Amazon
Avaya
Checkpoint
Cisco®
CompTIA
CrowdStrike
EC-Council
EXIN
Fortinet
Google
ISC
ISC2
ITIL®
Juniper
Microsoft
Okta
Palo Alto Networks
Salesforce
All Vendors
  1. Home
  2. Google
  3. CLOUD-DIGITAL-LEADER

Google CLOUD-DIGITAL-LEADER Exam (page: 14)
Google Cloud Digital Leader
Updated on: 25-Dec-2025

Viewing Page 14 of 84
CLOUD-DIGITAL-LEADER PDF 411 Questions

Your company needs to segment Google Cloud resources used by each team from the others. The teams' efforts are changing frequently, and you need to reduce operational risk and maintain cost visibility.
Which approach does Google recommend?

  1. One project per team.
  2. One organization per team.
  3. One project that contains all of each team's resources.
  4. One top-level folder per team.

Answer(s): A


Reference:

https://cloud.google.com/security/infrastructure/design

The Teams need to segmented to have visibility on the resources each team consumes



How do Migrate for Compute Engine and Migrate for Anthos differ?

  1. Unlike Migrate for Anthos, Migrate for Compute Engine assumes that the migration source is VMware vSphere.
  2. Migrate for Compute Engine charges for ingress, but Migrate for Anthos does not.
  3. Migrate for Compute Engine is closed source, and Migrate for Anthos is open source.
  4. Migrate for Anthos migrates to containers, and Migrate for Compute Engine migrates to virtual machines.

Answer(s): D


Reference:

https://cloud.google.com/migrate/anthos
Migrate workloads to Compute Engine with Migrate for Compute Engine. Migrate from Compute Engine to containers with Migrate for Anthos and GKE.
This method makes sense, for instance, in cases where you want to conduct a data-center migration and migrate all workloads into Compute Engine, and only at a second stage selectively modernize suitable workloads to containers.

https://cloud.google.com/migrate/containers/docs/architecture



An IoT platform is providing services to home security systems. They have more than a million customers, each with many home devices. Burglaries or child safety issues are concerns that the clients customers. Therefore, the platform has to respond very quickly in near real time.
What could be a typical data pipeline used to support this platform on Google Cloud?

  1. Cloud Pub/Sub, Cloud Dataflow, Data Studio
  2. Cloud Functions, Cloud Dataproc, Looker
  3. Cloud Pub/Sub, Cloud Dataflow, BigQuery
  4. Cloud Functions, Cloud Dataproc, BigQuery

Answer(s): A

Explanation:

Explanation

=> Cloud Pub/Sub- Cloud Pub/Sub is the best to be the end-point for ingesting large amounts of data. It will grow as required, can stream data to downstream systems, and can also work with intermittently available backends.
=> Cloud Dataflow- supports streaming data and therefore is an appropriate option for processing the data that is ingested.

=> BigQuery- BigQuery also supports streaming data and its possible to do real time ana-lytics on it.

=> DataStudio- DataStudio and Looker are for visualization. They don't have any in-built analysis.

=> Cloud Functions- Cloud Functions is a useful serverless endpoint. However, Pub/Sub is better in this case because it can also retain messages for a set period if it was not possi-ble to deliver it first time.

=>Cloud Dataproc- Cloud Dataproc is used for Hadoop/Spark workloads and won't be a good fit here.



An organization runs their application on a virtual machine, but every time they want to edit specific features, they have to bring the system offline to update the applica-tion.
What would be a more appropriate solution for their app?

  1. GPUs
  2. Containers
  3. Hypervisors
  4. Solid State Disk

Answer(s): B

Explanation:

Because containers can compartmentalize applications which enables parts to be edited in isolation.

Reference link- https://cloud.google.com/learn/what-are-containers



A Multiple projects within your organization have long-term VM usage. Based on current demand, they are able to project into the future and estimate how many VM hours they will use every year. Going in for a committed use contract seems sensible. How can you configure committed use easily across all the projects?

  1. Enable committed use with discount sharing for the projects
  2. Review the usage of resources by each project on a daily basis. Enable committed use for the following day based on that number, so that it gives maximum granularity without wastage.
  3. Take a report of each project's use in the last year. Enable committed use on a per-project basis based on the previous year's numbers.
  4. Share a Google Sheet and request each project team to send in their estimate. Enable committed use accordingly on a per-project basis.

Answer(s): A

Explanation:

Explanation
Enable committed use discounts are applied to the project from which you purchased it. To share the discount across multiple projects linked to your Cloud Billing account, enable committed use discount sharing from the console.
When you enable committed use discount sharing, all of your current active committed use dis-counts in all the projects under the same Cloud Billing account, including those you previously purchased and new ones you purchase in the future are shared across your Cloud Billing account. Your sustained use discounts are also pooled and shared across all projects within your Cloud Billing account.



Viewing Page 14 of 84



Share your comments for Google CLOUD-DIGITAL-LEADER exam with other users:

Ranveer 7/26/2023 7:26:00 PM

Pass this exam 3 days ago. The PDF version and the Xengine App is quite useful.
SOUTH AFRICA


Karthik 10/12/2023 10:51:00 AM

nice question
Anonymous


EDITH NCUBE 7/25/2023 7:28:00 AM

answers are correct
SOUTH AFRICA