Sometimes, attempting to run lambdas will return this type of error:
```
{"Type": "Server", "message": "Error executing Lambda function arn:aws:lambda:ap-northeast-1:000000000000:function:service-stage-functionName: An error occurred (ResourceAlreadyExistsException) when calling the CreateLogGroup operation: The specified log group already exists Traceback (most recent call last):\n 
File \"/opt/code/localstack/localstack/services/awslambda/lambda_api.py\", line 338, in run_lambda\n 
event, context=context, version=version, asynchronous=asynchronous)\n 
File \"/opt/code/localstack/localstack/services/awslambda/lambda_executors.py\", line 81, in execute\n 
return do_execute()\n File \"/opt/code/localstack/localstack/services/awslambda/lambda_executors.py\", line 70, in do_execute\n self._store_logs(func_details, log_output, invocation_time)\n 
File \"/opt/code/localstack/localstack/services/awslambda/lambda_executors.py\", line 105, in _store_logs\n logs_client.create_log_group(logGroupName=log_group_name)\n 
File \"/opt/code/localstack/.venv/lib/python3.6/site-packages/botocore/client.py\", line 357, in _api_call\n 
return self._make_api_call(operation_name, kwargs)\n 
File \"/opt/code/localstack/.venv/lib/python3.6/site-packages/botocore/client.py\", line 661, in _make_api_call\n 
raise error_class(parsed_response, operation_name)\n
botocore.errorfactory.ResourceAlreadyExistsException: An error occurred (ResourceAlreadyExistsException) when calling the CreateLogGroup operation: The specified log group already exists\n", "__type": "InternalFailure"}
```
I am not yet sure if there are any particular settings that cause it, since it does not occur for certain deployments.

Will update if I can figure out the exact configuration.
sm_name = resolve_refs_recursively(stack_name, sm_name, resources)
            sfn_client = aws_stack.connect_to_service('stepfunctions')
            state_machines = sfn_client.list_state_machines()['stateMachines']
            sm_arn = [m['stateMachineArn'] for m in state_machines if m['name'] == sm_name]
            if not sm_arn:
                return None
            result = sfn_client.describe_state_machine(stateMachineArn=sm_arn[0])
            return result
        elif resource_type == 'StepFunctions::Activity':
            act_name = resource_props.get('Name') or resource_id
            act_name = resolve_refs_recursively(stack_name, act_name, resources)
            sfn_client = aws_stack.connect_to_service('stepfunctions')
            activities = sfn_client.list_activities()['activities']
            result = [a['activityArn'] for a in activities if a['name'] == act_name]
            if not result:
                return None
            return result[0]
        if is_deployable_resource(resource):
            LOG.warning('Unexpected resource type %s when resolving references of resource %s: %s' %
                        (resource_type, resource_id, resource))
    except Exception as e:
        check_not_found_exception(e, resource_type, resource, resource_status)
    return None
def check_not_found_exception(e, resource_type, resource, resource_status):
    
    markers = ['NoSuchBucket', 'ResourceNotFound', '404']
    if not list(filter(lambda marker, e=e: marker in str(e), markers)):
        LOG.warning('Unexpected error retrieving details for resource %s: %s %s - %s %s' %
            (resource_type, e, traceback.format_exc(), resource, resource_status))
def extract_resource_attribute(resource_type, resource, attribute):