Amazon Web Services DOP-C02 Exam With Confidence Using Practice Dumps

The most operationally efficient solution is to use AWS Systems Manager Parameter Store1 to store the AMI ID and reference it in the launch template2. This way, the launch template does not need to be updated every time a new AMI is created by Image Builder. Instead, the Image Builder pipeline can update the Parameter Store value with the newest AMI ID3, and the Auto Scaling group can launch instances using the latest value from Parameter Store.

The other solutions require updating the launch template or creating a new version of it every time a new AMI is created, which adds complexity and overhead. Additionally, using EventBridge rules and Lambda functions or Run Command documents introduces additional dependencies and potential points of failure.

 1: AWS Systems Manager Parameter Store 2: Using AWS Systems Manager parameters instead of AMI IDs in launch templates 3: Update an SSM parameter with Image Builder

 Configure AWS Systems Manager on Each Instance:

AWS Systems Manager provides a unified interface for managing AWS resources. Install the Systems Manager agent on each EC2 instance to enable inventory management and other features.

 Use AWS Systems Manager Inventory:

Systems Manager Inventory collects metadata about your instances and the software installed on them. This data includes information about applications, network configurations, and more.

Enable Systems Manager Inventory on all EC2 instances to gather detailed information about installed applications.

 Use Systems Manager Resource Data Sync to Synchronize and Store Findings in an Amazon S3 Bucket:

Resource Data Sync aggregates inventory data from multiple accounts and regions into a single S3 bucket, making it easier to query and analyze the data.

Configure Resource Data Sync to automatically transfer inventory data to an S3 bucket for centralized storage.

 Create an AWS Lambda Function that Runs When New Objects are Added to the S3 Bucket:

Use an S3 event to trigger a Lambda function whenever new inventory data is added to the S3 bucket.

The Lambda function can parse the inventory data and check for the presence of prohibited applications.

 Configure the Lambda Function to Identify Prohibited Applications:

The Lambda function should be programmed to scan the inventory data for any known prohibited applications and generate alerts or take appropriate actions if such applications are found.

Example Lambda function in Python

import json

import boto3

def lambda_handler(event, context):

s3 = boto3.client('s3')

bucket = event['Records'][0]['s3']['bucket']['name']

key = event['Records'][0]['s3']['object']['key']

response = s3.get_object(Bucket=bucket, Key=key)

inventory_data = json.loads(response['Body'].read().decode('utf-8'))

prohibited_apps = ['app1', 'app2']

for instance in inventory_data['Instances']:

for app in instance['Applications']:

if app['Name'] in prohibited_apps:

# Send notification or take action

print(f"Prohibited application found: {app['Name']} on instance {instance['InstanceId']}")

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

By leveraging AWS Systems Manager Inventory, Resource Data Sync, and Lambda, this solution provides an efficient and automated way to audit EC2 instances for prohibited applications.