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Version:
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#!/usr/bin/python
# This file is part of Ansible
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
DOCUMENTATION = '''
---
module: execute_lambda
version_added: 1.0.0
short_description: Execute an AWS Lambda function
description:
- This module executes AWS Lambda functions, allowing synchronous and asynchronous
invocation.
extends_documentation_fragment:
- amazon.aws.aws
- amazon.aws.ec2
author: "Ryan Scott Brown (@ryansb) <ryansb@redhat.com>"
notes:
- Async invocation will always return an empty C(output) key.
- Synchronous invocation may result in a function timeout, resulting in an
empty C(output) key.
options:
name:
description:
- The name of the function to be invoked. This can only be used for
invocations within the calling account. To invoke a function in another
account, use I(function_arn) to specify the full ARN.
type: str
function_arn:
description:
- The name of the function to be invoked
type: str
tail_log:
description:
- If I(tail_log=yes), the result of the task will include the last 4 KB
of the CloudWatch log for the function execution. Log tailing only
works if you use synchronous invocation I(wait=yes). This is usually
used for development or testing Lambdas.
type: bool
default: false
wait:
description:
- Whether to wait for the function results or not. If I(wait=no)
the task will not return any results. To wait for the Lambda function
to complete, set I(wait=yes) and the result will be available in the
I(output) key.
type: bool
default: true
dry_run:
description:
- Do not *actually* invoke the function. A C(DryRun) call will check that
the caller has permissions to call the function, especially for
checking cross-account permissions.
type: bool
default: false
version_qualifier:
description:
- Which version/alias of the function to run. This defaults to the
C(LATEST) revision, but can be set to any existing version or alias.
See U(https://docs.aws.amazon.com/lambda/latest/dg/versioning-aliases.html)
for details.
type: str
payload:
description:
- A dictionary in any form to be provided as input to the Lambda function.
default: {}
type: dict
'''
EXAMPLES = '''
- community.aws.execute_lambda:
name: test-function
# the payload is automatically serialized and sent to the function
payload:
foo: bar
value: 8
register: response
# Test that you have sufficient permissions to execute a Lambda function in
# another account
- community.aws.execute_lambda:
function_arn: arn:aws:lambda:us-east-1:123456789012:function/some-function
dry_run: true
- community.aws.execute_lambda:
name: test-function
payload:
foo: bar
value: 8
wait: true
tail_log: true
register: response
# the response will have a `logs` key that will contain a log (up to 4KB) of the function execution in Lambda
# Pass the Lambda event payload as a json file.
- community.aws.execute_lambda:
name: test-function
payload: "{{ lookup('file','lambda_event.json') }}"
register: response
- community.aws.execute_lambda:
name: test-function
version_qualifier: PRODUCTION
'''
RETURN = '''
output:
description: Function output if wait=true and the function returns a value
returned: success
type: dict
sample: "{ 'output': 'something' }"
logs:
description: The last 4KB of the function logs. Only provided if I(tail_log) is true
type: str
returned: if I(tail_log) == true
status:
description: C(StatusCode) of API call exit (200 for synchronous invokes, 202 for async)
type: int
sample: 200
returned: always
'''
import base64
import json
try:
import botocore
except ImportError:
pass # Handled by AnsibleAWSModule
from ansible_collections.amazon.aws.plugins.module_utils.core import AnsibleAWSModule
from ansible_collections.amazon.aws.plugins.module_utils.core import is_boto3_error_code
def main():
argument_spec = dict(
name=dict(),
function_arn=dict(),
wait=dict(default=True, type='bool'),
tail_log=dict(default=False, type='bool'),
dry_run=dict(default=False, type='bool'),
version_qualifier=dict(),
payload=dict(default={}, type='dict'),
)
module = AnsibleAWSModule(
argument_spec=argument_spec,
supports_check_mode=True,
mutually_exclusive=[
['name', 'function_arn'],
]
)
name = module.params.get('name')
function_arn = module.params.get('function_arn')
await_return = module.params.get('wait')
dry_run = module.params.get('dry_run')
tail_log = module.params.get('tail_log')
version_qualifier = module.params.get('version_qualifier')
payload = module.params.get('payload')
if not (name or function_arn):
module.fail_json(msg="Must provide either a function_arn or a name to invoke.")
try:
client = module.client('lambda')
except (botocore.exceptions.ClientError, botocore.exceptions.BotoCoreError) as e:
module.fail_json_aws(e, msg='Failed to connect to AWS')
invoke_params = {}
if await_return:
# await response
invoke_params['InvocationType'] = 'RequestResponse'
else:
# fire and forget
invoke_params['InvocationType'] = 'Event'
if dry_run or module.check_mode:
# dry_run overrides invocation type
invoke_params['InvocationType'] = 'DryRun'
if tail_log and await_return:
invoke_params['LogType'] = 'Tail'
elif tail_log and not await_return:
module.fail_json(msg="The `tail_log` parameter is only available if "
"the invocation waits for the function to complete. "
"Set `wait` to true or turn off `tail_log`.")
else:
invoke_params['LogType'] = 'None'
if version_qualifier:
invoke_params['Qualifier'] = version_qualifier
if payload:
invoke_params['Payload'] = json.dumps(payload)
if function_arn:
invoke_params['FunctionName'] = function_arn
elif name:
invoke_params['FunctionName'] = name
if not module.check_mode:
wait_for_lambda(client, module, name)
try:
response = client.invoke(**invoke_params)
except is_boto3_error_code('ResourceNotFoundException') as nfe:
module.fail_json_aws(nfe, msg="Could not find Lambda to execute. Make sure "
"the ARN is correct and your profile has "
"permissions to execute this function.")
except botocore.exceptions.ClientError as ce: # pylint: disable=duplicate-except
module.fail_json_aws(ce, msg="Client-side error when invoking Lambda, check inputs and specific error")
except botocore.exceptions.ParamValidationError as ve: # pylint: disable=duplicate-except
module.fail_json_aws(ve, msg="Parameters to `invoke` failed to validate")
except Exception as e:
module.fail_json_aws(e, msg="Unexpected failure while invoking Lambda function")
results = {
'logs': '',
'status': response['StatusCode'],
'output': '',
}
if response.get('LogResult'):
try:
# logs are base64 encoded in the API response
results['logs'] = base64.b64decode(response.get('LogResult', ''))
except Exception as e:
module.fail_json_aws(e, msg="Failed while decoding logs")
if invoke_params['InvocationType'] == 'RequestResponse':
try:
results['output'] = json.loads(response['Payload'].read().decode('utf8'))
except Exception as e:
module.fail_json_aws(e, msg="Failed while decoding function return value")
if isinstance(results.get('output'), dict) and any(
[results['output'].get('stackTrace'), results['output'].get('errorMessage')]):
# AWS sends back stack traces and error messages when a function failed
# in a RequestResponse (synchronous) context.
template = ("Function executed, but there was an error in the Lambda function. "
"Message: {errmsg}, Type: {type}, Stack Trace: {trace}")
error_data = {
# format the stacktrace sent back as an array into a multiline string
'trace': '\n'.join(
[' '.join([
str(x) for x in line # cast line numbers to strings
]) for line in results.get('output', {}).get('stackTrace', [])]
),
'errmsg': results['output'].get('errorMessage'),
'type': results['output'].get('errorType')
}
module.fail_json(msg=template.format(**error_data), result=results)
module.exit_json(changed=True, result=results)
def wait_for_lambda(client, module, name):
try:
waiter = client.get_waiter('function_active')
waiter.wait(FunctionName=name)
except botocore.exceptions.WaiterError as e:
module.fail_json_aws(e, msg='Timeout while waiting on lambda to be Active')
except (botocore.exceptions.ClientError, botocore.exceptions.BotoCoreError) as e:
module.fail_json_aws(e, msg='Failed while waiting on lambda to be Active')
if __name__ == '__main__':
main()