Snowflake - Build and Architect Data Pipelines Using AWS - Lab – Set Up Managed Airflow Cluster on AWS

The video tutorial guides users through setting up a managed Apache Airflow environment on AWS. It covers creating an S3 bucket, configuring the Airflow version, setting up networking with VPC, and finalizing the environment setup. The tutorial emphasizes using version 1.10.12 of Airflow and provides detailed steps for each configuration aspect, including creating a new role and enabling logs. The setup process is expected to take 20 to 40 minutes.

What is the recommended version of Apache Airflow to use in this setup?

• 2.0.0

• 1.10.12

• 2.1.0

• 1.9.0

What should you create in the S3 bucket for Airflow?

• A folder named 'scripts'

• A folder named 'logs'

• A folder named 'daggs'

• A folder named 'data'

Which library is essential for connecting Python scripts to Snowflake from Airflow?

• cryptography

• snowflake-connector-python

• boto3

• pandas

What should you do if your AWS account does not have a VPC?

• Create a new CloudFormation stack

• Create a new S3 bucket

• Create a new IAM role

• Create a new EC2 instance

Which network type should be selected for a non-corporate environment?

• VPN network

• Hybrid network

• Private network

• Public network

What is the maximum number of worker nodes that can be set without incurring unnecessary costs?

• 10

• 20

• 5

• 15

Which logs should be enabled to monitor the Airflow environment effectively?

• All logs including web server, scheduler, worker, and DAG processing

• Only scheduler logs

• Only web server logs

• Only DAG processing logs