PCD Practice Test 4 — 10 Questions

Question 1

You are deploying a Node.js application on Cloud Run. The container image is stored in Artifact Registry. After deploying with gcloud run deploy, the revision fails with 'Container failed to start. Failed to start and then listen on the port defined by the PORT environment variable.' The application listens on port 8080 by default. The Dockerfile uses EXPOSE 8080. The Cloud Run service is configured with container port 8080. You have verified that the container starts locally using docker run -p 8080:8080. What is the most likely cause of the startup failure?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

The application is hardcoded to listen on port 8080 but the Cloud Run environment variable PORT may override it to a different value.. Cloud Run injects a PORT environment variable that the container must listen on; the application is hardcoded to 8080, so if Cloud Run sets PORT to a different value (e.g., 8081), the app listens on the wrong port and fails the health check. The error message explicitly references the PORT environment variable, indicating the app ignored it. Since the container works locally with port 8080, the issue is the mismatch between the hardcoded port and the dynamically assigned PORT.

Answer

The application is trying to bind to a privileged port.

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The Cloud Run service is configured with container port 443 by default.

Answer

The container does not have a proper HEALTHCHECK instruction.

Question 2

A team is deploying a microservice on Cloud Run that requires environment variables with sensitive information, such as database passwords. What is the recommended way to provide these secrets?

Accepted Answer

Use Secret Manager to store the secrets and refer to them in the Cloud Run service.. Secret Manager is Google Cloud's dedicated service for securely storing and managing sensitive data like API keys and database passwords. Cloud Run natively integrates with Secret Manager, allowing you to reference secret versions by name in your service configuration without exposing the secret value in plaintext. This approach ensures secrets are encrypted at rest and in transit, and access can be tightly controlled via IAM permissions.

Answer

Inject them directly in the Cloud Run YAML configuration.

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Embed them in the container image as environment variables.

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Store them in a Cloud Storage bucket and mount as a volume.

Question 3

Which THREE are valid approaches for automating testing in a Cloud Build CI pipeline?

Accepted Answer

Use Cloud Build triggers to run tests on every push to a branch.. Option B is correct because Cloud Build triggers (e.g., a push trigger on a branch) can automatically start a build that executes test steps whenever code is pushed, which is a standard CI testing approach. Option D is correct because Cloud Build supports multiple steps in a build config, and steps run in parallel by default unless you declare waitFor dependencies, so tests can be distributed across parallel steps for faster feedback. Option E is correct because a build step can use a custom builder image (referenced via the 'name' field in cloudbuild.yaml) that contains your test framework and commands, allowing arbitrary test execution inside the pipeline. Option A is not a valid testing approach because Cloud Monitoring is for metrics, dashboards, and alerting, not for shipping or executing test results as part of CI. Option C is not a valid Cloud Build testing approach because Cloud Build does not natively gate steps on manual approval; approvals are handled by external systems or release pipelines, not as a built-in Cloud Build test mechanism.

Answer

Use Cloud Build to ship test results to Cloud Monitoring.

Answer

Use Cloud Build to run tests only after manual approval.

Question 4

A company wants to run hybrid transactional/analytical processing (HTAP) workloads on a PostgreSQL-compatible database with built-in columnar engine for faster analytical queries. Which Google Cloud database should they choose?

Accepted Answer

AlloyDB. AlloyDB is a PostgreSQL-compatible database service with a built-in columnar engine that accelerates analytical queries by storing data in columns rather than rows, enabling HTAP workloads without needing to move data between separate transactional and analytical systems. Its architecture decouples compute from storage and uses a columnar cache to deliver up to 100x faster analytical queries than standard PostgreSQL, making it the correct choice for HTAP on Google Cloud.

Answer

Cloud SQL for PostgreSQL

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Cloud Spanner

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BigQuery

Question 5

A developer wants to automatically detect and capture application errors in a production environment on Google Cloud. Which two Google Cloud services should be enabled? (Choose two.)

Accepted Answer

Cloud Error Reporting. Cloud Error Reporting aggregates and displays application errors in real time, allowing developers to automatically detect and capture errors in production. Cloud Logging stores all application logs, which Error Reporting uses as a source to identify and analyze error events. Together, they provide a complete solution for error detection and capture without manual intervention.

Answer

Cloud Trace

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Cloud Profiler

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Cloud Debugger

Question 6

A developer notices that a Cloud Function is timing out after 60 seconds. The function makes an external API call that occasionally takes longer than the timeout. What is the best practice to handle this?

Accepted Answer

Increase the timeout for the specific Cloud Function to a higher value. Cloud Functions have a configurable timeout per function (up to 540 seconds for HTTP functions). Increasing the timeout for the specific function that makes the slow external API call directly addresses the timeout issue without affecting other functions or introducing unnecessary retry overhead. This is the most targeted and efficient solution.

Answer

Implement retry logic without changing the timeout

Answer

Increase the timeout for all Cloud Functions in the project

Answer

Decrease the timeout to fail fast and implement retry logic

Question 7

A company is migrating a monolithic Java application to microservices on Google Kubernetes Engine (GKE). The application uses a shared MySQL database. The team wants to adopt a testing strategy that validates service interactions without deploying to a full cluster. Which testing approach is most appropriate?

Accepted Answer

Consumer-driven contract testing with tools like Spring Cloud Contract.. Consumer-driven contract testing (CDC) with tools like Spring Cloud Contract validates the interactions between microservices by defining and verifying API contracts (e.g., request/response formats, headers, status codes) without requiring a full GKE cluster. This approach is ideal for a migration from a monolithic Java application because it ensures that each service adheres to its expected behavior when communicating over HTTP or messaging, catching integration issues early in the development cycle. It does not require deploying to a cluster, making it faster and more lightweight than end-to-end testing.

Answer

Load testing to simulate production traffic.

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Unit testing with mocked dependencies.

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End-to-end testing in a staging environment.

Question 8

A company is using Cloud Run for a stateless API. They want to ensure that the service can handle sudden traffic spikes. Which two features should they configure?

Accepted Answer

Enable container concurrency.. Enabling container concurrency allows a single Cloud Run container instance to handle multiple requests simultaneously, up to the configured concurrency limit (default 80, max 1000). This improves throughput and resource utilization during traffic spikes without requiring additional instances. Option D is correct because setting max instances to a high value ensures the service can scale out to handle sudden load by creating more container instances, up to the configured maximum, preventing cold starts and request queuing.

Answer

Use Cloud Load Balancing.

Answer

Enable CPU always on allocation.

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Set min instances to zero to save cost.

Question 9

You want to identify performance bottlenecks in your application's code, such as functions consuming excessive CPU. Which Google Cloud tool should you use?

Accepted Answer

Cloud Profiler. Cloud Profiler is the correct tool because it continuously gathers CPU and memory usage data from your application's functions and methods, presenting a flame graph or call graph that pinpoints which code paths consume the most resources. This allows you to identify performance bottlenecks like functions consuming excessive CPU without adding significant overhead to your production environment.

Answer

Cloud Monitoring

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Cloud Trace

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Cloud Logging

Question 10

A company is migrating a 500 GB MySQL database to Cloud SQL for MySQL 8.0. They want to test the migration with minimal risk before the final cutover. Which TWO testing approaches should they use?

Accepted Answer

Set up shadow writes to dual-write to both source and target databases.. Option A is correct because shadow writes (dual-writing to both the source and the Cloud SQL target) let the team validate write-path compatibility, replication fidelity, and application behavior against MySQL 8.0 in production-like conditions without exposing users to the new database, which directly supports low-risk testing before cutover. Option C is correct because running comparison queries on a snapshot of data from both databases verifies data consistency and correctness (row counts, checksums, key business queries) after a test migration, catching transformation or replication discrepancies before the final cutover. Option B is not appropriate because synthetic-data load testing alone does not validate real data fidelity or application compatibility with the actual 500 GB dataset. Option D is not a testing approach for validating the migration; migrating only the schema with Database Migration Service tests connectivity and DDL compatibility but not data movement or application behavior. Option E is a prudent risk-management step, but a rollback plan is not a migration testing approach and does not itself validate the migration.

Answer

Perform load testing using synthetic data only.

Answer

Use Database Migration Service to migrate only the schema first.

Answer

Create a rollback plan before starting migration.