Lambda の非同期呼び出し
Lambda 関数で非同期パターンを実装し、リトライ、デッドレターキュー、同時実行数を制御します。
「Lambda の非同期呼び出し」はCoddyKit上の無料AWS for Backend Developers (EC2, S3, RDS, Lambda)レッスンです。 これはレッスン1/4です。 下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。 これはAWS for Backend Developers (EC2, S3, RDS, Lambda)学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 AWS for Backend Developers (EC2, S3, RDS, Lambda)コースには全4レッスンが含まれています。
このレッスンの一部はまだ翻訳されておらず、英語で表示されています。
What is Asynchronous Invocation?
When you invoke an AWS Lambda function asynchronously, you don't wait for the function's response. It's a "fire and forget" model.
- The caller sends the event and doesn't wait for the result.
- Lambda handles the queuing and execution in the background.
- This pattern is perfect for event-driven architectures where immediate feedback isn't required.
How Asynchronous Invocation Works
Here's the typical flow for an asynchronous Lambda invocation:
- An event source (like S3, SNS, or a direct invocation) sends an event.
- Lambda places this event into an internal queue.
- Lambda then invokes your function from this queue.
- The event source receives an immediate success response, even if the function hasn't started processing yet.
Automatic Retries on Failure
One of the key benefits of asynchronous invocation is built-in fault tolerance. If your function encounters an unhandled error or times out during processing:
- Lambda automatically retries the invocation.
- By default, it attempts up to two more retries (total of three attempts).
- These retries occur with exponential backoff, meaning increasing delays between attempts.
Customizing Retry Settings
You have control over how Lambda handles failures for asynchronous invocations:
- You can configure the number of retry attempts (from 0 to 2).
- You can also set a Maximum Event Age, which is the longest time Lambda retains an event in its internal queue for processing.
- These settings can be adjusted in the Lambda console or through Infrastructure as Code (e.g., AWS SAM, CloudFormation).
Catching Failed Events with DLQs
What if your function fails after all retry attempts? By default, the event is dropped. This can lead to data loss.
A Dead-Letter Queue (DLQ) is a powerful feature that captures events that couldn't be processed successfully after all retries. It allows you to:
- Inspect and debug the failed events.
- Reprocess them later once the issue is resolved.
- Prevent critical data from being lost.
Configuring a Dead-Letter Queue
You can configure an Amazon SQS queue or an Amazon SNS topic as your Lambda function's DLQ:
- SQS Queue: Ideal for storing individual failed events for later batch processing or manual inspection.
- SNS Topic: Useful for sending notifications about failed events to multiple subscribers (e.g., email, other Lambda functions).
You specify the ARN (Amazon Resource Name) of your chosen DLQ resource in your Lambda function's configuration.
Managing Concurrent Executions
Concurrency refers to the number of requests your Lambda function is processing at any given time. Lambda automatically scales up to handle incoming events.
However, uncontrolled scaling can sometimes be problematic:
- Overloading downstream services (e.g., databases, APIs).
- Incurring unexpected costs.
AWS provides tools to manage concurrency: Reserved Concurrency and Provisioned Concurrency.
Limiting Function Execution: Reserved Concurrency
Reserved concurrency allows you to set a maximum number of concurrent executions for a specific Lambda function.
- It guarantees that your function always has that amount of capacity available.
- It prevents a single function from consuming all the available concurrency in your AWS account.
- If invocations exceed the reserved limit, they are throttled (rejected).
Keeping Functions Warm: Provisioned Concurrency
Provisioned concurrency pre-initializes a specified number of execution environments for your function.
- This significantly reduces cold starts, which are delays that occur when Lambda needs to set up a new execution environment.
- It's ideal for latency-sensitive applications like APIs where consistent, low-latency responses are crucial.
- You pay for provisioned concurrency even when the function isn't actively invoked.
Async Function with DLQ Example
Here's a simple Python Lambda function that simulates a failure based on event data. If configured with a DLQ, failed events would be sent there.
The if __name__ == "__main__": block demonstrates how to test it locally.
import json
def lambda_handler(event, context):
print(f"Received event: {json.dumps(event)}")
# Simulate a processing error based on event data
if event.get('fail_me', False):
print("Simulating a failure!")
raise Exception("Simulated processing error for event")
# If processing is successful
response_message = "Event processed successfully!"
print(response_message)
return {
'statusCode': 200,
'body': json.dumps(response_message)
}
# Example invocation for local testing/runnable context
if __name__ == "__main__":
# Simulate an event that should succeed
success_event = {"message": "Hello CoddyKit!"}
print("\n--- Running with success event ---")
lambda_handler(success_event, None)
# Simulate an event that should fail
failure_event = {"message": "Trigger failure", "fail_me": True}
print("\n--- Running with failure event ---")
try:
lambda_handler(failure_event, None)
except Exception as e:
print(f"Caught expected error: {e}")Async Invocation Check
Consider an asynchronous Lambda function configured with a Dead-Letter Queue (DLQ). If the function fails on its initial invocation and then again on its first retry, what is the default behavior?
Async Lambda Recap
We explored asynchronous Lambda invocation, a "fire and forget" model ideal for event-driven architectures.
- Learned about default retry behavior and how to customize it.
- Understood Dead-Letter Queues (DLQs) for capturing and managing failed events, preventing data loss.
- Finally, we covered concurrency controls: Reserved Concurrency to limit max executions and Provisioned Concurrency to reduce cold starts.
よくある質問
「Lambda の非同期呼び出し」レッスンは無料ですか？
はい。「Lambda の非同期呼び出し」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し（組み込みコードエディタと24時間対応のAIチューター）、AWS for Backend Developers (EC2, S3, RDS, Lambda)コースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 AWS for Backend Developers (EC2, S3, RDS, Lambda)コースには全4レッスンが含まれています。
「Lambda の非同期呼び出し」で何を学びますか？
Lambda 関数で非同期パターンを実装し、リトライ、デッドレターキュー、同時実行数を制御します。 ブラウザで直接実行するハンズオンコードでAWS for Backend Developers (EC2, S3, RDS, Lambda)を演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。
AWS for Backend Developers (EC2, S3, RDS, Lambda)を始めるのに経験は必要ですか？
事前経験は必要ありません。CoddyKitのAWS for Backend Developers (EC2, S3, RDS, Lambda)は初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。 これはレッスン1/4です。
「Lambda の非同期呼び出し」レッスンにはどのくらい時間がかかりますか？
ほとんどのCoddyKitレッスンは約5～10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。
このAWS for Backend Developers (EC2, S3, RDS, Lambda)レッスンでコードを書いて実行できますか？
はい。すべてのAWS for Backend Developers (EC2, S3, RDS, Lambda)レッスンに組み込みコードエディタが含まれているため、ブラウザでリアルコードを書いて実行し、即座のAIフィードバックを取得できます。ローカル設定は不要です。