Serverless Backend with AWS Lambda & API Gateway · レッスン

CloudWatchによるロギングと監視

Lambda関数に堅牢なロギングを実装し、AWS CloudWatchでパフォーマンスとエラーを監視します。

「CloudWatchによるロギングと監視」はCoddyKit上の無料Serverless Backend with AWS Lambda & API Gatewayレッスンです。これはレッスン3/4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Serverless Backend with AWS Lambda & API Gateway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。 Serverless Backend with AWS Lambda & API Gateway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。

Why Log & Monitor Lambda?

When your Lambda functions run in the cloud, you can't just attach a debugger. This is where logging and monitoring become incredibly important!

They help you understand what your function is doing, debug issues, and ensure it's performing well.

Meet AWS CloudWatch

AWS CloudWatch is the central observability service for AWS. It collects and processes raw data from AWS services (like Lambda) into readable metrics and logs.

CloudWatch Logs: Stores your function's text output.
CloudWatch Metrics: Gathers performance data (invocations, errors, duration).
CloudWatch Alarms: Notifies you when metrics cross defined thresholds.

Lambda Logs Automatically

Good news! AWS Lambda automatically integrates with CloudWatch Logs. Any output your function sends to stdout (standard output) or stderr (standard error) will be captured.

This means simple print() statements in Python, or console.log() in Node.js, will show up in CloudWatch Logs.

Python Logging Module

While print() works, for more robust logging in Python, you should use the built-in logging module. It allows you to:

Set different log levels (DEBUG, INFO, WARNING, ERROR, CRITICAL).
Include timestamps and other metadata automatically.
Format your log messages consistently.

Basic Lambda Logging Demo

Try running this simple Python Lambda function. Notice how both print() and logger.info() messages are captured. In a real Lambda, these would appear in CloudWatch Logs.

import json
import logging

# Configure logging
logger = logging.getLogger()
logger.setLevel(logging.INFO)

def lambda_handler(event, context):
    # Messages from print() go to CloudWatch Logs
    print("Starting Lambda execution!")

    # Messages from the logging module also go to CloudWatch Logs
    logger.info("This is an informational log message.")

    # Log the event received by the Lambda function
    logger.info(f"Received event: {json.dumps(event)}")

    # Simulate some work
    result = "Processing complete."
    logger.info(f"Function result: {result}")

    return {
        'statusCode': 200,
        'body': json.dumps(result)
    }

CloudWatch Log Structure

When Lambda sends logs to CloudWatch, they are organized in a specific way:

Log Group: A container for logs from a specific application or service. For Lambda, it's typically /aws/lambda/YOUR_FUNCTION_NAME.
Log Stream: Within a Log Group, each instance or invocation of your Lambda function creates a new Log Stream to store its logs.

Viewing Your Lambda Logs

You can access your function's logs in the AWS Console:

Navigate to the Lambda service.
Select your function.
Go to the 'Monitor' tab.
Click 'View logs in CloudWatch' to see the Log Group and Streams.

Here you can filter, search, and analyze your log data to debug issues.

Monitoring Lambda Metrics

Beyond logs, CloudWatch automatically collects metrics for your Lambda functions, giving you insights into their performance and health without any extra code.

Key metrics include:

Invocations: Total number of times your function was triggered.
Errors: Count of failed invocations.
Duration: Execution time of your function.
Throttles: When Lambda denied an invocation due to concurrency limits.

Setting Up CloudWatch Alarms

CloudWatch Alarms allow you to set up notifications or actions based on metric thresholds. For example, you can create an alarm that:

Triggers if the 'Errors' metric for your function is greater than 0 for 5 minutes.
Sends a notification via Amazon SNS (Simple Notification Service) to your email or an alerting system.

This is crucial for proactive monitoring!

CloudWatch Capabilities Check

CloudWatch is a powerful tool for serverless operations. Which of the following are capabilities of AWS CloudWatch when monitoring Lambda functions?

Lesson Summary

Great job! You've learned how critical logging and monitoring are for serverless applications, especially with AWS Lambda.

Lambda seamlessly integrates with CloudWatch Logs for capturing output.
The Python logging module provides robust logging.
CloudWatch Metrics give you insights into function performance.
CloudWatch Alarms enable proactive alerts based on these metrics.

These tools are essential for debugging, performance tuning, and maintaining healthy serverless backends.

よくある質問

「CloudWatchによるロギングと監視」レッスンは無料ですか？

はい。「CloudWatchによるロギングと監視」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）、Serverless Backend with AWS Lambda & API Gateway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。 Serverless Backend with AWS Lambda & API Gatewayコースには全4レッスンが含まれています。

「CloudWatchによるロギングと監視」で何を学びますか？

Lambda関数に堅牢なロギングを実装し、AWS CloudWatchでパフォーマンスとエラーを監視します。ブラウザで直接実行するハンズオンコードでServerless Backend with AWS Lambda & API Gateway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。

Serverless Backend with AWS Lambda & API Gateway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Serverless Backend with AWS Lambda & API Gateway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3/4です。

「CloudWatchによるロギングと監視」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Serverless Backend with AWS Lambda & API Gateway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Serverless Backend with AWS Lambda & API Gateway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。

このコースのすべてのレッスン

← Serverless Backend with AWS Lambda & API Gatewayに戻る