1. Sign in to the AWS Management Console.
2. Navigate to the CloudTrail service.
3. Click on "Create trail."
4. Enter a name for your trail.
5. Set "Apply trail to all regions" to Yes if you want to collect logs from all regions.
6. Under "Management events," choose "Read/Write events" to log all or select specific events.
7. In the "Data events" section, you can choose to log data events for S3 or Lambda.
8. For "Storage location," create or select an existing S3 bucket to store your logs.
9. Click "Create."

1. Navigate to the IAM service in the AWS Management Console.
2. Go to "Roles" and click "Create role."
3. Choose "Lambda" as the use case and click "Next: Permissions."
4. Attach the following policies: `AmazonS3ReadOnlyAccess`, `AmazonDynamoDBFullAccess`, and `CloudWatchLogsFullAccess` (or more restrictive policies if you prefer).
5. Review, name the role, and create it.

1. Go to the DynamoDB service in the AWS Management Console.
2. Click "Create table."
3. Enter a table name and primary key details (e.g., "EventID" as the primary key).
4. Configure table settings according to your requirements.
5. Click "Create."

1. Navigate to the Lambda service in the AWS Management Console.
2. Click "Create function."
3. Choose "Author from scratch."
4. Enter a function name.
5. Choose the runtime as Python, Node.js, or any other supported runtime.
6. Under "Permissions," choose "Use an existing role" and select the role created in Step 2.
7. Click "Create function."

In the Lambda function editor, write the code to:
  - Read the CloudTrail log file from the S3 bucket.
  - Parse the log data.
  - Write the relevant data to the DynamoDB table.
 
Here's a Python example to get you started:

‍
import boto3
import json

s3_client = boto3.client('s3')
dynamodb = boto3.resource('dynamodb')

def lambda_handler(event, context):
   # Get the S3 object from the event
   bucket_name = event['Records'][0]['s3']['bucket']['name']
   object_key = event['Records'][0]['s3']['object']['key']
   
   # Get the log file from S3
   log_file = s3_client.get_object(Bucket=bucket_name, Key=object_key)
   log_data = json.loads(log_file['Body'].read())
   
   # Process log data and write to DynamoDB
   table = dynamodb.Table('YourDynamoDBTableName')
   
   for record in log_data['Records']:
       # You can add logic here to filter or modify the records as needed
       table.put_item(Item=record)

   return 'Success'

1. In the Lambda function dashboard, click on "Add trigger."
2. Select "S3" from the trigger configuration services.
3. Choose the S3 bucket where CloudTrail logs are stored.
4. Set the event type to "PUT" or "Object Created (All)."
5. Click "Add."

1. Generate some events that CloudTrail will log (e.g., create an S3 bucket, start an EC2 instance).
2. CloudTrail writes logs to the S3 bucket.
3. The Lambda function triggers upon log file creation.
4. Check the DynamoDB table for the new entries.

1. Monitor the Lambda function executions in the AWS Lambda console.
2. Check the CloudWatch Logs for any error messages.
3. Adjust the Lambda function code and permissions as needed based on the logs.

1. Fine-tune the IAM policies to follow the principle of least privilege.
2. Optimize the Lambda function for performance and cost.
3. Set up alarms and notifications for any operational issues.