refactor(e2e): support fail fast in get_lambda_response (aws-powertools#2912)

Author: heitorlessa

tests/e2e/idempotency/test_idempotency_dynamodb.py

@@ -4,7 +4,7 @@
 import pytest
 
 from tests.e2e.utils import data_fetcher
-from tests.e2e.utils.functions import execute_lambdas_in_parallel
+from tests.e2e.utils.data_fetcher.common import GetLambdaResponseOptions, get_lambda_response_in_parallel
 
 
 @pytest.fixture
@@ -73,14 +73,21 @@ def test_ttl_caching_expiration_idempotency(ttl_cache_expiration_handler_fn_arn:
 @pytest.mark.xdist_group(name="idempotency")
 def test_ttl_caching_timeout_idempotency(ttl_cache_timeout_handler_fn_arn: str):
     # GIVEN
-    payload_timeout_execution = json.dumps({"sleep": 5, "message": "Powertools for AWS Lambda (Python) - TTL 1s"})
-    payload_working_execution = json.dumps({"sleep": 0, "message": "Powertools for AWS Lambda (Python) - TTL 1s"})
+    payload_timeout_execution = json.dumps(
+        {"sleep": 5, "message": "Powertools for AWS Lambda (Python) - TTL 1s"},
+        sort_keys=True,
+    )
+    payload_working_execution = json.dumps(
+        {"sleep": 0, "message": "Powertools for AWS Lambda (Python) - TTL 1s"},
+        sort_keys=True,
+    )
 
     # WHEN
     # first call should fail due to timeout
     execution_with_timeout, _ = data_fetcher.get_lambda_response(
         lambda_arn=ttl_cache_timeout_handler_fn_arn,
         payload=payload_timeout_execution,
+        raise_on_error=False,
     )
     execution_with_timeout_response = execution_with_timeout["Payload"].read().decode("utf-8")
 
@@ -99,12 +106,15 @@ def test_ttl_caching_timeout_idempotency(ttl_cache_timeout_handler_fn_arn: str):
 @pytest.mark.xdist_group(name="idempotency")
 def test_parallel_execution_idempotency(parallel_execution_handler_fn_arn: str):
     # GIVEN
-    arguments = json.dumps({"message": "Powertools for AWS Lambda (Python) - Parallel execution"})
+    payload = json.dumps({"message": "Powertools for AWS Lambda (Python) - Parallel execution"})
 
-    # WHEN
-    # executing Lambdas in parallel
-    lambdas_arn = [parallel_execution_handler_fn_arn, parallel_execution_handler_fn_arn]
-    execution_result_list = execute_lambdas_in_parallel("data_fetcher.get_lambda_response", lambdas_arn, arguments)
+    invocation_options = [
+        GetLambdaResponseOptions(lambda_arn=parallel_execution_handler_fn_arn, payload=payload, raise_on_error=False),
+        GetLambdaResponseOptions(lambda_arn=parallel_execution_handler_fn_arn, payload=payload, raise_on_error=False),
+    ]
+
+    # WHEN executing Lambdas in parallel
+    execution_result_list = get_lambda_response_in_parallel(invocation_options)
 
     timeout_execution_response = execution_result_list[0][0]["Payload"].read().decode("utf-8")
     error_idempotency_execution_response = execution_result_list[1][0]["Payload"].read().decode("utf-8")

tests/e2e/utils/data_builder/traces.py

@@ -2,7 +2,7 @@
 
 
 def build_trace_default_query(function_name: str) -> str:
-    return f'service("{function_name}")'
+    return f'service(id(name: "{function_name}"))'
 
 
 def build_put_annotations_input(**annotations: str) -> List[Dict]:

tests/e2e/utils/data_fetcher/common.py

@@ -1,24 +1,76 @@
+import functools
+import time
+from concurrent.futures import Future, ThreadPoolExecutor
 from datetime import datetime
-from typing import Optional, Tuple
+from typing import List, Optional, Tuple
 
 import boto3
 import requests
 from mypy_boto3_lambda import LambdaClient
 from mypy_boto3_lambda.type_defs import InvocationResponseTypeDef
+from pydantic import BaseModel
 from requests import Request, Response
 from requests.exceptions import RequestException
 from retry import retry
 
+GetLambdaResponse = Tuple[InvocationResponseTypeDef, datetime]
+
+
+class GetLambdaResponseOptions(BaseModel):
+    lambda_arn: str
+    payload: Optional[str] = None
+    client: Optional[LambdaClient] = None
+    raise_on_error: bool = True
+
+    # Maintenance: Pydantic v2 deprecated it; we should update in v3
+    class Config:
+        arbitrary_types_allowed = True
+
 
 def get_lambda_response(
     lambda_arn: str,
     payload: Optional[str] = None,
     client: Optional[LambdaClient] = None,
-) -> Tuple[InvocationResponseTypeDef, datetime]:
+    raise_on_error: bool = True,
+) -> GetLambdaResponse:
+    """Invoke function synchronously
+
+    Parameters
+    ----------
+    lambda_arn : str
+        Lambda function ARN to invoke
+    payload : Optional[str], optional
+        JSON payload for Lambda invocation, by default None
+    client : Optional[LambdaClient], optional
+        Boto3 Lambda SDK client, by default None
+    raise_on_error : bool, optional
+        Whether to raise exception upon invocation error, by default True
+
+    Returns
+    -------
+    Tuple[InvocationResponseTypeDef, datetime]
+        Function response and approximate execution time
+
+    Raises
+    ------
+    RuntimeError
+        Function invocation error details
+    """
     client = client or boto3.client("lambda")
     payload = payload or ""
     execution_time = datetime.utcnow()
-    return client.invoke(FunctionName=lambda_arn, InvocationType="RequestResponse", Payload=payload), execution_time
+    response: InvocationResponseTypeDef = client.invoke(
+        FunctionName=lambda_arn,
+        InvocationType="RequestResponse",
+        Payload=payload,
+    )
+
+    has_error = response.get("FunctionError", "") == "Unhandled"
+    if has_error and raise_on_error:
+        error_payload = response["Payload"].read().decode()
+        raise RuntimeError(f"Function failed invocation: {error_payload}")
+
+    return response, execution_time
 
 
 @retry(RequestException, delay=2, jitter=1.5, tries=5)
@@ -27,3 +79,39 @@ def get_http_response(request: Request) -> Response:
     result = session.send(request.prepare())
     result.raise_for_status()
     return result
+
+
+def get_lambda_response_in_parallel(
+    get_lambda_response_options: List[GetLambdaResponseOptions],
+) -> List[GetLambdaResponse]:
+    """Invoke functions in parallel
+
+    Parameters
+    ----------
+    get_lambda_response_options : List[GetLambdaResponseOptions]
+        List of options to call get_lambda_response with
+
+    Returns
+    -------
+    List[GetLambdaResponse]
+        Function responses and approximate execution time
+    """
+    result_list = []
+    with ThreadPoolExecutor() as executor:
+        running_tasks: List[Future] = []
+        for options in get_lambda_response_options:
+            # Sleep 0.5, 1, 1.5, ... seconds between each invocation. This way
+            # we can guarantee that lambdas are executed in parallel, but they are
+            # called in the same "order" as they are passed in, thus guaranteeing that
+            # we can assert on the correct output.
+            time.sleep(0.5 * len(running_tasks))
+
+            get_lambda_response_callback = functools.partial(get_lambda_response, **options.dict())
+            running_tasks.append(
+                executor.submit(get_lambda_response_callback),
+            )
+
+        executor.shutdown(wait=True)
+        result_list.extend(running_task.result() for running_task in running_tasks)
+
+    return result_list