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Google Cloud Professional Cloud Developer Practice Test

Google Professional Cloud Developer Practice Test

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Questions updated at Aug 26, 2026, 10:47 PM CDT

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Today's 10 Google Professional Cloud Developer questions

Use this Google Professional Cloud Developer practice test to review Google Cloud Professional Cloud Developer. Questions rotate daily and each answer links back to the source used to write it.

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200 verified questions are in the live bank. Free daily questions are selected from a rotating sample set. Unlock Pro to access the full question bank.

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Question 1 of 10
Objective Testing applications Building and testing applications (~23%)

A retry library is added to an API client. Which negative test is essential?

Concept tested:
Question 2 of 10
Objective Designing secure applications Designing highly scalable, secure, and reliable cloud-native applications (~32%)

A Cloud Run application calls Google Cloud APIs. The team is about to download a service-account JSON key because the code expects credentials. What should they do instead?

Concept tested:
Question 3 of 10
Objective Deploying applications to Cloud Run Configuring cloud-native applications for deployment (~24%)

A service requires a configuration value that is not secret and varies by environment. Which deployment mechanism is appropriate?

Concept tested:
Question 4 of 10
Objective Setting up your development environment Building and testing applications (~23%)

An engineer wants to inspect and modify a Kubernetes manifest with schema-aware assistance from within an IDE rather than switching to a separate browser console. Which tool is the best fit?

Concept tested:
Question 5 of 10
Objective Deploying containers to Google Kubernetes Engine Configuring cloud-native applications for deployment (~24%)

A production GKE cluster must reject an image unless it is signed by an approved release process. Which control should be used?

Concept tested:
Question 6 of 10
Objective Consuming Google Cloud APIs Integrating applications with Google Cloud services (~21%)

A Google Cloud API returns transient `UNAVAILABLE` responses during a brief outage. What retry strategy is appropriate?

Concept tested:
Question 7 of 10
Objective Building applications Building and testing applications (~23%)

An application passed tests against image digest X. A later pipeline rebuilds the same source and creates digest Y. Which artifact should be promoted if the goal is 'deploy exactly what was tested'?

Concept tested:
Question 8 of 10
Objective Troubleshooting and observability Integrating applications with Google Cloud services (~21%)

Trace ingestion cost is rising, but the team still needs representative latency visibility. What should they adjust rather than disabling tracing entirely?

Concept tested:
Question 9 of 10
Objective Integrating applications with data and storage services Integrating applications with Google Cloud services (~21%)

A system stores transactional order rows and multi-megabyte invoice PDFs. Which data layout is most appropriate?

Concept tested:
Question 10 of 10
Objective Designing high-performing applications and APIs Designing highly scalable, secure, and reliable cloud-native applications (~32%)

A product catalog service repeatedly reads the same small reference dataset from a database. The data changes only every few minutes, and database read latency dominates requests. What should the developer add?

Concept tested:
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The free daily Google Professional Cloud Developer set includes crawlable question text, answer choices, correct answer labels, objective mapping, and source links. Only the first SEO card includes answer explanations and any extra learning features. Pro-only bank questions stay locked; this section mirrors only the 10 free daily questions already shown on this page.

Question 1 A retry library is added to an API client. Which negative test is essential?

Answer choices

  1. A. Verify every API error is retried forever with exponential backoff so the client eventually succeeds without classifying errors as retryable or permanent.
  2. B. Verify non-transient or non-retryable errors are not retried indefinitely.
  3. C. Verify retries ignore server throttling.
  4. D. Verify successful requests are duplicated.

Correct answer

Verify non-transient or non-retryable errors are not retried indefinitely.

API clients should retry appropriate transient failures rather than every error indiscriminately. Core constraint: A retry library is added to an API client. The client should verify non-transient or non-retryable errors are not retried indefinitely.

Wrong-answer review

  • A. Verify every API error is retried forever with exponential backoff so the client eventually succeeds without classifying errors as retryable or permanent.: Incorrect. Retrying every error forever can loop on permanent failures such as invalid arguments or authorization errors, consuming resources and potentially duplicating side effects. Retry policy must distinguish transient failures.
  • C. Verify retries ignore server throttling.: Incorrect. Ignoring server throttling causes retries to compete with a service that is explicitly asking clients to slow down. Retry tests should verify appropriate backoff and respect for retryable conditions.
  • D. Verify successful requests are duplicated.: Incorrect. Successful requests should not be deliberately duplicated by a retry library. Retrying after success risks duplicate mutations and violates normal retry semantics.

Extra learning features

Why candidates miss this

The trap in this question is retrying every error indefinitely because the retry library was added for transient failures. The decisive clue is that test that transient failures retry with bounds while validation, permission, and other non-retryable errors fail without repeated side effects. Likely wrong answer: Verify every API error is retried forever with exponential backoff so the client eventually succeeds without classifying errors as retryable or permanent. Review focus: Professional Cloud Developer exam guide

Objective/domain: Building and testing applications (~23%)

Source: Cloud Client Libraries explained

Question 2 A Cloud Run application calls Google Cloud APIs. The team is about to download a service-account JSON key because the code expects credentials. What should they do instead?

Answer choices

  1. A. Embed the service-account key in the container image.
  2. B. Place the service-account key in a public Cloud Storage bucket under an obscure object name so the container can download it at startup.
  3. C. Use Application Default Credentials with the Cloud Run service identity.
  4. D. Grant every developer Owner so credentials are unnecessary.

Correct answer

Use Application Default Credentials with the Cloud Run service identity.

Objective/domain: Designing highly scalable, secure, and reliable cloud-native applications (~32%)

Source: How Application Default Credentials works

Question 3 A service requires a configuration value that is not secret and varies by environment. Which deployment mechanism is appropriate?

Answer choices

  1. A. Supply the value as a Cloud Run environment variable or service configuration rather than hard-coding it in the image.
  2. B. Store the nonsecret value in Secret Manager and grant the service secret-access permissions in every environment.
  3. C. Bake the environment-specific value into the container image and publish a different image for each environment.
  4. D. Pass the value as a Docker build argument and set it permanently in the image during the build.

Correct answer

Supply the value as a Cloud Run environment variable or service configuration rather than hard-coding it in the image.

Objective/domain: Configuring cloud-native applications for deployment (~24%)

Source: Configure environment variables for services

Question 4 An engineer wants to inspect and modify a Kubernetes manifest with schema-aware assistance from within an IDE rather than switching to a separate browser console. Which tool is the best fit?

Answer choices

  1. A. Use `kubectl explain` from Cloud Shell to inspect resource fields while editing the manifest separately.
  2. B. Use Cloud Code's Kubernetes development support in the IDE.
  3. C. Edit the manifest in the Google Cloud console and validate it only when applying it to the cluster.
  4. D. Use a generic YAML linter in the IDE without Kubernetes resource schemas or cluster-aware tooling.

Correct answer

Use Cloud Code's Kubernetes development support in the IDE.

Objective/domain: Building and testing applications (~23%)

Source: Cloud Code overview

Question 5 A production GKE cluster must reject an image unless it is signed by an approved release process. Which control should be used?

Answer choices

  1. A. Set `imagePullPolicy: Always` so each pod fetches the latest image before it starts.
  2. B. Enforce a Binary Authorization policy that requires the approved attestation.
  3. C. Grant Artifact Registry read access only to the production node identities and treat repository IAM as the signature check.
  4. D. Use a custom admission webhook that checks image tags but does not verify trusted attestations for the digest.

Correct answer

Enforce a Binary Authorization policy that requires the approved attestation.

Objective/domain: Configuring cloud-native applications for deployment (~24%)

Source: Binary Authorization overview

Question 6 A Google Cloud API returns transient `UNAVAILABLE` responses during a brief outage. What retry strategy is appropriate?

Answer choices

  1. A. Retry only retryable transient failures using bounded exponential backoff, adding jitter where appropriate.
  2. B. Retry `UNAVAILABLE` with a fixed one-second delay forever until the call succeeds.
  3. C. Apply the same retry loop to transient errors and permanent errors such as `PERMISSION_DENIED`.
  4. D. Disable retries entirely so the client never risks issuing the operation twice.

Correct answer

Retry only retryable transient failures using bounded exponential backoff, adding jitter where appropriate.

Objective/domain: Integrating applications with Google Cloud services (~21%)

Source: Cloud Client Libraries explained

Question 7 An application passed tests against image digest X. A later pipeline rebuilds the same source and creates digest Y. Which artifact should be promoted if the goal is 'deploy exactly what was tested'?

Answer choices

  1. A. Promote digest X rather than rebuilding an untested replacement artifact.
  2. B. Rebuild the same source again in the production pipeline and deploy whatever new digest results after production dependencies are resolved.
  3. C. Use the latest tag regardless of digest.
  4. D. Choose the larger image because it contains more packages.

Correct answer

Promote digest X rather than rebuilding an untested replacement artifact.

Objective/domain: Building and testing applications (~23%)

Source: Artifact Registry overview

Question 8 Trace ingestion cost is rising, but the team still needs representative latency visibility. What should they adjust rather than disabling tracing entirely?

Answer choices

  1. A. Log every request twice to compensate.
  2. B. Tune trace sampling to retain a useful representative subset that meets troubleshooting needs.
  3. C. Disable all telemetry.
  4. D. Increase sampling to 100% solely to reduce cost.

Correct answer

Tune trace sampling to retain a useful representative subset that meets troubleshooting needs.

Objective/domain: Integrating applications with Google Cloud services (~21%)

Source: Cloud Trace overview

Question 9 A system stores transactional order rows and multi-megabyte invoice PDFs. Which data layout is most appropriate?

Answer choices

  1. A. Store all PDF bytes in every order row by default.
  2. B. Store transactional rows as Secret Manager versions.
  3. C. Keep transactional order metadata in a database and store invoice PDFs in Cloud Storage, linking them by identifier.
  4. D. Use Pub/Sub as permanent PDF storage.

Correct answer

Keep transactional order metadata in a database and store invoice PDFs in Cloud Storage, linking them by identifier.

Objective/domain: Integrating applications with Google Cloud services (~21%)

Source: Storage options

Question 10 A product catalog service repeatedly reads the same small reference dataset from a database. The data changes only every few minutes, and database read latency dominates requests. What should the developer add?

Answer choices

  1. A. Cache the hot reference data in Memorystore with an expiration strategy appropriate to the update frequency.
  2. B. Increase database write capacity.
  3. C. Persist the cache only in each ephemeral application instance with an expiration policy chosen for the application's current data-refresh pattern.
  4. D. Replace asynchronous requests with synchronous calls.

Correct answer

Cache the hot reference data in Memorystore with an expiration strategy appropriate to the update frequency.

Objective/domain: Designing highly scalable, secure, and reliable cloud-native applications (~32%)

Source: Memorystore for Redis overview

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