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Question 289 - Professional Data Engineer discussion

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You are configuring networking for a Dataflow job. The data pipeline uses custom container images with the libraries that are required for the transformation logic preinstalled. The data pipeline reads the data from Cloud Storage and writes the data to BigQuery. You need to ensure cost-effective and secure communication between the pipeline and Google APIs and services. What should you do?

A.
Leave external IP addresses assigned to worker VMs while enforcing firewall rules.
Answers
A.
Leave external IP addresses assigned to worker VMs while enforcing firewall rules.
B.
Disable external IP addresses and establish a Private Service Connect endpoint IP address.
Answers
B.
Disable external IP addresses and establish a Private Service Connect endpoint IP address.
C.
Disable external IP addresses from worker VMs and enable Private Google Access.
Answers
C.
Disable external IP addresses from worker VMs and enable Private Google Access.
D.
Enable Cloud NAT to provide outbound internet connectivity while enforcing firewall rules.
Answers
D.
Enable Cloud NAT to provide outbound internet connectivity while enforcing firewall rules.
Suggested answer: C

Explanation:

Private Google Access allows VMs without external IP addresses to communicate with Google APIs and services over internal routes. This reduces the cost and increases the security of the data pipeline. Custom container images can be stored in Container Registry, which supports Private Google Access. Dataflow supports Private Google Access for both batch and streaming jobs.Reference:

Private Google Access overview

Using Private Google Access and Cloud NAT

Using custom containers with Dataflow

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asked 18/09/2024
Kingsley Tibs
43 questions
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