. These runs must belong to the flow you specify in your request.

If you omit this parameter, your request ends all active runs that belong to the flow.



"string" "string" ...

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command's default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination.

--output (string)

The formatting style for command output.

  • json
  • text
  • table

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

  • on
  • off
  • auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.


invalidExecutions -> (list)

The IDs of runs that Amazon AppFlow couldn't cancel. These runs might be ineligible for canceling because they haven't started yet or have already completed.