PySpark and AWS: Master Big Data with PySpark and AWS - Testing Invoke

The video tutorial covers managing an S3 bucket, deploying a Lambda function, and uploading files to trigger AWS services like Glue. It emphasizes the importance of monitoring with CloudWatch and analyzing logs. The tutorial also discusses AWS updates and best practices, highlighting the need to avoid errors to minimize costs.

What is the first step before uploading a new file to the S3 bucket?

• Delete the existing file

• Check CloudWatch logs

• Run the Lambda function

• Deploy the Glue job

What should be ensured before uploading a dump file to trigger the Lambda function?

• The S3 bucket is empty

• The CloudWatch logs are cleared

• The Lambda function is deployed

• The Glue job is running

Why is it important to check for errors before running a Glue job?

• To clear CloudWatch logs

• To ensure the S3 bucket is empty

• To deploy the Lambda function

• To avoid unnecessary costs

What is a potential consequence of running a Glue job with errors?

• Increased AWS costs

• Inability to access CloudWatch

• Loss of data in S3

• Failure to deploy Lambda

What recent change was mentioned regarding AWS Glue job outputs?

• The logs are no longer accessible

• The output is now found in AWS Glue jobs output

• The job outputs are now free of charge

• The layout now includes the job name

What should you do if you can't find the expected information in CloudWatch logs?

• Look around for the updated information

• Contact AWS support immediately

• Panic and restart the process

• Delete the existing logs

What is the final step in ensuring the integration between S3, Lambda, and Glue is successful?

• Re-upload the dump file

• Restart the Lambda function

• Verify the CloudWatch log streams

• Check the S3 bucket for errors