可以使用AWS CloudWatch中的事件规则和Lambda函数结合起来实现此需求。

首先，创建一个事件规则，该规则将在每天指定的时间触发Lambda函数。在本例中，我们将每天早上8点运行函数。

import boto3
import os
import sys
from datetime import datetime, timedelta

REGION_NAME = os.environ['AWS_REGION']
EVENT_BUS_NAME = 'default'
RULE_NAME = 'lambda-rule'
LAMBDA_FUNCTION_NAME = 'my-lambda-function'
CRON_EXPRESSION = 'cron(0 8 * * ? *)'

def create_event_rule():
    print(f"Creating event rule {RULE_NAME}...")
    try:
        client = boto3.client('events', region_name=REGION_NAME)
        response = client.put_rule(
            Name=RULE_NAME,
            ScheduleExpression=CRON_EXPRESSION,
            State='ENABLED'
        )
        print(f"Event rule created: {response['RuleArn']}")
        return response['RuleArn']
    except Exception as e:
        print(f"Failed to create event rule {RULE_NAME}: {str(e)}")
        sys.exit(1)

def run_lambda(event, context):
    print('Lambda function is running...')
    # 业务逻辑代码
    print('Lambda function has completed its execution.')

create_event_rule()

接下来，将Lambda函数更新为检查上次执行时间并确定是否超过一天。如果超过一天，就触发警报。

import boto3
import os
import sys
from datetime import datetime, timedelta

REGION_NAME = os.environ['AWS_REGION']
EVENT_BUS_NAME = 'default'
RULE_NAME = 'lambda-rule'
LAMBDA_FUNCTION_NAME = 'my-lambda-function'
CRON_EXPRESSION = 'cron(0 8 * * ? *)'
ALARM_NAME = 'lambda-alarm'
ALARM_DESCRIPTION = 'Lambda function has not been executed for more than one day.'
METRIC_NAMESPACE = 'AWS/Lambda'
METRIC_NAME = 'Invocations'
DIMENSIONS = [
    {
        'Name': 'FunctionName',
        'Value': LAMBDA_FUNCTION_NAME