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Google Professional Cloud Developer exam dumps: questions 301 to 400 of 480

Page 4 of the free Google Professional Cloud Developer question bank for the Professional Cloud Developer exam. Questions 301 to 400 are listed below, the first 5 in full with answers and explanations. Back to page 1 for the exam overview and FAQ.

Question bank last updated December 2024

Free Google Professional Cloud Developer practice questions

Questions 301 to 305 of 480

Pick an answer before you open the explanation. Each question also has its own page with a permalink.

Google Professional Cloud Developer Question 301

Select 3Google Cloud Platform

You are deploying a new feature for a global e-commerce application hosted on Google Cloud. The feature is expected to significantly impact the user experience, and you want to minimize risk while monitoring user feedback. Which rollout strategies should you consider for this deployment?

  1. A

    Blue/Green Deployment

  2. B

    Canary Deployment

  3. C

    Big Bang Deployment

  4. D

    Feature Flags

  5. E

    Recreating all instances at once

Show answer and explanation

Correct answers: A, B, D

Explanation

Blue/Green Deployment, Canary Deployment, and Feature Flags are all appropriate rollout strategies for minimizing risk and monitoring feedback during feature deployment. These strategies allow for gradual or controlled rollouts, enabling you to verify the feature's impact and make adjustments if necessary. Big Bang Deployment and recreating all instances at once, however, are high-risk approaches that lack the flexibility needed for critical feature rollouts.

  • A. Correct.

    Blue/Green Deployment is a good strategy for minimizing risk because it allows you to test the new version on a separate environment and switch traffic to it only after verifying its stability.

  • B. Correct.

    Canary Deployment is suitable for gradually rolling out the feature to a small subset of users, which allows for monitoring and feedback before scaling up to the entire user base.

  • C. Incorrect.

    Big Bang Deployment involves deploying the feature to all users at once, which increases risk and does not allow for gradual monitoring or rollback. This is not recommended for critical feature rollouts.

  • D. Correct.

    Feature Flags allow you to roll out the feature to specific users or regions dynamically without redeploying the application, making it a flexible and low-risk option.

  • E. Incorrect.

    Recreating all instances at once is a high-risk approach that does not allow for gradual rollout or rollback. It is not considered an appropriate rollout strategy.

Google Professional Cloud Developer Question 302

Single answerGoogle Cloud Platform

Your team is deploying a new feature in a production environment with millions of active users. To minimize risk and ensure proper testing, you want to gradually expose the feature to a small subset of users before releasing it broadly. Which feature rollout strategy should you adopt?

  1. A

    Canary release

  2. B

    Blue/Green deployment

  3. C

    Big bang release

  4. D

    A/B testing

Show answer and explanation

Correct answer: A

Explanation

The canary release strategy is the most appropriate for gradually rolling out a feature to a small subset of users, allowing for risk mitigation and monitoring before a full deployment. This aligns with best practices for adopting feature rollout strategies in production environments.

  • A. Correct.

    Canary release involves deploying a new feature or version to a small subset of users first. This allows you to monitor its performance and catch issues before rolling it out to the entire user base, making it ideal for minimizing risk.

  • B. Incorrect.

    Blue/Green deployment focuses on switching traffic between two environments (Blue and Green) to ensure zero downtime deployment. Although useful for deployments, it does not provide gradual exposure to a subset of users.

  • C. Incorrect.

    Big bang release involves deploying the feature to all users at once. This approach is high-risk and does not allow for gradual rollout or testing with a smaller audience.

  • D. Incorrect.

    A/B testing is primarily used for comparing two versions of a feature or design to determine which performs better. It is not specifically a feature rollout strategy.

Google Professional Cloud Developer Question 303

Select 3Google Cloud Platform

Your team is preparing to release a new feature for a cloud-based application that serves global users. To ensure minimal disruption and a smooth user experience, you decide to adopt a feature rollout strategy. Which strategy or strategies would be most appropriate to achieve this goal?

  1. A

    Use a canary deployment to release the feature to a small percentage of users and monitor its performance before a full rollout.

  2. B

    Perform a blue/green deployment to switch all users to the new feature version immediately after testing.

  3. C

    Roll out the feature to all users simultaneously without monitoring, to minimize development time.

  4. D

    Leverage a phased rollout to gradually introduce the feature to users in different regions or groups.

  5. E

    Implement feature flags to enable or disable the feature for specific users or groups dynamically.

Show answer and explanation

Correct answers: A, D, E

Explanation

The combination of canary deployment, phased rollout, and feature flags provides a robust approach to adopting feature rollout strategies. Canary deployment ensures the feature is tested with minimal impact, phased rollout helps control exposure across regions or groups, and feature flags offer dynamic control over the feature's availability. These strategies collectively minimize disruption and enhance the user experience during a global feature rollout.

  • A. Correct.

    Canary deployment is a suitable strategy as it allows gradual exposure of the feature to a small group of users, helping to detect potential issues early and limit the impact.

  • B. Incorrect.

    While blue/green deployment ensures a smooth transition between versions, it typically involves switching all users to the new version at once, which doesn't align with minimizing disruption for global users.

  • C. Incorrect.

    Simultaneous rollout without monitoring increases the risk of introducing issues to all users and is not a best practice for critical applications.

  • D. Correct.

    Phased rollout is appropriate for gradual feature introduction, especially when targeting users in specific regions or groups, reducing the risk of widespread issues.

  • E. Correct.

    Feature flags provide flexibility to enable or disable the feature dynamically for specific users or groups, which is ideal for testing and addressing potential issues promptly.

Google Professional Cloud Developer Question 304

Single answerGoogle Cloud Platform

You are developing a new feature for a web application running on Google Cloud. The team wants to roll out the feature to a small subset of users to test its performance and gather initial feedback before releasing it to all users. Which strategy should you use to achieve this goal?

  1. A

    Blue/Green Deployment

  2. B

    Canary Deployment

  3. C

    Rolling Deployment

  4. D

    Big Bang Deployment

Show answer and explanation

Correct answer: B

Explanation

The Canary Deployment strategy is ideal for rolling out a new feature to a small subset of users. It allows the team to monitor the feature's performance, collect feedback, and ensure stability before a full rollout. Other strategies, such as Blue/Green and Rolling Deployments, may not focus on targeting a subset of users, while Big Bang Deployment introduces all changes to all users simultaneously, which can be risky.

  • A. Incorrect.

    Blue/Green Deployment involves having two separate environments (blue and green) where one is live and the other is used for testing. It is not designed for testing new features with a small subset of users.

  • B. Correct.

    Canary Deployment is a strategy where a new feature or version is rolled out to a small subset of users first, allowing you to monitor its impact and performance before rolling it out to the entire user base. This is the correct choice for the scenario.

  • C. Incorrect.

    Rolling Deployment gradually replaces instances of the old version with the new version across the entire infrastructure, but it does not specifically target a small subset of users, making it less suitable for this scenario.

  • D. Incorrect.

    Big Bang Deployment involves releasing the feature to all users at once. This approach does not allow for testing with a small subset of users and carries higher risks of widespread issues.

Google Professional Cloud Developer Question 305

Single answerGoogle Cloud Platform

You are responsible for deploying a new feature in a production environment on Google Cloud. The feature introduces significant changes to the user experience, and you want to minimize the risk of a negative impact on end-users. Which feature rollout strategy should you adopt to ensure a smooth transition and allow for monitoring and feedback before a full-scale release?

  1. A

    Blue-green deployment

  2. B

    Feature flagging

  3. C

    Canary deployment

  4. D

    Big bang deployment

Show answer and explanation

Correct answer: C

Explanation

Canary deployment is the most appropriate strategy for rolling out a feature in a controlled manner. It allows you to release the feature to a small subset of users, observe its performance, and identify issues before scaling up to the entire user base. This minimizes the impact of potential issues and ensures a smooth transition.

  • A. Incorrect.

    Blue-green deployment involves running two environments (blue and green) and switching traffic from one to the other. While it ensures zero downtime, it is not ideal for testing a feature incrementally for a subset of users.

  • B. Incorrect.

    Feature flagging allows you to toggle features on or off for specific users, but it doesn't control traffic segmentation or provide a gradual rollout strategy.

  • C. Correct.

    Canary deployment gradually releases the feature to a small subset of users, monitors its impact, and incrementally increases the release scope. This minimizes risk and gathers feedback effectively.

  • D. Incorrect.

    Big bang deployment releases the feature to all users at once. This is high-risk and does not allow for monitoring or gradual rollout, making it unsuitable for this scenario.

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Google Professional Cloud Developer practice questions 301 to 400 of 480

Every question has a page with the answer and explanation. Numbers are stable, so you can bookmark or share them. The bank is split into 5 pages of up to 100 questions.

  1. 301.You are deploying a new feature for a global e-commerce application hosted on Google Cloud. The feature is...
  2. 302.Your team is deploying a new feature in a production environment with millions of active users. To minimize...
  3. 303.Your team is preparing to release a new feature for a cloud-based application that serves global users. To...
  4. 304.You are developing a new feature for a web application running on Google Cloud. The team wants to roll out...
  5. 305.You are responsible for deploying a new feature in a production environment on Google Cloud. The feature...
  6. 306.You are deploying a new feature for your application on Google Cloud. The feature is critical, but you want...
  7. 307.You are deploying a new feature for your web application hosted on Google Cloud and want to run an A/B test...
  8. 308.You are a cloud developer managing a web application hosted on Google Cloud. You want to implement A/B...
  9. 309.You are developing a new feature for a web application hosted on Google Cloud. To evaluate the feature’s...
  10. 310.You are building an e-commerce application deployed on Google Cloud that uses A/B testing to evaluate two...
  11. 311.You are developing a web application hosted on Google Cloud that needs to implement A/B testing for a new...
  12. 312.You are developing a web application hosted on Google Cloud and want to implement A/B testing for a new...
  13. 313.You are developing a new feature in a microservices-based application deployed on Google Cloud. To enable...
  14. 314.Your team is developing a new feature for a production application hosted on Google Cloud. You want to...
  15. 315.You are deploying a new feature for your application using feature flags on Google Cloud. The feature is...
  16. 316.You are developing a microservices-based application on Google Cloud and want to roll out a new feature to...
  17. 317.Your team is deploying a new feature to a high-traffic application hosted on Google Cloud. To minimize risk,...
  18. 318.You are developing a web application deployed on Google Cloud that serves a global user base. The application...
  19. 319.You are working on a microservices-based application deployed on Google Kubernetes Engine (GKE). Your team is...
  20. 320.You are developing a new version of a REST API on Google Cloud that introduces additional fields to a...
  21. 321.You are developing a new version of a REST API for a microservices-based application deployed on Google...
  22. 322.You are developing a RESTful API that is widely used by client applications. A new requirement comes in to...
  23. 323.You are developing a REST API for an e-commerce platform hosted on Google Cloud. The API is already used by...
  24. 324.You are developing a new version of a REST API for a cloud-based application deployed on Google Cloud. The...
  25. 325.You are developing a RESTful API for a financial application and need to implement API versioning to ensure...
  26. 326.You are developing an API for a retail application and need to create a versioning strategy to ensure...
  27. 327.You are developing a REST API for an e-commerce platform and plan to introduce a new version of the API to...
  28. 328.You are developing an API that will be consumed by multiple clients, and you need to ensure backward...
  29. 329.You are designing a new version of an existing API using Apigee. To ensure backward compatibility and a...
  30. 330.You are developing an API for a payment processing system using Apigee. The API is currently versioned as...
  31. 331.You are developing a REST API service and want to deploy it to a serverless environment using Google Cloud...
  32. 332.You are deploying a Python-based REST API to Google Cloud Functions. The API relies on a third-party library...
  33. 333.You are tasked with deploying a Node.js application to a serverless environment using Google Cloud Functions....
  34. 334.You are deploying a serverless application using Cloud Run. The application processes incoming HTTP requests...
  35. 335.You are deploying a new serverless application to Google Cloud Functions. The application needs to process...
  36. 336.You are deploying a Python-based application to Google Cloud Functions. The application processes uploaded...
  37. 337.You are developing a Node.js application and want to deploy it to Google Cloud Run directly from your source...
  38. 338.You are tasked with deploying a web application to Google Cloud. The source code is stored in a GitHub...
  39. 339.You are tasked with deploying an application from source code to Google Cloud. The application is a Node.js...
  40. 340.You are tasked with deploying a Node.js application to Google Cloud. The application source code is stored in...
  41. 341.You are tasked with deploying a containerized application to Google Kubernetes Engine (GKE) directly from its...
  42. 342.You want to deploy a Node.js application to Google Cloud without manually creating a Dockerfile or managing...
  43. 343.You are developing a backend system on Google Cloud and need to process uploaded images in real-time. The...
  44. 344.You are building a serverless application using Google Cloud Functions, and you need to trigger a function...
  45. 345.You are developing a serverless application using Google Cloud Functions. The application needs to...
  46. 346.You are developing a Google Cloud Function to process user-uploaded images. The function should automatically...
  47. 347.You are developing a serverless application on Google Cloud and want to trigger a Cloud Function when a new...
  48. 348.You are developing a serverless application on Google Cloud and need to trigger a Cloud Function whenever a...
  49. 349.You are developing a cloud-native application that processes file uploads to a Cloud Storage bucket. When a...
  50. 350.You are developing a serverless application that needs to process events generated by a Cloud Storage bucket...
  51. 351.You are building a serverless application on Google Cloud and need to configure an event-driven architecture...
  52. 352.You are developing a serverless application that processes images uploaded to a Cloud Storage bucket. You...
  53. 353.You are developing a serverless application and need to configure an event-driven architecture. Your...
  54. 354.Your development team is building a serverless architecture where events from a Cloud Storage bucket trigger...
  55. 355.You are developing an API that will be exposed to external clients to retrieve sensitive customer data. To...
  56. 356.You are developing an API for an e-commerce application on Google Cloud. The API needs to be exposed to...
  57. 357.You are developing an API for your application and want to expose it securely using Apigee. The API must...
  58. 358.You are tasked with exposing an existing backend service through a secure API using Apigee. The API should...
  59. 359.You are a developer tasked with exposing an API for a retail application using Apigee. The API must be...
  60. 360.You are developing an API for an e-commerce platform that will be exposed to third-party developers. To...
  61. 361.You are deploying a stateless web application to Google Kubernetes Engine (GKE). The application needs to...
  62. 362.You are deploying a multi-tier web application to Google Kubernetes Engine (GKE). The application consists of...
  63. 363.You are deploying a stateless microservice application to Google Kubernetes Engine (GKE). The application...
  64. 364.You are deploying a web application to Google Kubernetes Engine (GKE). The application requires high...
  65. 365.You are deploying a stateless web application to Google Kubernetes Engine (GKE) and need to ensure that the...
  66. 366.You are deploying a web application to Google Kubernetes Engine (GKE) with autoscaling enabled. The...
  67. 367.You are tasked with deploying a containerized application to Google Kubernetes Engine (GKE). The application...
  68. 368.You are deploying a containerized web application to Google Kubernetes Engine (GKE). The application requires...
  69. 369.You are tasked with deploying a containerized application to a Google Kubernetes Engine (GKE) cluster. The...
  70. 370.You are tasked with deploying a containerized application to a Google Kubernetes Engine (GKE) cluster. The...
  71. 371.You are tasked with deploying a containerized application to Google Kubernetes Engine (GKE). The application...
  72. 372.You are deploying a containerized application to a Google Kubernetes Engine (GKE) cluster. The application...
  73. 373.You are deploying a Kubernetes application on Google Kubernetes Engine (GKE) and want to enforce fine-grained...
  74. 374.You are deploying a Kubernetes application on Google Kubernetes Engine (GKE) and need to configure...
  75. 375.You are developing a Kubernetes-based application hosted in Google Kubernetes Engine (GKE). The application...
  76. 376.You are deploying a Kubernetes application on Google Kubernetes Engine (GKE) and want to integrate Kubernetes...
  77. 377.You are a cloud developer tasked with integrating Kubernetes RBAC and Google Cloud IAM for a GKE cluster. You...
  78. 378.You are developing a Kubernetes application running on Google Kubernetes Engine (GKE). Your team wants to...
  79. 379.You are deploying a containerized workload to Google Kubernetes Engine (GKE). The workload requires a minimum...
  80. 380.You are deploying a containerized web application on Google Kubernetes Engine (GKE) and want to ensure the...
  81. 381.You are deploying a machine learning model as a containerized application on Google Kubernetes Engine (GKE)....
  82. 382.You are deploying a containerized application to Google Kubernetes Engine (GKE). The application has a...
  83. 383.You are tasked with deploying a new containerized workload on Google Kubernetes Engine (GKE). The workload is...
  84. 384.You are deploying a containerized application to Google Kubernetes Engine (GKE). The application has variable...
  85. 385.You are tasked with building a container image for your application using Google Cloud Build. The application...
  86. 386.You are tasked with building a container image for your application using Cloud Build. The application...
  87. 387.You are tasked with building a container image for a Python-based web application using Google Cloud Build....
  88. 388.You are developing a web application and need to containerize it using Cloud Build. Your application requires...
  89. 389.You are a developer tasked with creating a container image for your Python application using Google Cloud...
  90. 390.You are a developer tasked with building a container image for your application using Cloud Build. The...
  91. 391.You are developing a cloud-based application that processes and analyzes large datasets stored in Google...
  92. 392.You are developing a serverless web application on Google Cloud that needs to store user-uploaded images and...
  93. 393.You are building a serverless application on Google Cloud that processes user-uploaded images and stores...
  94. 394.You are developing a serverless application on Google Cloud that processes images uploaded by users. The...
  95. 395.You are designing a serverless application on Google Cloud that processes customer orders. Each order's...
  96. 396.You are developing a cloud-native application that needs to store large amounts of unstructured data, such as...
  97. 397.You are developing a serverless application on Google Cloud that needs to interact with a Cloud SQL database....
  98. 398.You are developing a serverless application on Google Cloud that uses Cloud Run to handle HTTP requests. Your...
  99. 399.You are building a serverless application on Google Cloud that connects to a Cloud SQL database. The...
  100. 400.You are developing a cloud-native application that needs to connect to a Cloud SQL database. The application...