PCD Building and testing applications Practice Test 2 — 15 Questions

Question 1

A developer created a Cloud Function that makes an HTTP request to an external API. The above error occurs intermittently. The external API is working correctly. What is the most likely cause?

Accepted Answer

The request to the external API has incorrect headers or payload. Intermittent failures on an HTTP call to a healthy external API most commonly stem from malformed requests — incorrect headers (e.g., missing Content-Type, bad Authorization token) or payloads that only fail under certain conditions (e.g., specific input values, expired tokens). Since the API itself works, the fault lies in how the function constructs the request.

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The function is not handling network retries properly

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The Cloud Function is not deployed in the same region as the API

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The function is timing out due to long response time

Question 2

A company uses Cloud Build to build multiple microservices. They want to reuse a set of build steps across all services. What is the most maintainable approach?

Accepted Answer

Use Cloud Build substitutions. Cloud Build substitutions allow you to define reusable variables in a central configuration, enabling you to parameterize build steps across multiple microservices without duplicating code. By referencing substitution variables (e.g., $_SERVICE_NAME) in a single cloudbuild.yaml, you can maintain one source of truth for common steps, making updates easier and reducing errors. This approach is more maintainable than copying steps because changes propagate automatically to all services.

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Copy the steps into each service's cloudbuild.yaml

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Create a custom builder image with the steps

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Use Cloud Build triggers with a common config file

Question 3

A team is setting up a CI/CD pipeline for a Node.js App Engine application using Cloud Build. The source code is in Cloud Source Repositories. What must be configured to automatically run unit tests before deployment?

Accepted Answer

Add a cloudbuild.yaml file with a test step. Cloud Build uses a cloudbuild.yaml file to define build steps, and adding a test step ensures unit tests run automatically before deployment. Without this configuration, Cloud Build will not execute tests; it only runs the steps explicitly defined in the build configuration file.

Answer

Enable Cloud Build triggers on the repository

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Use the App Engine deployment wizard

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Use a Dockerfile to run tests

Question 4

During a Cloud Build run, a developer sees the error: "Step #0: error: failed to fetch metadata: connection refused". The build is trying to access a private Docker registry in a different project. What is the most likely cause?

Accepted Answer

The build environment cannot reach the registry due to network restrictions. The error 'connection refused' indicates a network connectivity issue, not an authentication or authorization problem. The most likely cause is that the build environment (Cloud Build) cannot reach the private Docker registry in the other project due to network restrictions such as VPC Service Controls, firewall rules, or the registry being in a different VPC network. Authentication errors would typically show 'denied' or 'unauthorized'. Therefore, option B is correct.

Answer

The registry does not exist

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The build service account lacks IAM permissions to the registry

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The build is using a public pool with no access to internal networks

Question 5

A developer is using Cloud Functions and wants to ensure that their testing environment mirrors production as closely as possible. Which approach should they take?

Accepted Answer

Use the Functions Framework with a simulated production event. The Functions Framework is a local emulator that allows developers to run Cloud Functions locally with the same invocation context and event triggers as in production. By using the Functions Framework with a simulated production event, you can test your function's behavior, including event data parsing and response handling, without deploying to any cloud environment, ensuring the testing environment mirrors production as closely as possible.

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Use Cloud Build to run tests before deployment

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Run all tests in Cloud Shell

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Deploy to a staging Cloud Function and run tests against it

Question 6

Refer to the exhibit. A developer uses the above cloudbuild.yaml for a Cloud Run service. The trigger is set to run on pushes to the main branch. After a push, the build succeeds but the deployment fails with a permission error. What is the most likely issue?

Accepted Answer

The Cloud Build service account lacks permission to deploy to Cloud Run. The Cloud Build service account (typically the default compute engine service account or a user-specified service account) does not have the required IAM roles (e.g., roles/run.admin or roles/run.invoker) to deploy to Cloud Run. Even though the build step succeeds, the deployment step fails because the service account lacks the `run.services.create` or `run.services.update` permission for the target Cloud Run service.

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The region 'us-central1' is incorrect

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The container image tag ${SHORT_SHA} is invalid

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The Cloud Run service name 'my-service' is misspelled

Question 7

Refer to the exhibit. A developer runs the above command to deploy a Cloud Function triggered by Pub/Sub. The function fails to execute when a message is published. The logs show: "Function execution took 60001 ms, finished with status: 'timeout'". What should the developer do?

Accepted Answer

Check the function code for long-running operations. The timeout error indicates the Cloud Function is exceeding its maximum execution duration. The default timeout for Cloud Functions is 60 seconds, and the logs confirm the function ran for 60001 ms before being forcibly terminated. The most likely cause is that the function code contains long-running operations (e.g., synchronous HTTP calls, database queries, or heavy computation) that do not complete within the allotted time. Therefore, the developer should inspect and optimize the function code to reduce execution time, such as by using asynchronous processing or breaking the work into smaller chunks.

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Change the trigger to HTTP

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Reduce the number of function instances

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Increase the function timeout to 9 minutes

Question 8

Refer to the exhibit. A developer writes the above Dockerfile for a Cloud Run service. The service fails to start. The logs indicate that the container exited immediately. What is the most likely cause?

Accepted Answer

The server.js file is missing from the build context. The most likely cause is that the server.js file is missing from the build context. When the Dockerfile contains a COPY command (e.g., COPY . .) to copy application files, the server.js file must exist in the source directory from which the build is run. If it is absent, the container will have no entry point, and the CMD instruction (e.g., CMD ["node", "server.js"]) will fail because the file does not exist inside the image, causing the container to exit immediately. Cloud Run requires the container to start a listening process; without server.js, no process runs.

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The WORKDIR is set to a directory that doesn't exist

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The CMD instruction is incorrectly formatted

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The EXPOSE 8080 instruction is unnecessary and may cause conflicts

Question 9

A development team wants to implement a CI/CD pipeline for a containerized application on Google Cloud. They are using Cloud Build and Cloud Deploy. The application requires canary deployments with automatic rollback if the error rate increases by more than 10% within 5 minutes after deployment. Which Cloud Deploy feature should they configure?

Accepted Answer

Define a Cloud Deploy deployment policy with a rollout policy that uses a canary strategy and a verification phase with automated rollback. Cloud Deploy's deployment policies allow you to define a canary rollout strategy with an automated verification phase. When the verification phase detects that the error rate exceeds the defined threshold (e.g., 10% increase within 5 minutes), Cloud Deploy automatically initiates a rollback to the previous stable revision, meeting the team's requirement without additional custom code.

Answer

Configure a Pub/Sub notification on the rollout to trigger a rollback via a Cloud Function

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Use Cloud Monitoring to create an alert policy that triggers a Cloud Function to rollback the deployment

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Set up a Cloud Build trigger to rebuild the previous image on error

Question 10

Your organization uses Cloud Functions (1st gen) to process events from Cloud Storage. Recently, you migrated to Cloud Functions (2nd gen) to take advantage of longer timeouts and concurrency. After the migration, some invocations fail with 'DeadlineExceeded' errors even though the total execution time is below the 60-minute limit. What is the most likely cause?

Accepted Answer

The function is processing multiple concurrent requests per instance, causing a single request to exceed the HTTP timeout due to contention. Cloud Functions (2nd gen) supports concurrent request processing per instance. When multiple requests are handled simultaneously by the same instance, they share the instance's resources, including the HTTP timeout. If one request consumes excessive time due to contention (e.g., waiting for CPU or I/O), other concurrent requests may hit the HTTP request timeout (default 60 minutes for 2nd gen) even if their individual execution time is shorter. This is a common issue when migrating from 1st gen (which processes one request at a time) to 2nd gen with concurrency enabled.

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The function does not have enough memory allocated for the new workload

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The function is being cold-started more frequently due to reduced min instances

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The function timeout is still set to the 1st gen default of 9 minutes

Question 11

Your team is building a Node.js application for Google App Engine Standard Environment. The application uses a custom runtime and must run background tasks. However, you notice that background tasks are being terminated after a few seconds. What is the most likely reason?

Accepted Answer

App Engine Standard Environment does not support background threads; use App Engine Flexible or Cloud Run instead. In Google App Engine Standard Environment, background threads are not supported because the runtime can terminate idle instances or scale down to zero, killing any background tasks. The correct solution is to use App Engine Flexible Environment or Cloud Run, which support long-running background processes, or to offload tasks to a service like Cloud Tasks or Cloud Pub/Sub. Option D correctly identifies this fundamental limitation of the Standard Environment.

Answer

The application should use Cloud Tasks instead of background threads

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The application is not configured with max_concurrent_requests set to 1

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You are using an automatic scaling instance class that does not support background threads

Question 12

You are designing a CI/CD pipeline for a microservices application deployed on GKE. Your team requires that each service have independent release cycles and canary deployments. Which combination of Google Cloud services should you use?

Accepted Answer

Cloud Source Repositories, Cloud Build, and Cloud Deploy with GKE target. Cloud Deploy provides native support for canary deployments and progressive delivery strategies to GKE targets, enabling independent release cycles per microservice. Cloud Source Repositories hosts the code, Cloud Build compiles and tests it, and Cloud Deploy manages the rollout with Skaffold-based pipelines, allowing fine-grained traffic splitting and automated promotion or rollback.

Answer

Cloud Source Repositories, Cloud Build, and App Engine

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Cloud Source Repositories, Cloud Build, and Cloud Run

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Cloud Source Repositories, Cloud Build, and Spinnaker

Question 13

Your team is using Cloud Build to build and test a Java application. The build includes unit tests, integration tests, and static code analysis. The build is failing intermittently due to flaky tests. You want to automatically retry the failed steps without rebuilding everything. Which Cloud Build feature should you use?

Accepted Answer

Set the 'allowFailure: false' and 'retry: 2' options on the test steps in the cloudbuild.yaml. Cloud Build supports the `retry` option on individual build steps, which allows a step to be automatically retried a specified number of times upon failure without re-executing previous steps. This is ideal for handling flaky tests, as it only reruns the failed step, preserving build artifacts and avoiding a full rebuild.

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Configure a Cloud Build trigger to rerun the build on failure

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Use build substitutions to pass different test parameters on failure

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Increase the timeout for the build to allow retries

Question 14

Refer to the exhibit. You have the above cloudbuild.yaml file. The build succeeds but the call to the function fails with a permission error. What is the most likely cause?

Accepted Answer

The function call is occurring before the deployment is fully complete, and the function is not yet ready to serve requests. The most likely cause is that the Cloud Build step deploys the function, but the subsequent test call occurs before the function's HTTP endpoint is fully provisioned and serving requests. Cloud Functions deployment is asynchronous; after the `gcloud functions deploy` command returns, the function may still be in a 'DEPLOYING' or 'ACTIVE' state but not yet ready to handle traffic. A permission error in this context typically arises because the function's IAM policy (e.g., `--allow-unauthenticated`) is applied only after the deployment completes, and the function's runtime endpoint may return a 403 until fully ready.

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The function is using the wrong trigger type

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The runtime 'nodejs16' is not supported

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The '--allow-unauthenticated' flag is not allowed in Cloud Build

Question 15

Refer to the exhibit. A developer deployed a Cloud Run service with the above command. They notice that the service's latency is higher than expected under load. The service performs CPU-intensive tasks. What is the most likely reason for the high latency?

Accepted Answer

The execution environment is gen2, which only allocates CPU during request processing by default; the high concurrency causes CPU contention. Cloud Run's gen2 execution environment, by default, allocates CPU only during request processing. When concurrency is high, multiple requests compete for the same CPU quota, causing contention and increased latency for CPU-intensive tasks. The service's CPU-intensive nature exacerbates this issue, as the CPU is not continuously available between requests.

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The service is using gen2, which does not support CPU-intensive workloads

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The service should be deployed with --max-instances set to a lower number

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The memory is insufficient for the concurrency level