Google Cloud Digital Leader practice questions

1. Question 1 of 25

   Your organization stores highly sensitive data on-premises that cannot be sent over the public internet. The data must be processed both on-premises and in the cloud. What should your organization do?

   • AConfigure Identity-Aware Proxy (IAP) in your Google Cloud VPC network
   • BCreate a Cloud VPN tunnel between Google Cloud and your data center
   • COrder a Partner Interconnect connection with your network provider
   • DEnable Private Google Access in your Google Cloud VPC network

   Show answer

   Correct answer: C

   How others answered

   • C69%
   • B27%

   Only 69% agreed on this answer — treat it as contested rather than settled.

   Explanation

   Go for B. Always we have to review the statement carefully. It says: "hightly sensitive data". Due to Cloud VPN, which encrypt data is the better option. Partner interconnect: https://cloud.google.com/network-connectivity/docs/how-to/choose-product The connection between your network and Google's network is not encrypted. If you require additional data security, use application-level encryption or your own VPN. Currently, you can't use Cloud VPN with Partner Interconnect, but you can use your own VPN solution.

   Adapted from community discussion by haroldbenites · 2022-06-17 · 18 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

   Supporting references

   • Google Cloud documentation
   • Google Cloud documentation

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   Candidate context

   Question 1 discussion

   These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

   1. H

      haroldbenites

      2022-06-17

      18 upvotes

      Go for B. Always we have to review the statement carefully. It says: "hightly sensitive data". Due to Cloud VPN, which encrypt data is the better option. Partner interconnect: https://cloud.google.com/network-connectivity/docs/how-to/choose-product The connection between your network and Google's network is not encrypted. If you require additional data security, use application-level encryption or your own VPN. Currently, you can't use Cloud VPN with Partner Interconnect, but you can use your own VPN solution.

   2. M

      Mwafrika

      2023-07-19

      Selected C6 upvotes

      Option B (Create a Cloud VPN tunnel) might seem like a plausible choice for connecting on-premises to Google Cloud, but it is essential to note that VPNs usually use the public internet to create encrypted connections, which contradicts the requirement that the data cannot be sent over the public internet. Partner Interconnect, on the other hand, establishes a private connection, making it a more suitable option in this case.

   3. J

      jaxclain

      2022-09-24

      Selected C5 upvotes

      I would also go for C, I know is overkill but after doing the ACE exam I learned that Google exams always have a key point and you have to make your choice depending on the question and not what you think would be better, it says "cannot be sent over the public internet" so Partner Interconnect would be the choice.

   4. C

      cookieMr

      2023-06-10

      Selected C5 upvotes

      Set up a dedicated private network connection between your on-premises infrastructure and Google Cloud Platform (GCP). This can be achieved using Dedicated Interconnect or Partner Interconnect, which provide direct, private, and secure connections between your on-premises data center and GCP's network.

2. Question 2 of 25

   An organization needs to migrate specialized workloads to the cloud while maintaining their existing complex licensing and architecture. What Google Cloud solution should the organization use?

   • ACompute Engine
   • BBare Metal Solution
   • CCloud Run
   • DCloud Functions

   Show answer

   Correct answer: B

   How others answered

   • B80%
   • A20%

   Explanation

   B. There are many workloads that are easy to lift and shift to the cloud, but there are also specialized workloads (such as Oracle) that are difficult to migrate to a cloud environment due to complicated licensing, hardware, and support requirements. Bare Metal Solution provides a path to modernize these applications.

   Adapted from community discussion by joesatriani · 2023-12-06 · 12 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

   Supporting references

   • Google Cloud documentation
   • Google Cloud documentation

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   Question 2 discussion

   These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

   1. J

      joesatriani

      2023-12-06

      12 upvotes

      B. There are many workloads that are easy to lift and shift to the cloud, but there are also specialized workloads (such as Oracle) that are difficult to migrate to a cloud environment due to complicated licensing, hardware, and support requirements. Bare Metal Solution provides a path to modernize these applications.

   2. E

      Ej24356

      2023-09-04

      Selected B6 upvotes

      “This solution provides a path to modernize your application infrastructure landscape, while maintaining your existing investments and architecture. With Bare Metal Solution, you can bring your specialized workloads to Google Cloud, allowing you access and integration with GCP services with minimal latency.”

   3. B

      BryRob

      2023-11-06

      Selected B2 upvotes

      https://cloud.google.com/blog/products/compute/bare-metal-solution-enabling-specialized-workloads-in-google-cloud https://cloud.google.com/bare-metal/docs/bms-setup

   4. _

      __rajan__

      2024-10-22

      Selected B1 upvote

      The best Google Cloud solution for migrating specialized workloads to the cloud while maintaining their existing complex licensing and architecture is Bare Metal Solution.

3. Question 3 of 25

   Your company's development team is building an application that will be deployed on Cloud Run. You are designing a CI/CD pipeline so that any new version of the application can be deployed in the fewest number of steps possible using the CI/CD pipeline you are designing. You need to select a storage location for the images of the application after the CI part of your pipeline has built them. What should you do?

   • ACreate a Compute Engine image containing the application
   • BStore the images in Container Registry
   • CStore the images in Cloud Storage
   • DCreate a Compute Engine disk containing the application

   Show answer

   Correct answer: B

   How others answered

   • B83%
   • C17%

   Explanation

   B is correct but currently Google is promoting Artifact Registry over Container Registry. You may get that in the main exam MCQ.

   Adapted from community discussion by __rajan__ · 2024-04-11 · 6 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

   Supporting references

   • Google Cloud documentation
   • Google Cloud documentation

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   Question 3 discussion

   These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

   1. _

      __rajan__

      2024-04-11

      Selected B6 upvotes

      B is correct but currently Google is promoting Artifact Registry over Container Registry. You may get that in the main exam MCQ.

   2. C

      cookieMr

      2023-12-10

      Selected B4 upvotes

      Select Google Container Registry (GCR) as the storage location for your application images. GCR allows you to securely store and manage container images in a private registry. It is tightly integrated with other Google Cloud services, including Cloud Run, making it a convenient choice.

   3. S

      sivakarthick16

      2024-07-17

      Selected B3 upvotes

      Container Registry is a managed Docker container image storage service provided by Google Cloud. It is specifically designed for storing and managing container images, making it the ideal choice for storing the application images in your CI/CD pipeline. By using Container Registry, you can easily manage and deploy the application images to Cloud Run in the most efficient and streamlined manner.

   4. K

      kummimhk

      2022-12-08

      Selected B3 upvotes

      CloudRun is used for development, deployment of containerized applications. it's wise to choose container registry to store images.

4. Question 4 of 25

   Your organization uses Active Directory to authenticate users. Users' Google account access must be removed when their Active Directory account is terminated. How should your organization meet this requirement?

   • AConfigure two-factor authentication in the Google domain
   • BRemove the Google account from all IAM policies
   • CConfigure BeyondCorp and Identity-Aware Proxy in the Google domain
   • DConfigure single sign-on in the Google domain

   Show answer

   Correct answer: D

   How others answered

   • D94%

   Explanation

   Per Google Docs article, Federating Google Cloud with Active Directory. "This article describes how you can configure Cloud Identity or Google Workspace to use Active Directory as IdP and authoritative source. The article compares the logical structure of Active Directory with the structure used by Cloud Identity and Google Workspace and describes how you can map Active Directory forests, domains, users, and groups. The article also provides a flowchart that helps you determine the best mapping approach for your scenario." https://cloud.google.com/architecture/identity/federating-gcp-with-active-directory-introduction

   Adapted from community discussion by ucsdmiami2020 · 2022-12-05 · 6 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

   Supporting references

   • Google Cloud documentation
   • Google Cloud documentation

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   Question 4 discussion

   These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

   1. J

      JCE

      2022-01-07

      10 upvotes

      D seems correct https://cloud.google.com/architecture/identity/federating-gcp-with-active-directory-configuring-single-sign-on

   2. C

      cookieMr

      2023-06-10

      Selected D8 upvotes

      SSO allows for centralized user management, where user accounts and access permissions are managed in a single identity provider (such as Active Directory). When a user's Active Directory account is terminated, SSO provides a centralized point to revoke access across multiple applications and services, including Google accounts.

   3. U

      ucsdmiami2020

      2022-12-05

      Selected D6 upvotes

      Per Google Docs article, Federating Google Cloud with Active Directory. "This article describes how you can configure Cloud Identity or Google Workspace to use Active Directory as IdP and authoritative source. The article compares the logical structure of Active Directory with the structure used by Cloud Identity and Google Workspace and describes how you can map Active Directory forests, domains, users, and groups. The article also provides a flowchart that helps you determine the best mapping approach for your scenario." https://cloud.google.com/architecture/identity/federating-gcp-with-active-directory-introduction

   4. M

      Monicaarg

      2022-05-15

      Selected D4 upvotes

      Your organization uses Active Directory to authenticate users. Then you need to use Single sign-on (SSO) is an authentication scheme that allows a user to log in with a single ID and password to different systems and software. SSO allows IT departments to administrator a single identity that can access many machines and cloud services.

5. Question 5 of 25

   An organization needs a platform to create custom end-to-end artificial intelligence models. Which Google Cloud product or service should the organization use?

   • ADataproc
   • BCompute Engine
   • CRecommendations AI
   • DVertex AI

   Show answer

   Correct answer: D

   How others answered

   • D100%

   Explanation

   Recommendations AI enables you to build an end-to-end personalized recommendation system based on state-of-the-art deep learning ML models, without a need for expertise in ML or recommendation systems. With Vertex AI, both AutoML training and custom training are available options. Whichever option you choose for training, you can save models, deploy models, and request predictions with Vertex AI.

   Adapted from community discussion by Ej24356 · 2023-09-05 · 8 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

   Supporting references

   • Google Cloud documentation
   • Google Cloud documentation

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   Candidate context

   Question 5 discussion

   These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

   1. E

      Ej24356

      2023-09-05

      Selected D8 upvotes

      Recommendations AI enables you to build an end-to-end personalized recommendation system based on state-of-the-art deep learning ML models, without a need for expertise in ML or recommendation systems. With Vertex AI, both AutoML training and custom training are available options. Whichever option you choose for training, you can save models, deploy models, and request predictions with Vertex AI.

   2. U

      ucsdmiami2020

      2023-12-19

      Selected D2 upvotes

      Per Google docs, Recommendations AI "enables you to build an end-to-end personalized recommendation system based on state-of-the-art deep learning ML models, without a need for expertise in ML or recommendation systems." https://cloud.google.com/recommendations-ai/docs

   3. A

      Akshay0403

      2023-11-16

      Selected D2 upvotes

      Vertex AI Workbench is the single environment for data scientists to complete all of their ML work, from experimentation, to deployment, to managing and monitoring models

   4. C

      CoffeeCloud

      2024-11-21

      Selected D2 upvotes

      What is going on here? C isn't the best option as it reduces the level of customization it offers

6. Question 6 of 25

   What is out-of-the-box observability within the context of cloud operations?

   • AMonitoring project development timelines
   • BMonitoring IT infrastructure and applications
   • CMonitoring customer satisfaction and feedback
   • DMonitoring cloud subscription costs

   Show answer

   Correct answer: B

   How others answered

   • B88%

   Explanation

   Out-of-the-box observability within the context of cloud operations means having preconfigured monitoring and analysis tools that provide visibility into various aspects of an organization's IT infrastructure and applications without requiring extensive configuration or customization. This includes monitoring metrics such as system performance, availability, and error rates, as well as logs, traces, and other data that can be used to diagnose and troubleshoot issues. The goal is to provide quick and easy access to relevant information that can help IT teams understand the health and performance of their systems and applications.

   Adapted from community discussion by SoftSami · 2023-03-15 · 5 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

   Supporting references

   • Google Cloud documentation
   • Google Cloud documentation

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   Question 6 discussion

   These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

   1. S

      SoftSami

      2023-03-15

      Selected B5 upvotes

      Out-of-the-box observability within the context of cloud operations means having preconfigured monitoring and analysis tools that provide visibility into various aspects of an organization's IT infrastructure and applications without requiring extensive configuration or customization. This includes monitoring metrics such as system performance, availability, and error rates, as well as logs, traces, and other data that can be used to diagnose and troubleshoot issues. The goal is to provide quick and easy access to relevant information that can help IT teams understand the health and performance of their systems and applications.

   2. G

      gviolant

      2023-02-19

      Selected B4 upvotes

      What is observability in Cloud? In IT and cloud computing, observability also refers to software tools and practices for aggregating, correlating and analyzing a steady stream of performance data from a distributed application along with the hardware and network it runs on, in order to more effectively monitor, troubleshoot and debug the application

   3. E

      Emma412

      2023-08-25

      Selected B2 upvotes

      Answer = B Explanation: Refer the documentation https://cloud.google.com/products/operations?hl=en (goto first use-case) "Cloud Logging and Cloud Monitoring provide your IT Ops/SRE/DevOps teams with out-of-the box observability needed to monitor your infrastructure and applications."

   4. A

      adz07

      2023-03-11

      Selected B1 upvote

      It seems B. based on this https://cloud.google.com/blog/products/management-tools/cloud-operations-suite-gets-21-new-features

7. Question 7 of 25

   An international law firm needs their HR application to be able to share and access varying amounts of sensitive data across their branch offices. Why would using Cloud Storage be beneficial for them?

   • AIt stores geographically dispersed copies of data to prevent loss.
   • BIt offers an affordable upgrade that enables data encryption.
   • CIt randomly allocates data to different storage locations to protect against threats.
   • DIt has a low minimum storage amount requirement.

   Show answer

   Correct answer: A

   How others answered

   • A63%
   • B28%

   Only 63% agreed on this answer — treat it as contested rather than settled.

   Explanation

   By default - Cloud Storage encrypts data at no additional cost (Cloud Storage always encrypts your data on the server side, before it is written to disk, at no additional charge. - https://cloud.google.com/storage/docs/encryption/). This sorts out the sensitive data requirement of the HR company. Data Loss is minimised by having geographically dispersed copies. Answer B is possible but not required unless the customer wants key storage (HSM units) to secure/manage their cryptographic keys for an additional fee....

   Adapted from community discussion by NoCrapEva · 2023-08-29 · 4 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

   Supporting references

   • Google Cloud documentation
   • Google Cloud documentation

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   Candidate context

   Question 7 discussion

   These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

   1. M

      ManishSinha

      2023-03-20

      7 upvotes

      I think A is better option.One of the primary benefits of using Google Cloud Storage is that it stores geographically dispersed copies of data to prevent data loss. This means that even if one copy of the data is lost or corrupted, other copies stored in different locations can be used to recover the data.

   2. N

      NoCrapEva

      2023-08-29

      Selected A4 upvotes

      By default - Cloud Storage encrypts data at no additional cost (Cloud Storage always encrypts your data on the server side, before it is written to disk, at no additional charge. - https://cloud.google.com/storage/docs/encryption/). This sorts out the sensitive data requirement of the HR company. Data Loss is minimised by having geographically dispersed copies. Answer B is possible but not required unless the customer wants key storage (HSM units) to secure/manage their cryptographic keys for an additional fee....

   3. J

      joshnort

      2025-01-02

      Selected A1 upvote

      A: It stores geographically dispersed copies of data to prevent loss. Cloud Storage is ideal for an international law firm needing to share and access sensitive data securely across branch offices. Its benefits include: - Geographic redundancy: Cloud Storage automatically replicates data across multiple locations, ensuring high availability and preventing data loss due to localized failures. - Data security: It includes built-in encryption for sensitive data, both at rest and in transit. - Scalability: It allows the firm to handle varying amounts of data without worrying about storage limits. B: is wrong. Data encryption is built-in with Cloud Storage, and there’s no need for an "affordable upgrade."

   4. _

      __rajan__

      2023-10-23

      Selected A2 upvotes

      A. It stores geographically dispersed copies of data to prevent loss. One of the key benefits of Cloud Storage is that it stores geographically dispersed copies of data to prevent loss. This is important for an international law firm that needs to be able to share and access varying amounts of sensitive data across their branch offices.

8. Question 8 of 25

   An organization with a commissions-based business model is struggling to predict cloud costs due to fluctuating revenue. How can the organization optimize the use of their cloud resources?

   • ABy applying intelligent recommendations
   • BBy decentralizing financial decision making
   • CBy sharing project ownership across all teams
   • DBy increasing their capital expenditure

   Show answer

   Correct answer: A

   How others answered

   • A80%
   • B20%

   Explanation

   The organization can optimize the use of their cloud resources by applying intelligent recommendations. This means using tools and services that can analyze their cloud usage and identify areas where they can save money. For example, they could use a tool that can automatically shut down unused resources or that can move workloads to cheaper regions. Decentralizing financial decision making, sharing project ownership across all teams, and increasing their capital expenditure would not necessarily help the organization optimize the use of their cloud resources. In fact, these options could make it more difficult to track and manage cloud costs.

   Adapted from community discussion by yizza · 2023-03-29 · 4 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

   Supporting references

   • Google Cloud documentation
   • Google Cloud documentation

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   Candidate context

   Question 8 discussion

   These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

   1. Y

      yizza

      2023-03-29

      Selected A4 upvotes

      The organization can optimize the use of their cloud resources by applying intelligent recommendations. This means using tools and services that can analyze their cloud usage and identify areas where they can save money. For example, they could use a tool that can automatically shut down unused resources or that can move workloads to cheaper regions. Decentralizing financial decision making, sharing project ownership across all teams, and increasing their capital expenditure would not necessarily help the organization optimize the use of their cloud resources. In fact, these options could make it more difficult to track and manage cloud costs.

   2. J

      joshnort

      2025-01-04

      Selected A1 upvote

      A. By applying intelligent recommendations. Organizations with fluctuating revenue can optimize their cloud costs by using intelligent recommendations provided by cloud services. These recommendations, such as those from Google Cloud's Recommender, analyze usage patterns and suggest ways to: - Right-size resources: Adjust compute, storage, or other resources to match actual usage. - Remove idle resources: Identify and shut down unused or underutilized resources. - Optimize spending: Leverage savings plans, committed use discounts, or preemptible VMs for predictable workloads. - Schedule workloads: Automate resource allocation during peak and off-peak times to avoid unnecessary expenses. These proactive strategies help align cloud resource usage with revenue fluctuations, minimizing waste and optimizing costs.

   3. _

      __rajan__

      2023-10-23

      Selected A3 upvotes

      A. By applying intelligent recommendations Intelligent recommendations can help organizations to optimize the use of their cloud resources by identifying and suggesting ways to reduce costs.

   4. E

      Emma412

      2023-08-25

      Selected A2 upvotes

      Answer = A Explanation: Refer the section "recommendations" under cost management "View intelligent recommendations for optimizing your costs and usage. Easily apply these changes for immediate cost savings and greater efficiency." https://cloud.google.com/cost-management

9. Question 9 of 25

   Your organization needs a large amount of extra computing power within the next two weeks. After those two weeks, the need for the additional resources will end. Which is the most cost-effective approach?

   • AUse a committed use discount to reserve a very powerful virtual machine
   • BPurchase one very powerful physical computer
   • CStart a very powerful virtual machine without using a committed use discount
   • DPurchase multiple physical computers and scale workload across them

   Show answer

   Correct answer: C

   How others answered

   • C100%

   Explanation

   C is correct because we don’t know the compute use for 2 weeks and discount is available on 1-3 years not for 2 weeks. https://cloud.google.com/compute/docs/instances/signing-up-committed-use-discounts

   Adapted from community discussion by Syd · 2022-01-02 · 33 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

   Supporting references

   • Google Cloud documentation
   • Google Cloud documentation

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   Question 9 discussion

   These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

   1. S

      Syd

      2022-01-02

      33 upvotes

      C is correct because we don’t know the compute use for 2 weeks and discount is available on 1-3 years not for 2 weeks. https://cloud.google.com/compute/docs/instances/signing-up-committed-use-discounts

   2. U

      ucsdmiami2020

      2022-12-04

      5 upvotes

      Agreed C. "When you purchase a committed use contract, you purchase Compute Engine resources—such as vCPUs, memory, GPUs, local SSDs, and sole-tenant nodes—at a discounted price in return for committing to paying for those resources for 1 year or 3 years."

   3. K

      kummimhk

      2022-06-08

      Selected C4 upvotes

      A - ruled out due to short duration of requirement about 2 weeks. B - not recommended C- Recommended D - Not recommended as there's no definite compute that's given in this option.

   4. N

      NU_1234

      2022-03-31

      Selected C3 upvotes

      Key words -> use of high computing power is only for 2 weeks. Committed use discounts are provided for long term use and not for just 2 weeks

10. Question 10 of 25

    Your organization needs to establish private network connectivity between its on-premises network and its workloads running in Google Cloud. You need to be able to set up the connection as soon as possible. Which Google Cloud product or feature should you use?

    • ACloud Interconnect
    • BDirect Peering
    • CCloud VPN
    • DCloud CDN

    Show answer

    Correct answer: C

    How others answered

    • C90%

    Explanation

    Cloud VPN setup can be done instantly and though it travels over internet, it is private in nature. Cloud interconnect needs physically dedicated connection.

    Adapted from community discussion by anirban7172 · 2023-01-19 · 42 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

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    Question 10 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. A

       anirban7172

       2023-01-19

       Selected C42 upvotes

       Cloud VPN setup can be done instantly and though it travels over internet, it is private in nature. Cloud interconnect needs physically dedicated connection.

    2. C

       cookieMr

       2024-06-10

       Selected C4 upvotes

       To establish private network connectivity between your on-premises network and workloads running in Google Cloud, you should use Google Cloud VPN (Virtual Private Network). Google Cloud VPN allows you to securely connect your on-premises network to your virtual private cloud (VPC) network in Google Cloud. It enables encrypted communication over the public internet, providing a secure and private connection between your on-premises environment and your cloud resources.

    3. P

       pspandher

       2023-09-29

       3 upvotes

       I will go with Cloud VPN, as per Google the Cloud VPN can be established using a private and public IP both , Now here the main point or thing to focus is Bandwidth requirement if it is Private and your connection is in Google POP then we use Dedicated Interconnect or Partner Interconnect. Else for Public IP we use Direct peering Or carrier peering. https://cloud.google.com/blog/products/networking/google-cloud-network-connectivity-options-explained I hope this answer everybody questions (refer to diagram)

    4. K

       kummimhk

       2023-06-08

       3 upvotes

       Cloud VPN is incorrect because data travels over internet thought encrypted. But, in the question it is mentioned as Private network connectivity hence A.Interconnect is correct. Hey, wait but in the question its mentioned as able to setup connection as soon as possible - how much time it takes to setup Cloud Interconnect.I am clueless as i couldn't find it in documenation.

11. Question 11 of 25

    Your organization is developing a mobile app and wants to select a fully featured cloud-based compute platform for it. Which Google Cloud product or feature should your organization use?

    • AGoogle Kubernetes Engine
    • BFirebase
    • CCloud Functions
    • DApp Engine

    Show answer

    Correct answer: B

    How others answered

    • B77%
    • D23%

    Explanation

    this doesnt mean you choose correct answer, because exam wont show you where you made misstakes after passing and you dont even know how many misstakes you made, iam still leaning to B for Firebase because only diffrence between app engine and firebase is that Firebase is recommended for mobile app development

    Adapted from community discussion by [Removed] · 2022-04-06 · 23 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

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    Candidate context

    Question 11 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. [

       [Removed]

       2022-04-06

       23 upvotes

       this doesnt mean you choose correct answer, because exam wont show you where you made misstakes after passing and you dont even know how many misstakes you made, iam still leaning to B for Firebase because only diffrence between app engine and firebase is that Firebase is recommended for mobile app development

    2. M

       mdmahanti

       2022-08-28

       15 upvotes

       But that doesnt mean that App Engine is correct. Unless you scores 100%

    3. S

       szefco

       2022-07-28

       7 upvotes

       Although it is possible to build an app in App Engine, Firebase is dedicated suite for mobile apps. B is correct

    4. R

       RobertPL

       2023-09-26

       Selected B4 upvotes

       It's a tricky question, because it refers to compute engine, and according to Google cheatsheet, Compute services do not include Firebase, but App Engine is included. However, one must notice, that Firebase is part of a completely separate ecosystem of services, dedicated to mobile apps, which also includes specialized compute services. So, the correct answer is B. See https://googlecloudcheatsheet.withgoogle.com/

12. Question 12 of 25

    Your organization wants to migrate its data management solutions to Google Cloud because it needs to dynamically scale up or down and to run transactional SQL queries against historical data at scale. Which Google Cloud product or service should your organization use?

    • ABigQuery
    • BCloud Bigtable
    • CPub/Sub
    • DCloud Spanner

    Show answer

    Correct answer: D

    How others answered

    • D78%
    • A22%

    Explanation

    Google BigQuery does not support transactions and does not allow updating of existing records. On the other hand, Google Cloud Spanner supports OLTP along with scalability and high availability.

    Adapted from community discussion by oncleled · 2022-12-01 · 8 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

    View community discussion4

    Candidate context

    Question 12 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. O

       oncleled

       2022-12-01

       Selected D8 upvotes

       Google BigQuery does not support transactions and does not allow updating of existing records. On the other hand, Google Cloud Spanner supports OLTP along with scalability and high availability.

    2. O

       omgitsele

       2023-04-24

       7 upvotes

       Wrong. BigQuery is OLAP while the question asks you for OLTP. So the answer is D.

    3. C

       cookieMr

       2023-06-10

       Selected D3 upvotes

       Cloud Spanner is a globally distributed, horizontally scalable, and strongly consistent relational database service provided by Google Cloud. Cloud Spanner is well-suited for transactional workloads with strong consistency requirements across multiple regions. If your focus is more on performing transactional SQL queries against historical data, ensuring strong consistency, and managing relational database workloads, Cloud Spanner would be a suitable choice.

    4. _

       __rajan__

       2023-10-16

       Selected D3 upvotes

       Cloud Spanner is a globally distributed, strongly consistent, and horizontally scalable database service on Google Cloud. It's designed for high availability, scalability, and transactional consistency, making it a great choice for applications that require both transactional and analytical capabilities.

13. Question 13 of 25

    Your organization needs to categorize objects in a large group of static images using machine learning. Which Google Cloud product or service should your organization use?

    • ABigQuery ML
    • BAutoML Video Intelligence
    • CCloud Vision API
    • DAutoML Tables

    Show answer

    Correct answer: C

    How others answered

    • C97%

    Explanation

    For categorizing objects in static images using machine learning, your organization can utilize Google Cloud Vision API. Google Cloud Vision API offers pre-trained machine learning models for image analysis and recognition tasks. By leveraging the Google Cloud Vision API, your organization can automate the process of categorizing objects in large sets of static images, reducing the manual effort required for image analysis. The API provides a simple and scalable solution for image recognition tasks, enabling you to extract valuable insights and metadata from your image data.

    Adapted from community discussion by cookieMr · 2024-06-10 · 5 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

    View community discussion4

    Candidate context

    Question 13 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. E

       ergauravtaneja

       2023-08-12

       Selected C7 upvotes

       Vision API can assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog.

    2. C

       cookieMr

       2024-06-10

       Selected C5 upvotes

       For categorizing objects in static images using machine learning, your organization can utilize Google Cloud Vision API. Google Cloud Vision API offers pre-trained machine learning models for image analysis and recognition tasks. By leveraging the Google Cloud Vision API, your organization can automate the process of categorizing objects in large sets of static images, reducing the manual effort required for image analysis. The API provides a simple and scalable solution for image recognition tasks, enabling you to extract valuable insights and metadata from your image data.

    3. J

       Jay1312

       2023-08-19

       4 upvotes

       I agree with those who say that AutoML Tables is the incorrect answer as it is used for structured data. Static images is unstructured data. https://cloud.google.com/automl-tables/docs AutoML Tables enables your entire team to automatically build and deploy state-of-the-art machine learning models on structured data at massively increased speed and scale.

    4. A

       albert_kuo

       2023-04-25

       Selected C3 upvotes

       Vision AI derives insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more.

14. Question 14 of 25

    Your organization runs all its workloads on Compute Engine virtual machine instances. Your organization has a security requirement: the virtual machines are not allowed to access the public internet. The workloads running on those virtual machines need to access BigQuery and Cloud Storage, using their publicly accessible interfaces, without violating the security requirement. Which Google Cloud product or feature should your organization use?

    • AIdentity-Aware Proxy
    • BCloud NAT (network address translation)
    • CVPC internal load balancers
    • DPrivate Google Access

    Show answer

    Correct answer: D

    How others answered

    • D89%

    Explanation

    Agree with fpreli, the answer is D. According to the Google Documents >>> By default, when a Compute Engine VM lacks an external IP address assigned to its network interface, it can only send packets to other internal IP address destinations. You can allow these VMs to connect to the set of external IP addresses used by Google APIs and services by enabling Private Google Access on the subnet used by the VM's network interface. Besides, the security rules say no Internet access while NAt provite internet access. Google Private Access is like AWS VPC endpoint where you access GCP Public services without using Public Internet.

    Adapted from community discussion by A_A_AB · 2022-07-09 · 32 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

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    Candidate context

    Question 14 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. A

       A_A_AB

       2022-07-09

       Selected D32 upvotes

       Agree with fpreli, the answer is D. According to the Google Documents >>> By default, when a Compute Engine VM lacks an external IP address assigned to its network interface, it can only send packets to other internal IP address destinations. You can allow these VMs to connect to the set of external IP addresses used by Google APIs and services by enabling Private Google Access on the subnet used by the VM's network interface. Besides, the security rules say no Internet access while NAt provite internet access. Google Private Access is like AWS VPC endpoint where you access GCP Public services without using Public Internet.

    2. H

       Huntishi

       2023-06-04

       Selected D4 upvotes

       Cloud NAT (Paid service) will work in this scenario however so will Private Google Access (which is free). Private Google Access allows VMs with no external IP address to access publicly available Google APIs and services. Private Google Access -> VM instances that only have internal IP addresses (no external IP addresses) can use Private Google Access. They can reach the external IP addresses of Google APIs and services. Source - https://cloud.google.com/vpc/docs/private-google-access

    3. S

       sivakarthick16

       2024-06-18

       Selected D4 upvotes

       Private Google Access allows virtual machine instances in a VPC network to access Google Cloud services like BigQuery and Cloud Storage using internal IP addresses, without requiring public IP addresses or access to the public internet. By enabling Private Google Access, your organization can ensure that the workloads can securely access these services while adhering to the security requirement of not allowing access to the public internet.

    4. C

       cookieMr

       2023-12-10

       Selected D3 upvotes

       To meet the security requirement of restricting virtual machines from accessing the public internet while allowing access to BigQuery and Cloud Storage, your organization can utilize Private Google Access. Private Google Access allows Compute Engine virtual machine instances to access Google Cloud services like BigQuery and Cloud Storage using internal IP addresses, without requiring public internet connectivity. It enables private communication between your virtual machines and the Google Cloud services within the same Virtual Private Cloud (VPC) network.

15. Question 15 of 25

    Your organization wants to run a container-based application on Google Cloud. This application is expected to increase in complexity. You have a security need for fine-grained control of traffic between the containers. You also have an operational need to exercise fine-grained control over the application's scaling policies. What Google Cloud product or feature should your organization use?

    • AGoogle Kubernetes Engine cluster
    • BApp Engine
    • CCloud Run
    • DCompute Engine virtual machines

    Show answer

    Correct answer: A

    How others answered

    • A97%

    Explanation

    I would say A. GKE seems a better fit since the requirement is for "security need for fine-grained control of traffic between the containers" and "fine-grained control over scaling policies". Such level of control is easier on GKE that Cloud Run.

    Adapted from community discussion by fpreli · 2023-01-04 · 22 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

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    Candidate context

    Question 15 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. F

       fpreli

       2023-01-04

       22 upvotes

       I would say A. GKE seems a better fit since the requirement is for "security need for fine-grained control of traffic between the containers" and "fine-grained control over scaling policies". Such level of control is easier on GKE that Cloud Run.

    2. K

       kimkimkimkimkim

       2023-01-07

       Selected A11 upvotes

       I think the answer should be A because it says that there is a need for "fine-grained control". Check out this brief comparison: https://cloud.google.com/blog/products/containers-kubernetes/when-to-use-google-kubernetes-engine-vs-cloud-run-for-containers

    3. V

       VenRam

       2023-01-29

       2 upvotes

       The Options are a bit misleading. If it states, CloudRun with VPC Service Controls, then, it would have been easier choice to pick C. Please refer to this link (https://cloud.google.com/blog/products/serverless/cloud-run-gets-enterprise-grade-network-security-with-vpc-sc) where it states: VPC Service Controls (VPC SC) give you fine-grained control over how data moves into and out of a VPC SC service perimeter. VPC SC provides an additional layer of security defense for Google Cloud that is independent of Identity and Access Management (IAM). IAM currently enables granular identity based access control; VPC SC enables a security parameter that lets you secure your cloud resources and set up private connectivity to Google Cloud’s APIs and services. This helps protect against risks including: Data exfiltration from malicious insiders or compromised code Accidental public exposure of private data, caused by misconfigured IAM policies Access from unauthorized networks using stolen credentials

    4. C

       cookieMr

       2024-06-10

       Selected A2 upvotes

       Google Kubernetes Engine is a managed Kubernetes service that provides a secure, reliable, and scalable environment for deploying and managing containerized applications. By using Google Kubernetes Engine, your organization can deploy and manage container-based applications with fine-grained control over traffic and scaling policies. GKE offers a secure, scalable, and reliable platform for running your applications, while leveraging the power and flexibility of Kubernetes for container orchestration.

16. Question 16 of 25

    Your organization is developing an application that will manage payments and online bank accounts located around the world. The most critical requirement for your database is that each transaction is handled consistently. Your organization anticipates almost unlimited growth in the amount of data stored. Which Google Cloud product should your organization choose?

    • ACloud SQL
    • BCloud Storage
    • CFirestore
    • DCloud Spanner

    Show answer

    Correct answer: D

    How others answered

    • D90%

    Explanation

    CloudSpanner is the correct answer. Firestore is for mobile applications developed from Firebase, GCS is not a Database and Cloud SQL is to simple for this amout of data.

    Adapted from community discussion by vinibisineli · 2022-01-22 · 30 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation

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    Candidate context

    Question 16 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. V

       vinibisineli

       2022-01-22

       Selected D30 upvotes

       CloudSpanner is the correct answer. Firestore is for mobile applications developed from Firebase, GCS is not a Database and Cloud SQL is to simple for this amout of data.

    2. S

       sivakarthick16

       2024-01-19

       Selected D8 upvotes

       Cloud Spanner is a globally distributed, horizontally scalable, and strongly consistent relational database service offered by Google Cloud. It provides the ability to scale both storage and compute resources as needed, ensuring consistent transaction handling across multiple regions. This makes it an ideal choice for applications that require strong consistency and high scalability. While options A (Cloud SQL), B (Cloud Storage), and C (Firestore) are also valuable Google Cloud products, they may not meet the specific requirements mentioned in the context as effectively as Cloud Spanner. Cloud SQL is a managed relational database service, but it may not provide the same level of scalability and global consistency as Cloud Spanner. Cloud Storage is a scalable object storage solution, and Firestore is a NoSQL document database, but they may not offer the same level of transaction consistency required for managing payments and online bank accounts.

    3. L

       Lufly

       2023-08-22

       Selected D4 upvotes

       The other options are not as suitable for this purpose. Cloud SQL: Cloud SQL is a managed database service that offers a variety of relational database engines, including MySQL, PostgreSQL, and SQL Server. However, Cloud SQL does not offer transactional consistency at global scale. Cloud Storage: Cloud Storage is a object storage service that is designed for storing large amounts of unstructured data. It is not a relational database and does not offer transactional consistency. Firestore: Firestore is a NoSQL document database that is designed for mobile and web applications. It is not a relational database and does not offer transactional consistency.

    4. O

       omgitsele

       2023-04-22

       4 upvotes

       Good answer but Firestore is not only or mobile apps. The reason it is not the correct answer is the limitations analyzed here. Essentially it does not cover the unlimited growth. https://firebase.google.com/docs/firestore/quotas#collections_documents_and_fields

17. Question 17 of 25

    Your company is running the majority of its workloads in a co-located data center. The workloads are running on virtual machines (VMs) on top of a hypervisor and use either Linux or Windows server editions. As part of your company's transformation strategy, you need to modernize workloads as much as possible by adopting cloud-native technologies. You need to migrate the workloads into Google Cloud. What should you do?

    • AExport the VMs into VMDK format, and import them into Compute Engine
    • BExport the VMs into VMDK format, and import them into Google Cloud VMware Engine
    • CMigrate the workloads using Migrate for Compute Engine
    • DMigrate the workloads using Migrate for Anthos

    Show answer

    Correct answer: D

    How others answered

    • D57%
    • C41%

    Only 57% agreed on this answer — treat it as contested rather than settled.

    Explanation

    Agree with C, Compute Engine. From GCP documentation "For the workloads that will benefit from containers, Migrate for Anthos and GKE delivers a fast, smooth path to modernization. For other workloads that are better suited as a VM, simply move them as is with Migrate for Compute Engine "

    Adapted from community discussion by fpreli · 2022-01-04 · 27 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

    View community discussion4

    Candidate context

    Question 17 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. F

       fpreli

       2022-01-04

       27 upvotes

       Agree with C, Compute Engine. From GCP documentation "For the workloads that will benefit from containers, Migrate for Anthos and GKE delivers a fast, smooth path to modernization. For other workloads that are better suited as a VM, simply move them as is with Migrate for Compute Engine "

    2. X

       x6207

       2022-03-06

       Selected D12 upvotes

       I would choose D. Migrate the workloads using Migrate for Anthos, because it is similar to Question #43 and this is C. Migrate the workloads to Compute Engine. I agree with Tom666

    3. H

       himanshu3004

       2023-08-17

       Selected D9 upvotes

       Difference between option C & D based on Purpose and Focus: Migrate for Anthos: This solution is focused on modernizing and migrating applications to containers and Kubernetes. It helps you containerize and manage your workloads using Google Kubernetes Engine (GKE) and provides a path to adopting cloud-native technologies. Migrate for Compute Engine: This solution is designed for straightforward lift-and-shift migrations of virtual machines (VMs) from on-premises or other clouds to Google Compute Engine (GCE) instances. In this question it's specifically mentioned that you need to modernize workloads as much as possible by adopting cloud-native technologies. Hence, I feel Anthos is a better choice here.

    4. F

       fpreli

       2022-01-04

       8 upvotes

       But, right, it says "cloud-native" and "modernize", so probably Migrate for Anthos is correct.

18. Question 18 of 25

    Your organization needs to minimize how much it pays for data traffic from the Google network to the internet. What should your organization do?

    • AChoose the Standard network service tier.
    • BChoose the Premium network service tier.
    • CDeploy Cloud VPN.
    • DDeploy Cloud NAT.

    Show answer

    Correct answer: A

    How others answered

    • A82%

    Explanation

    While Premium tier is the default for all egress traffic and offers the highest performance, it might not be the best option when cost is a consideration. Standard tier is the more economical , So option is A

    Adapted from community discussion by Tom666 · 2022-02-17 · 13 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

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    Candidate context

    Question 18 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. B

       Begum

       2022-02-15

       50 upvotes

       C& D are mechanisms , Use premium tier for performance and standard tier for cost optimizations.

    2. T

       Tom666

       2022-02-17

       Selected A13 upvotes

       While Premium tier is the default for all egress traffic and offers the highest performance, it might not be the best option when cost is a consideration. Standard tier is the more economical , So option is A

    3. L

       Lufly

       2023-08-25

       Selected A3 upvotes

       The answer is A. Choose the Standard network service tier. The Standard network service tier offers the best price-performance ratio for most workloads. It provides a predictable and reliable network with low latency and high throughput. The Premium network service tier offers a higher level of performance and reliability, but it also comes with a higher price tag. It is a good option for workloads that require the lowest possible latency or the highest possible throughput. Cloud VPN and Cloud NAT are both networking services that can be used to connect your Google Cloud resources to the internet. However, they do not directly affect the cost of data traffic from the Google network to the internet.

    4. M

       mintupintu

       2022-01-23

       4 upvotes

       Agree that question is vague and incomplete. Based on what is given, C (Cloud NAT) seems the best answer as it provide scalable / cost optimized solution for internal VM's to access the internet

19. Question 19 of 25

    Your organization wants to migrate your on-premises environment to Google Cloud. The on-premises environment consists of containers and virtual machine instances. Which Google Cloud products can help to migrate the container images and the virtual machine disks?

    • ACompute Engine and Filestore
    • BArtifact Registry and Cloud Storage
    • CDataflow and BigQuery
    • DPub/Sub and Cloud Storage

    Show answer

    Correct answer: B

    How others answered

    • B88%

    Explanation

    I'm voting for B, not A because Filestore is more user files oriented when Cloud Storage is the best choice for disk images. Artifact Registry (aka Container Registry) is THE storage service for container images.

    Adapted from community discussion by S00999 · 2022-08-12 · 9 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

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    Question 19 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. D

       Daffy16

       2022-06-01

       Selected B21 upvotes

       B: Artifact Registry can manage container image migration and Cloud Storage can store virtual disk image

    2. S

       S00999

       2022-08-12

       Selected B9 upvotes

       I'm voting for B, not A because Filestore is more user files oriented when Cloud Storage is the best choice for disk images. Artifact Registry (aka Container Registry) is THE storage service for container images.

    3. C

       cookieMr

       2023-06-11

       Selected B4 upvotes

       When migrating your containers and virtual machines to Google Cloud, you can utilize Artifact Registry and Cloud Storage to streamline the process and ensure a smooth transition. Artifact Registry can be used to store your container images as "golden images." These are pre-configured and optimized container images that serve as a starting point for deploying your containers in Google Cloud. You can push your golden images to Artifact Registry, where they will be securely stored and versioned. This allows you to easily manage and track different versions of your container images. On the other hand, Cloud Storage can be used to store your virtual machine disk images, which can also be considered as "golden images." These disk images contain the operating system and pre-installed software configurations that you want to use for your virtual machine instances. By uploading these disk images to Cloud Storage, you can ensure their availability and accessibility during the migration process.

    4. L

       Lufly

       2023-08-28

       Selected B3 upvotes

       Here are the reasons why the other options are not as good as Artifact Registry and Cloud Storage for migrating container images and virtual machine disks to Google Cloud: Compute Engine and Filestore are both compute services that can be used to create and run virtual machines. However, they do not provide a good way to store and manage container images. Dataflow and BigQuery are both data processing services. They can be used to process and analyze data, but they are not designed for storing and managing container images. Pub/Sub and Cloud Storage are both messaging and storage services. They can be used to store and transmit data, but they are not designed for storing and managing container images.

20. Question 20 of 25

    Your organization is defining the resource hierarchy for its new application in Google Cloud. You need separate development and production environments. The production environment will be deployed in Compute Engine in two regions. Which structure should your organization choose?

    • ACreate a single project for all environments. Use labels to segregate resources by environment.
    • BCreate a single project for all environments. Use tags to segregate resources by environment.
    • CCreate one project for the development environment and one project for the production environment.
    • DCreate two projects for the development environment and two projects for the production environment (one for each region).

    Show answer

    Correct answer: C

    How others answered

    • C96%

    Explanation

    The recommended structure for your organization's resource hierarchy in Google Cloud would be C. Create one project for the development environment and one project for the production environment. This structure provides clear separation between the development and production environments, allowing for better management and control of resources. By having separate projects, you can enforce different access controls, configurations, and deployments for each environment. This ensures that changes made in the development environment do not impact the production environment. Option A and B suggest using a single project for all environments and relying on labels or tags to segregate resources. While labels and tags can be useful for organizing and categorizing resources, they may not provide the same level of isolation and control as separate projects. Option D suggests creating multiple projects for each environment, with separate projects for the development and production environments in each region. While this approach could work, it may introduce unnecessary complexity, especially if the two regions have similar configurations and requirements.

    Adapted from community discussion by cookieMr · 2024-06-11 · 7 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

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    Candidate context

    Question 20 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. C

       cookieMr

       2024-06-11

       Selected C7 upvotes

       The recommended structure for your organization's resource hierarchy in Google Cloud would be C. Create one project for the development environment and one project for the production environment. This structure provides clear separation between the development and production environments, allowing for better management and control of resources. By having separate projects, you can enforce different access controls, configurations, and deployments for each environment. This ensures that changes made in the development environment do not impact the production environment. Option A and B suggest using a single project for all environments and relying on labels or tags to segregate resources. While labels and tags can be useful for organizing and categorizing resources, they may not provide the same level of isolation and control as separate projects. Option D suggests creating multiple projects for each environment, with separate projects for the development and production environments in each region. While this approach could work, it may introduce unnecessary complexity, especially if the two regions have similar configurations and requirements.

    2. F

       fpreli

       2023-01-05

       10 upvotes

       C is easier and you won't get less than D. I think creating one project per region wouldn't create benefit.

    3. A

       ajhak

       2024-01-04

       Selected C6 upvotes

       The part of compute engine being in two regions is meant to confuse you. It's not relevance.

    4. D

       desertlotus1211

       2023-02-10

       4 upvotes

       There is no such thing as creating a project by region... Resources are either global or regional....A project is just a 'project'... When you set up a project - where do you configure the region? https://cloud.google.com/resource-manager/docs/creating-managing-projects

21. Question 21 of 25

    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?

    • AOne project per team.
    • BOne organization per team.
    • COne project that contains all of each team's resources.
    • DOne top-level folder per team.

    Show answer

    Correct answer: D

    How others answered

    • D72%
    • A28%

    Only 72% agreed on this answer — treat it as contested rather than settled.

    Explanation

    It should be D, a top-level folder for each team give the ability to have multiple projects(I guess here goes the "teams efforts change frequently) and also cost is closely being watched and separated by Team->Team_Project. I hate GCP, so many poorly worded and vague questions...shame

    Adapted from community discussion by mamitos · 2022-09-28 · 41 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

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    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

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    Question 21 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. M

       mamitos

       2022-09-28

       Selected D41 upvotes

       It should be D, a top-level folder for each team give the ability to have multiple projects(I guess here goes the "teams efforts change frequently) and also cost is closely being watched and separated by Team->Team_Project. I hate GCP, so many poorly worded and vague questions...shame

    2. M

       mintupintu

       2022-01-23

       21 upvotes

       Correction: This is actually a tricky question. If we just follow the best practices of resource hierarchy recommendations by Google, D would the right answer. However, if you all pay close attention to the phrase "maintain cost visibility", this can be done using projects. The billing accounts can only be set at the Org level or the Project level, not the folder level. Hence, Answer is A. Read the below https://stackoverflow.com/questions/69421432/gcp-can-billing-be-configured-at-the-folder-level#:~:text=1%20Answer&text=You%20can%20associated%20a%20Google,billing%20account%20with%20a%20folder.

    3. P

       ptoul74

       2023-04-28

       8 upvotes

       Have a look at this image https://cloud.google.com/static/resource-manager/img/cloud-hierarchy.svg?dcb_=0.14515370615705625. Then, the correct answer is obviously D.

    4. D

       desertlotus1211

       2022-02-06

       7 upvotes

       Answer is A.... The Teams need to segmented to have visibility on the resources each team consumes

22. Question 22 of 25

    Your organization recently migrated its compute workloads to Google Cloud. You want these workloads in Google Cloud to privately and securely access your large volume of on-premises data, and you also want to minimize latency. What should your organization do?

    • AUse Storage Transfer Service to securely make your data available to Google Cloud
    • BCreate a VPC between your on-premises data center and your Google resources
    • CPeer your on-premises data center to Google's Edge Network
    • DUse Transfer Appliance to securely make your data available to Google Cloud

    Show answer

    Correct answer: B

    How others answered

    • B65%
    • C33%

    Only 65% agreed on this answer — treat it as contested rather than settled.

    Explanation

    Answer is C: Peer your on-premises data center to Googles Edge Network https://cloud.google.com/blog/products/networking/understanding-google-cloud-network-edge-points Scroll down to or Find "Cloud Interconnect POPs" where it says the following: "Dedicated Interconnect provides direct physical connections between your on-premises network and Google's network. Dedicated Interconnect enables you to efficiently transfer large amounts of data between networks."

    Adapted from community discussion by jexmtropicscheatchatya · 2022-08-25 · 11 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

    View community discussion4

    Candidate context

    Question 22 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. R

       rga91

       2022-05-14

       15 upvotes

       "privately and securely" doesnt fit with peering.... Answer is B

    2. J

       jexmtropicscheatchatya

       2022-08-25

       11 upvotes

       Answer is C: Peer your on-premises data center to Googles Edge Network https://cloud.google.com/blog/products/networking/understanding-google-cloud-network-edge-points Scroll down to or Find "Cloud Interconnect POPs" where it says the following: "Dedicated Interconnect provides direct physical connections between your on-premises network and Google's network. Dedicated Interconnect enables you to efficiently transfer large amounts of data between networks."

    3. K

       KC_go_reply

       2023-03-23

       12 upvotes

       You know B says 'VPC' and not 'VPN', right? A VPC is a virtual network, not a connection itself. You can´t use a VPC alone to connect between on-prem and GCP.

    4. L

       Loved

       2022-10-19

       12 upvotes

       Direct Peering or Carrier peering are both private and secure

23. Question 23 of 25

    An organization is searching for an open-source machine learning platform to build and deploy their own custom machine learning applications using TPUs. Which Google Cloud product or service should the organization use?

    • ATensorFlow
    • BBigQuery ML
    • CVision API
    • DAutoML Vision

    Show answer

    Correct answer: A

    How others answered

    • A73%
    • D27%

    Only 73% agreed on this answer — treat it as contested rather than settled.

    Explanation

    For building and deploying custom machine learning applications using TPUs, the organization can consider using Google Cloud's TensorFlow platform. TensorFlow is an open-source machine learning framework that provides comprehensive support for developing and deploying machine learning models, including integration with TPUs (Tensor Processing Units).

    Adapted from community discussion by cookieMr · 2023-06-11 · 6 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

    View community discussion4

    Candidate context

    Question 23 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. T

       the_var

       2023-07-06

       11 upvotes

       TPU = TensorFlow = TPU = TensorFlow! Admin, please correct the selected answer!

    2. C

       cookieMr

       2023-06-11

       Selected A6 upvotes

       For building and deploying custom machine learning applications using TPUs, the organization can consider using Google Cloud's TensorFlow platform. TensorFlow is an open-source machine learning framework that provides comprehensive support for developing and deploying machine learning models, including integration with TPUs (Tensor Processing Units).

    3. D

       ddeveloperr

       2025-02-01

       Selected A3 upvotes

       The correct answer is A. TensorFlow because it is an open-source machine learning platform that allows organizations to build and deploy custom machine learning models, including support for Google Cloud TPUs (Tensor Processing Units) to accelerate training and inference. Why Not the Other Options? B. BigQuery ML – Used for training ML models using SQL queries, but it does not provide full flexibility for building custom ML applications or TPU support. C. Vision API – A pre-trained API for image analysis, not for custom ML model development. D. AutoML Vision – A no-code/low-code solution for image classification, but it does not provide the full customization or TPU support needed for complex ML applications.

    4. T

       tjdef

       2022-10-24

       5 upvotes

       Based on the TensorFlow Enterprise product page, TF Enterprise is an opensource product which is offered on Google Cloud Platform: https://cloud.google.com/tensorflow-enterprise

24. Question 24 of 25

    An organization wants to use Apigee to manage all their application programming interfaces (APIs). What will Apigee enable the organization to do?

    • AIncrease application privacy
    • BMeasure and track API performance
    • CAnalyze application development speed
    • DMarket and sell APIs

    Show answer

    Correct answer: B

    How others answered

    • B95%

    Explanation

    The answer is B. Measure and track API performance. Apigee is an API management platform that helps organizations to develop, secure, and manage APIs. It provides a number of features that can help organizations to measure and track API performance, including:

    Adapted from community discussion by hireshgupta · 2023-07-24 · 6 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

    View community discussion4

    Candidate context

    Question 24 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. H

       hireshgupta

       2023-07-24

       Selected B6 upvotes

       The answer is B. Measure and track API performance. Apigee is an API management platform that helps organizations to develop, secure, and manage APIs. It provides a number of features that can help organizations to measure and track API performance, including:

    2. _

       __rajan__

       2023-10-22

       Selected B4 upvotes

       B. Measure and track API performance Apigee is an API management platform that helps organizations design, secure, deploy, monitor, and scale APIs. One of the key functionalities is the ability to measure and track API performance. Apigee provides analytics and monitoring tools that allow organizations to gain insights into how their APIs are being used, track performance metrics, and ensure that APIs are operating efficiently. This helps in optimizing API usage and identifying areas for improvement.

    3. F

       flykiwi

       2022-10-23

       Selected B4 upvotes

       Apigee features 1. Monitor APIs with comprehensive controls 2. Analyze your API traffic and developer engagement 3. Productize your APIs and drive their consumption 4. Capture direct or indirect revenues from your API products Just listed some features. the first one indicate answer B is correct The second one indicate answer C is not correct, because Apigee can not analyze development speed. The last two points indicate answer D sounds correct, but not accuracy

    4. O

       omgitsele

       2023-04-23

       Selected B4 upvotes

       So many wrong answers...Apigee is a comprehensive API management platform. Deployment options: Cloud, on-premises and hybrid. It can manage COMPLETE API lifecycle (Design, Secure, Monitor and Monetize APIs)

25. Question 25 of 25

    An organization needs to search an application's source code to identify a potential issue. The application is distributed across multiple containers. Which Google Cloud product should the organization use?

    • AGoogle Cloud Console
    • BCloud Trace
    • CCloud Monitoring
    • DCloud Logging

    Show answer

    Correct answer: D

    How others answered

    • D46%
    • B32%
    • A17%

    Only 46% agreed on this answer — treat it as contested rather than settled.

    Explanation

    Cloud Logging is a Google Cloud product that allows organizations to store, search, analyze, and monitor logs from various sources, including containers. By configuring the appropriate logging options, the organization can capture logs from the containers and then search the logs to identify potential issues within the application's source code. Therefore, option D (Cloud Logging) is the suitable Google Cloud product for searching an application's source code distributed across multiple containers.

    Adapted from community discussion by sivakarthick16 · 2024-01-21 · 7 community upvotes. Third-party contribution; reviewed by our quality filter, not independently verified.

    Supporting references

    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation
    • Google Cloud documentation

    View community discussion4

    Candidate context

    Question 25 discussion

    These are quality-filtered excerpts from third-party community discussion. They can be useful reasoning signals, but they are not official answers and have not been independently verified by CDL or CertExamHQ.

    1. S

       sivakarthick16

       2024-01-21

       Selected D7 upvotes

       Cloud Logging is a Google Cloud product that allows organizations to store, search, analyze, and monitor logs from various sources, including containers. By configuring the appropriate logging options, the organization can capture logs from the containers and then search the logs to identify potential issues within the application's source code. Therefore, option D (Cloud Logging) is the suitable Google Cloud product for searching an application's source code distributed across multiple containers.

    2. C

       cookieMr

       2023-06-11

       Selected D5 upvotes

       Cloud Logging is a Google Cloud product that allows organizations to store, search, analyze, and monitor log data generated by their applications and infrastructure. In the given scenario, where the organization needs to search an application's source code distributed across multiple containers, Cloud Logging can help in identifying potential issues by examining the logs. By configuring logging for the containers and the application running within them, the organization can capture relevant log data, including error messages, warnings, and other relevant information. They can then use Cloud Logging to search and analyze these logs to identify any potential issues within the application's source code.

    3. D

       Dardeery

       2023-11-09

       6 upvotes

       D is the correct answer , Cloud Logging is the Google Cloud product that allows organizations to search and analyze log data, including logs from distributed applications running across multiple containers. It provides a centralized location to view, filter, and search logs, making it suitable for identifying potential issues in an application's source code. You can use it to track and troubleshoot issues efficiently across your distributed environment. It's like having a detective tool that helps you find clues about what's happening inside your containers.

    4. P

       Preeetii

       2023-08-10

       Selected D3 upvotes

       Ans is D Cloud Logging is the Google Cloud product that allows organizations to search and analyze the logs generated by various services and applications running in their environment, including those distributed across multiple containers. In this case, the organization needs to identify a potential issue in an application's source code, and logs are often a valuable source of information to troubleshoot and diagnose issues. Cloud Logging allows you to collect, store, and analyze logs from different sources, including containers, virtual machines, and other Google Cloud services. By searching through logs using filters, you can pinpoint specific events, errors, or patterns that might indicate the source of the issue you're investigating. This is particularly useful when dealing with distributed systems like those running in containers, where logs from different containers can be aggregated and analyzed in one place.

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