PySpark and AWS: Master Big Data with PySpark and AWS - Stopping Instances

The video tutorial emphasizes the importance of stopping replication and RDS instances to avoid unnecessary costs. It provides a step-by-step guide on how to stop these services and highlights the need to manage cloud resources efficiently. The tutorial concludes with a reminder to not leave services running when not in use, as this can lead to unexpected charges.

Why is it recommended to stop the replication instance after its job is done?

• To prevent data loss

• To save on costs as it might start charging after a free period

• To ensure data security

• To improve system performance

What is the purpose of stopping the RDS instance in the process described?

• To create a backup

• To save costs and because it's not needed immediately

• To upgrade the instance

• To delete unnecessary data

What is the main task of the PySpark job mentioned in the video?

• To analyze data in real-time

• To process data from S3 and transfer it to another S3 bucket

• To encrypt data for security

• To backup data to a local server

Why is it unnecessary to create a snapshot when stopping the RDS instance?

• Because the data is already backed up

• Because the instance will be deleted

• Because a snapshot is not needed for the current task

• Because it is too costly

What is the key takeaway regarding service management from the video?

• Create backups frequently to prevent data loss

• Upgrade services regularly to avoid issues

• Stop services when not in use to avoid costs

• Always keep services running for quick access