PySpark and AWS: Master Big Data with PySpark and AWS - Checking Trigger

This video tutorial explains how to integrate AWS Lambda with S3, focusing on setting up triggers and testing the Lambda function. It covers deploying the code, using CloudWatch for monitoring logs, and verifying that file uploads to S3 trigger the Lambda function. The tutorial concludes with a preview of the next video, which will discuss passing file names to a PySpark job.

What is the first step before running a Lambda function?

• Check CloudWatch logs

• Upload a file to S3

• Create a test event

• Deploy the code

What should you specify when creating a test event for a Lambda function?

• The name of the S3 bucket

• The event name

• The CloudWatch log group

• The IAM role

Which service is used to monitor logs for a Lambda function?

• AWS S3

• AWS IAM

• AWS CloudWatch

• AWS EC2

What is the purpose of using CloudWatch with Lambda functions?

• To store files

• To deploy code

• To manage IAM roles

• To monitor execution logs

What happens when a file is uploaded to the S3 bucket linked to a Lambda function?

• The file is moved to another bucket

• The Lambda function is triggered

• The file is renamed

• The file is automatically deleted

Why might changes to a Lambda function not be reflected immediately?

• The S3 bucket is not configured

• The IAM role is incorrect

• The CloudWatch logs are not updated

• The changes were not deployed

What should you do after uploading a file to the S3 bucket to verify the Lambda function?

• Check the S3 bucket size

• Refresh the CloudWatch logs

• Re-deploy the Lambda function

• Create a new test event