PCD Practice Test 26 — 15 Questions

Question 1

A development team is building a containerized application on Google Cloud. They want to implement a CI/CD pipeline that automatically builds and tests their application on every push to the main branch. Which TWO actions should they take to achieve this?

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

Accepted Answer

Configure a Cloud Build trigger to run on push events to the main branch.. Cloud Build triggers can be configured to automatically start a build whenever a push event occurs on a specific branch, such as main. This is the standard way to initiate a CI/CD pipeline in response to code changes in Google Cloud.

Answer

Enable Cloud Run for Anthos to automatically deploy after build.

Answer

Use Cloud Scheduler to trigger a Cloud Build trigger every 5 minutes.

Answer

Create a Cloud Source Repository and use Cloud Functions to build on push.

Question 2

A company uses Cloud Bigtable for time-series data. They notice uneven load distribution across nodes causing hot spots. Which tool should they use to identify the hot spots?

Accepted Answer

Cloud Bigtable Key Visualiser. Cloud Bigtable Key Visualiser graphically shows read/write heatmaps to identify hot spots. Monitoring dashboards show metrics but not specific hot spots. cbt tool is CLI, not visual. Cloud Logging records operations but doesn't visualize load distribution.

Answer

Cloud Monitoring dashboards

Answer

cbt command-line tool

Answer

Cloud Logging

Question 3

A team is migrating a Teradata data warehouse to BigQuery. They use BTEQ scripts for ETL. What is the best approach to migrate the BTEQ scripts?

Accepted Answer

Rewrite BTEQ scripts as BigQuery SQL using GoogleSQL syntax, manually handling differences.. Teradata BTEQ scripts use Teradata SQL dialect. BigQuery uses GoogleSQL (or legacy SQL). Direct translation is needed. The BigQuery Data Transfer Service can automate loading from Teradata but does not convert BTEQ scripts. Manual rewriting or using a SQL translation tool is required. Some BTEQ commands have no BigQuery equivalent (e.g., .EXPORT).

Answer

Use a third-party tool like Ora2Pg to convert BTEQ scripts.

Answer

Use BigQuery Data Transfer Service to automatically convert BTEQ scripts to BigQuery SQL.

Answer

Run BTEQ scripts directly in BigQuery using the BigQuery Connector for Teradata.

Question 4

Your company is deploying a web application on Cloud Run using a continuous deployment pipeline from Cloud Build. The application is built as a Docker container and pushed to Container Registry. The Cloud Run service is configured with the '--no-allow-unauthenticated' flag. You have set up Cloud Build triggers to build and deploy on commits to the main branch. The deployment works correctly for the first few commits, but after adding a new environment variable in the Cloud Build configuration file (cloudbuild.yaml), the deployment fails with an error that the Cloud Run service cannot be updated because the new revision fails health checks. The application code has not changed. What is the most likely cause?

Accepted Answer

The new environment variable causes the application to fail its startup or health check.. The application code has not changed, yet the deployment fails health checks immediately after adding a new environment variable. This indicates that the application is likely reading that variable at startup and crashing or failing its readiness probe due to an invalid value, missing dependency, or misconfiguration. Cloud Run requires the new revision to pass health checks (e.g., HTTP GET on the configured port) before it can serve traffic; if the variable causes the app to exit or hang, the revision is considered unhealthy and the update is rejected.

Answer

The Cloud Build service account does not have permission to update the Cloud Run service.

Answer

The new environment variable exceeds the maximum size limit for environment variables in Cloud Run.

Answer

The health check configuration in the Cloud Run service was overwritten by the new deployment.

Question 5

A developer needs to connect to a Cloud SQL for PostgreSQL instance from a Compute Engine VM without adding the VM's IP to an authorized networks list. Which method should they use?

Accepted Answer

Use Cloud SQL Auth Proxy. The Cloud SQL Auth Proxy is the recommended method for securely connecting to a Cloud SQL instance from a Compute Engine VM without adding the VM's IP to an authorized networks list. It uses mutual TLS (mTLS) to authenticate and encrypt traffic, and it handles IAM-based authorization, so the VM only needs the Cloud SQL Client role and outbound access to the Cloud SQL API (port 443). This avoids exposing the database to the public internet or requiring static IP management.

Answer

Connect via Cloud Shell

Answer

Configure direct IP connection with SSL

Answer

Set up VPC peering and use private IP

Question 6

A company is migrating a MySQL database to Cloud SQL. They want to test the migration by sending writes to both the old and new databases simultaneously and comparing results. Which TWO techniques should they use?

Accepted Answer

Shadow writes (dual-write to both databases). Option A, shadow writes (dual-write to both databases), is correct because it is the core mechanism for this test: the application writes each transaction to the legacy MySQL database and the Cloud SQL instance at the same time, letting the team observe how the new database behaves under real production write traffic without cutting over. Option E, comparison queries to validate data consistency, is correct because after (or during) dual-writing, the team must run queries that compare row counts, checksums, or key values between the two databases to confirm the new database produces the same results as the old one. Option B, rollback plan documentation, is a prudent migration practice but does not itself send writes to both databases or compare results, so it does not satisfy the scenario. Option C, load testing with production data shape, exercises performance and capacity but does not perform simultaneous dual writes or consistency comparison. Option D, Database Migration Service continuous migration, is a replication/migration tool for moving data, not a technique for dual-writing from the application and validating consistency between the two live databases.

Answer

Rollback plan documentation

Answer

Load testing with production data shape

Answer

Database Migration Service continuous migration

Question 7

A team is deploying a microservices application on Google Kubernetes Engine (GKE). They want to ensure that if a pod fails, Kubernetes automatically replaces it and maintains the desired number of replicas. Which Kubernetes resource should they use?

Accepted Answer

Deployment. A Deployment is the correct Kubernetes resource for managing stateless microservices that require automatic pod replacement to maintain a desired replica count. It uses a ReplicaSet to ensure the specified number of pod replicas are running, and if a pod fails, the ReplicaSet controller immediately creates a new pod to restore the desired state.

Answer

StatefulSet

Answer

Job

Answer

DaemonSet

Question 8

A development team needs a serverless NoSQL document database for a new mobile application that requires offline synchronization for users. The database should scale automatically and integrate with Firebase Authentication. Which Google Cloud database meets these requirements?

Accepted Answer

Firestore. Firestore is a serverless NoSQL document database that natively supports offline synchronization for mobile and web clients, scales automatically, and integrates directly with Firebase Authentication. These features match every requirement in the scenario. It is the default choice for Firebase-based mobile applications.

Answer

Memorystore for Redis

Answer

Cloud SQL

Answer

Cloud Bigtable

Question 9

What is the primary benefit of using Cloud Load Balancing with global anycast IP?

Accepted Answer

Reduces latency for users worldwide. Cloud Load Balancing with a global anycast IP directs user traffic to the nearest available backend instance based on network topology and latency. This minimizes the number of network hops and reduces round-trip time, providing lower latency for users worldwide compared to a single-region deployment.

Answer

Provides DDoS protection

Answer

Supports WebSocket

Answer

Enables cross-zone failover

Question 10

A financial services company needs a globally distributed database with strong consistency across continents, 99.999% SLA, and support for ACID transactions. They expect millions of transactions per day. Which Google Cloud database should they use?

Accepted Answer

Cloud Spanner. Cloud Spanner is the only Google Cloud database that offers global distribution with strong consistency, ACID transactions, and 99.999% SLA. It is designed for mission-critical workloads that require horizontal scaling and geo-replication.

Answer

Cloud SQL

Answer

Bigtable

Answer

Firestore

Question 11

A team is building a microservices architecture on Google Cloud. They want services to communicate asynchronously to avoid tight coupling. They also need to guarantee at-least-once delivery of messages. Which two services should they use together? (Choose TWO.)

Accepted Answer

Cloud Tasks. To achieve asynchronous communication with at-least-once delivery, the team should use Cloud Tasks (option C) for reliable task execution with retries and Cloud Pub/Sub (option D) for asynchronous messaging with guaranteed at-least-once delivery. Cloud Run (HTTP) is synchronous, Cloud Endpoints is an API gateway, and Cloud Datastore is a database, so none of these meet the async and delivery requirements.

Answer

Cloud Run (HTTP)

Answer

Cloud Endpoints

Answer

Cloud Datastore

Question 12

A company uses Cloud Spanner for its global financial application. They want to capture all changes to a Spanner table and stream them to Pub/Sub for downstream processing by a Dataflow pipeline. What is the recommended approach?

Accepted Answer

Create a Spanner change stream and use Dataflow to read from the change stream and publish to Pub/Sub.. Spanner change streams are the native, built-in mechanism for capturing row-level changes in Cloud Spanner. Dataflow can directly read from a Spanner change stream using the Spanner change streams connector, and then publish the changes to Pub/Sub for downstream processing. This approach is fully managed, scalable, and avoids the latency and consistency issues of polling or external CDC tools.

Answer

Configure Pub/Sub Lite to directly connect to Spanner change streams.

Answer

Use a Cloud Function to query the Spanner table every minute and publish changes to Pub/Sub.

Answer

Enable Cloud SQL change data capture on the Spanner table and push changes to Pub/Sub.

Question 13

A company wants to implement polyglot persistence: an RDBMS for transactions, a NoSQL database for session storage, and a data warehouse for analytics. Which combination of Google Cloud databases best suits this architecture?

Accepted Answer

Cloud SQL (transactions), Bigtable (session storage), BigQuery (analytics). Cloud SQL is a managed relational database service offering ACID transactions and is the standard choice for transactional workloads that do not require global scale. Bigtable is a NoSQL wide-column database designed for high-throughput, low-latency access, making it suitable for session storage at scale. BigQuery is a serverless data warehouse for analytics. Cloud Spanner is a globally distributed relational database that is more expensive and complex than necessary for typical transactional workloads, and Firestore is a document database better suited to mobile and web application data than session caching.

Answer

Cloud Spanner (transactions), Firestore (session storage), BigQuery (analytics)

Answer

Cloud SQL (transactions), Firestore (session storage), Bigtable (analytics)

Answer

Firestore (transactions), Memorystore (session storage), BigQuery (analytics)

Question 14

A developer is building a containerized application on Cloud Run. They want to test the application locally before deploying. Which two tools should they use? (Choose 2)

Accepted Answer

Docker Desktop. Docker Desktop allows running the container locally. Cloud Code (for VS Code or IntelliJ) provides integrated debugging, local emulation, and one-click deployment to Cloud Run. Cloud Build is for CI/CD, not local testing. Functions Framework is for Cloud Functions, not Cloud Run. Cloud Run for Anthos is for hybrid environments.

Answer

Functions Framework

Answer

Cloud Build

Answer

Cloud Run for Anthos

Question 15

A company is using Datastream to replicate data from an on-premises PostgreSQL database to BigQuery. They encounter high latency in replication. Which THREE steps should they take to improve performance? (Select 3)

Accepted Answer

Enable parallel processing in Datastream source configuration. Option B is correct because Datastream supports parallel processing of a PostgreSQL source by splitting the initial backfill and change stream across multiple concurrent streams/threads, which increases throughput and reduces replication latency. Option C is correct because the Dataflow streaming job that writes Datastream changes into BigQuery scales with the number of workers; adding workers increases parallelism for the write/transform stage and relieves worker-side bottlenecks. Option D is correct because inserting a Pub/Sub topic between Datastream and Dataflow provides a durable buffer that absorbs bursts of change events, preventing backpressure from stalling the pipeline and smoothing latency spikes. Option A is not correct because Datastream is a fully managed, serverless service and does not expose a user-selectable 'machine type' to resize. Option E is not correct because reducing PostgreSQL WAL retention does not improve replication throughput and can actually break replication if Datastream falls behind and the required WAL segments are removed.

Answer

Switch to a larger Datastream machine type

Answer

Reduce the retention period of the PostgreSQL WAL logs