CloudWatch Logs & Metrics in AWS Serverless

1. Introduction

AWS CloudWatch is a powerful monitoring service for AWS cloud resources and applications. It provides a way to collect and track metrics, collect log files, and set alarms. This lesson will dive deep into CloudWatch Logs and Metrics, particularly in the context of serverless applications.

2. CloudWatch Logs

CloudWatch Logs allow you to monitor, store, and access log files from Amazon EC2 instances, AWS CloudTrail, and other sources. This feature is essential for debugging and auditing applications.

2.1 Key Concepts

• Log Groups: A group of log streams that share the same retention, monitoring, and access control settings.
• Log Streams: A sequence of log events that share the same source.
• Log Events: The individual log messages that are stored in a log stream.

2.2 Creating Log Groups and Streams

To create a log group and log stream using AWS CLI, you can use the following commands:

# Create a log group
aws logs create-log-group --log-group-name MyLogGroup

# Create a log stream
aws logs create-log-stream --log-group-name MyLogGroup --log-stream-name MyLogStream
        

2.3 Sending Logs to CloudWatch

To send logs from a Lambda function to CloudWatch, ensure you have the appropriate IAM role with the necessary permissions. Here’s an example of logging from a Lambda function:

import json
import logging

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

def lambda_handler(event, context):
    logger.info("Log message: %s", json.dumps(event))
    return {
        'statusCode': 200,
        'body': json.dumps('Hello from Lambda!')
    }
        

3. CloudWatch Metrics

CloudWatch Metrics provide real-time monitoring and automate the collection of metrics for your AWS resources. This includes utilization, latency, error rates, and more.

3.1 Defining Custom Metrics

You can publish custom metrics to CloudWatch. Here’s an example using AWS SDK for Python (Boto3):

import boto3

cloudwatch = boto3.client('cloudwatch')

def publish_custom_metric():
    cloudwatch.put_metric_data(
        Namespace='MyApp',
        MetricData=[
            {
                'MetricName': 'SuccessfulRequests',
                'Value': 1,
                'Unit': 'Count'
            },
        ]
    )
        

3.2 Viewing Metrics

You can view metrics through the AWS Management Console or by using the CLI command:

aws cloudwatch list-metrics --namespace MyApp
        

4. Best Practices

• Use structured logging for better searchability.
• Limit log retention to save costs.
• Utilize CloudWatch Alarms to proactively monitor metrics.
• Regularly review logs and metrics for performance optimization.
• Integrate with AWS Lambda to automate log processing.

5. FAQ

6. Conclusion

Mastering CloudWatch Logs and Metrics is essential for effective observability in AWS serverless applications. By leveraging these tools, you can enhance your application's performance and reliability.