PCD Practice Test 3 — 30 Questions

Question 1

A company wants to deploy a containerized application to Cloud Run. Which two approaches are supported? (Choose two.)

Accepted Answer

Use gcloud beta run deploy with --source flag to build and deploy from source. Option A is correct because Cloud Run supports source-based deployments via the `gcloud beta run deploy --source` flag, which uses Cloud Build (with buildpacks) to automatically build the container image from source code and deploy it to Cloud Run. Option E is correct because the standard container-based workflow is to build the image locally with Docker, push it to a registry such as Artifact Registry (or Container Registry), and then deploy it using `gcloud run deploy --image` referencing that image. Option B is incorrect because Cloud Functions is a separate serverless product for functions, not a mechanism for packaging and deploying containers to Cloud Run. Option C is incorrect because the Cloud Run console does not accept a Dockerfile for server-side building; builds from source are done via gcloud/Cloud Build, not by uploading a Dockerfile to the console. Option D is incorrect because deploying to Kubernetes Engine (GKE) and then migrating is not a supported Cloud Run deployment approach; Cloud Run deploys containers directly from a registry or source.

Answer

Use Cloud Functions to package the container as a function

Answer

Upload a Dockerfile to Cloud Run console and let it build

Answer

Use Kubernetes Engine to deploy the container and then migrate to Cloud Run

Question 2

A company is deploying a global microservices application on Cloud Run. They need to design for high availability, scalability, and low latency. Which three practices should they implement? (Choose three.)

Accepted Answer

Enable Cloud CDN for caching static assets.. Cloud CDN caches static assets at Google's global edge locations, reducing latency for users worldwide and offloading requests from Cloud Run. This improves performance for static content like images, CSS, and JavaScript, which is essential for a global microservices application requiring low latency.

Answer

Use Cloud Scheduler to trigger services periodically.

Answer

Set a limit on the number of Cloud Run containers per revision to control costs.

Question 3

A company runs a batch job that processes large files from Cloud Storage every night. The job must complete within a 2-hour window. If the job fails, it should retry automatically. Which Google Cloud service should they use to orchestrate this job?

Accepted Answer

Cloud Composer. Cloud Composer (D) is the correct choice because it is a fully managed workflow orchestration service built on Apache Airflow, designed to schedule, monitor, and retry batch jobs with complex dependencies. It can trigger a Cloud Storage file processing job, enforce a 2-hour execution window, and automatically retry on failure using Airflow's built-in retry mechanisms and SLA monitoring.

Answer

Compute Engine with startup script

Answer

Cloud Run

Answer

App Engine Cron

Question 4

A company is designing a real-time leaderboard for a mobile gaming application. The leaderboard must support millions of concurrent users updating their scores and querying rankings with low latency (under 100ms). Scores change frequently and require strong consistency for reads. The development team is evaluating Cloud SQL and Cloud Spanner. They estimate they need to handle 100,000 writes per second. Which database should they choose and why?

Accepted Answer

Cloud Spanner because it provides horizontal scaling, strong consistency, and high write throughput.. Cloud Spanner is the correct choice because it provides horizontal scaling with strong consistency and can handle 100,000 writes per second while maintaining ACID transactions and low-latency reads. Unlike Cloud SQL, Spanner scales horizontally across nodes without sacrificing consistency, making it ideal for a real-time leaderboard with millions of concurrent users.

Answer

Cloud Firestore because it offers real-time synchronization and is serverless.

Answer

Cloud Bigtable because it's optimized for high write throughput and time-series data.

Answer

Cloud SQL with read replicas because it's cost-effective and supports ACID transactions.

Question 5

A developer needs to connect a Cloud SQL MySQL instance from an application running on Compute Engine without whitelisting IP addresses. Which method should they use?

Accepted Answer

Configure the application to use Cloud SQL Auth Proxy.. Cloud SQL Auth Proxy provides secure, IAM-authenticated connectivity to a Cloud SQL instance without requiring authorized networks (IP whitelisting) or manual SSL certificate management. The proxy runs locally (or as a sidecar) and establishes an encrypted tunnel to the instance, so the application connects to localhost and the proxy handles authentication and encryption. This directly satisfies the requirement of connecting without whitelisting IP addresses.

Answer

Connect via Cloud Shell using the mysql client.

Answer

Set up a Cloud SQL private IP connection.

Answer

Use SSL/TLS connection with the public IP address.

Question 6

Match each Firebase feature to its description.

Accepted Answer

Cloud Firestore: A NoSQL document database for storing and syncing data in real time.. Firebase features include Cloud Firestore (NoSQL database), Authentication (user login), and Cloud Functions (backend code). Common confusions: mixing NoSQL vs relational, and hosting vs functions.

Answer

Cloud Firestore: A relational database with SQL queries for structured data.

Answer

Firebase Hosting: A Firebase feature for running backend code in response to events.

Question 7

A company is migrating an on-premises PostgreSQL database to Cloud SQL for PostgreSQL. They need to minimize downtime and ensure continuous replication during the cutover. Which Google Cloud service should they use to achieve continuous change data capture (CDC)?

Accepted Answer

Database Migration Service (DMS). Database Migration Service (DMS) supports continuous change data capture (CDC) for PostgreSQL migrations to Cloud SQL by using PostgreSQL's native logical replication. This allows DMS to replicate ongoing changes from the source to the target with minimal downtime, enabling a near-zero-downtime cutover by simply promoting the Cloud SQL instance as the new primary.

Answer

Cloud Data Fusion

Answer

Dataproc

Answer

Cloud Memorystore

Question 8

A company needs a globally distributed, strongly consistent relational database with horizontal scaling and a 99.999% SLA for a financial application. Which Google Cloud database should they choose?

Accepted Answer

Cloud Spanner. Cloud Spanner is the correct choice because it provides a globally distributed, strongly consistent relational database with horizontal scaling and a 99.999% SLA. It combines the benefits of relational database structure (ACID transactions and SQL queries) with horizontal scalability across regions, making it ideal for financial applications that require strict consistency and high availability.

Answer

Cloud SQL

Answer

Cloud Bigtable

Answer

Firestore

Question 9

Which Google Cloud database service is designed as a fully managed, in-memory data store for caching, session management, and pub/sub messaging?

Accepted Answer

Memorystore. Memorystore is Google Cloud's fully managed in-memory data store service, offering Redis and Memcached engines. It is designed for caching, session management, and pub/sub messaging (Redis supports pub/sub), making it the correct match for the described use case.

Answer

Cloud SQL

Answer

Firestore

Answer

Bigtable

Question 10

Which service provides serverless change data capture (CDC) from MySQL and PostgreSQL to BigQuery or Cloud Storage without writing code?

Accepted Answer

Datastream. Datastream is Google Cloud's serverless change data capture (CDC) service that replicates data from MySQL, PostgreSQL, Oracle, and SQL Server into BigQuery or Cloud Storage with minimal configuration and no code. It reads the source database's transaction logs (binlog for MySQL, WAL for PostgreSQL) and streams changes continuously. This matches the question's requirement exactly.

Answer

BigQuery Data Transfer Service

Answer

Cloud Functions

Answer

Dataflow

Question 11

A team is building a serverless event-driven application using Cloud Functions and Cloud Pub/Sub. The function processes messages from a Pub/Sub subscription and writes results to Firestore. During peak hours, the function experiences high latency and some messages are being retried multiple times. Which three steps should the team take to improve reliability and scalability? (Choose three.)

Accepted Answer

Enable retry policy on the Pub/Sub subscription to automatically retry failed messages.. Enabling a retry policy on the Pub/Sub subscription ensures that messages that fail to be processed (e.g., due to transient errors or timeouts) are automatically retried. This prevents message loss and improves reliability by allowing the Cloud Function to reprocess messages without manual intervention. The retry policy works with the subscription's acknowledgement deadline, so messages are redelivered if not acknowledged in time.

Answer

Batch multiple Pub/Sub messages into a single Cloud Function invocation.

Answer

Increase the Cloud Function timeout to the maximum allowed value.

Question 12

A company deploys a microservices application on Google Kubernetes Engine (GKE). The operations team needs to monitor API latency between services. Which Google Cloud service should they use to trace requests across services?

Accepted Answer

Cloud Trace. Cloud Trace is the correct choice because it is a distributed tracing system designed to capture latency data as requests propagate through microservices. It provides end-to-end visibility by collecting trace spans from each service, allowing the operations team to identify bottlenecks and measure API latency between services in a GKE environment.

Answer

Error Reporting

Answer

Cloud Logging

Answer

Cloud Monitoring

Question 13

A development team is implementing a CI/CD pipeline using Cloud Build. They need to ensure that sensitive data, such as API keys, are never exposed in build logs. What is the best practice?

Accepted Answer

Use Cloud Build's encrypted variables or Secret Manager to pass secrets at build time.. Cloud Build's encrypted variables and Secret Manager are designed to securely inject sensitive data like API keys at build time without exposing them in logs. Encrypted variables are stored in Cloud KMS and decrypted only during the build, while Secret Manager provides versioned secrets with fine-grained access control. This ensures secrets never appear in plaintext in the build configuration or output logs.

Answer

Store the API keys in a separate file in the source repository and reference it in the build.

Answer

Use custom substitutions with default values and rely on Cloud Build's encryption.

Answer

Store the API keys as plain text in cloudbuild.yaml and restrict access to the file.

Question 14

A multinational corporation runs a web application on Google Kubernetes Engine (GKE) with multiple microservices. They use Cloud Service Mesh (Anthos) for observability and security. The application uses gRPC for inter-service communication. Recently, they have observed increased latency and occasional timeouts between services in different regional clusters connected via Cloud VPN. The team wants to diagnose the issue and improve reliability. They suspect network round-trip time (RTT) is causing the latency, but they are not sure if the problem is at the application or network layer. Which tool should they use to pinpoint the exact cause?

Accepted Answer

Use Cloud Trace to analyze distributed traces and identify bottlenecks in request paths.. Cloud Trace is the correct tool because it provides end-to-end distributed tracing, which can capture the exact latency contribution of each gRPC call across microservices and regional clusters. By analyzing trace spans, the team can determine whether the increased latency is due to network round-trip time (RTT) between clusters or due to application-level processing delays within a service.

Answer

Use Cloud Monitoring to view gRPC latency distributions and break down by service and method.

Answer

Use VPC Flow Logs to examine network throughput and packet loss.

Answer

Use Cloud Logging to search for error logs in the application containers.

Question 15

A company uses Cloud Spanner for a globally distributed application. They need to design their table schema for maximum scalability and performance. Which two design considerations are critical? (Choose two.)

Accepted Answer

Use interleaved tables to colocate related data.. Option A is correct because interleaved tables physically colocate child rows with their parent row, so related data is stored on the same node and joins between parent and child can be executed locally without network shuffling, which improves performance and scalability for hierarchical data. Option E is correct because Cloud Spanner shards data by primary key ranges, so choosing keys that spread writes evenly across nodes (for example, using hashed or reversed keys) avoids hotspots and lets the system scale horizontally. Option B is not appropriate because Spanner is optimized for structured relational data and large binary blobs should be stored in Cloud Storage with references in Spanner. Option C is wrong because indexing every column adds write amplification and storage overhead without query benefit. Option D is wrong because monotonically increasing primary keys (such as timestamps or sequential IDs) concentrate writes on the last key range, creating a hotspot that limits scalability.

Answer

Store large binary blobs directly in Spanner.

Answer

Define secondary indexes on every column.

Answer

Use monotonically increasing primary keys.

Question 16

A company is migrating a 5 TB SQL Server database to Cloud SQL for SQL Server using Database Migration Service (DMS). After the full dump phase, the continuous replication (CDC) phase starts. The team notices that the source database transaction log is growing rapidly and the CDC phase is failing intermittently with 'log space' errors. What should they do?

Accepted Answer

Increase the size of the source transaction log and ensure it is not limited. The intermittent 'log space' errors during CDC indicate that the source transaction log is running out of space to record changes for replication. Database Migration Service (DMS) requires sufficient log space to capture ongoing changes; increasing the log size and removing any size limits ensures the log can grow to accommodate the replication lag without failing.

Answer

Reduce the retention period for the source transaction log backups

Answer

Shrink the source transaction log to free up space

Answer

Switch the source database to simple recovery model to reduce logging

Question 17

An e-commerce company relies on a Compute Engine backend serving content to global users. They notice high latency for users outside the primary region. Which service should they add to reduce latency by caching content at edge locations?

Accepted Answer

Cloud CDN. Cloud CDN (Content Delivery Network) uses Google's global edge cache locations to serve cached content closer to users, reducing latency for requests that would otherwise travel to the origin Compute Engine backend in a single region. By caching static or dynamic content at edge nodes, Cloud CDN minimizes round-trip time and offloads traffic from the backend instance.

Answer

Cloud Armor

Answer

Cloud NAT

Answer

Cloud Endpoints

Answer

Cloud Load Balancing

Question 18

A startup is migrating an on-premises PostgreSQL 14 database to Cloud SQL. The database is 500 GB and handles OLTP workloads. They want to minimize downtime during migration. Which approach should they use?

Accepted Answer

Use Database Migration Service (DMS) with continuous replication. Database Migration Service (DMS) supports continuous replication from source PostgreSQL to Cloud SQL, allowing near-zero downtime. Export/import requires downtime. Replica promotion is not a migration method.

Answer

Export the database using pg_dump and import using psql

Answer

Create a Cloud SQL read replica from the on-premises database

Answer

Use gcloud sql import to directly import from a dump file

Question 19

Match each Cloud Logging and Monitoring concept to its definition.

Accepted Answer

Cloud Logging: Collects and stores log data from applications and services.. Correct matches: Cloud Logging handles log data, Cloud Monitoring provides performance insights, Log-based Metrics turn logs into metrics, Error Reporting aggregates errors. Common confusions include swapping Cloud Logging and Cloud Monitoring definitions.

Answer

Cloud Monitoring: Collects and stores log data from applications and services.

Answer

Error Reporting: Provides visibility into the performance, uptime, and health of cloud applications.

Question 20

A data engineering team needs to replicate data from a PostgreSQL database to BigQuery in near real-time for analytics. Which Google Cloud service is most suitable for this task with minimal setup?

Accepted Answer

Datastream. Datastream is a serverless CDC replication service specifically designed for replicating from sources like PostgreSQL, MySQL, and Oracle to BigQuery, Cloud Storage, or Pub/Sub. It handles schema mapping and initial backfill.

Answer

Cloud SQL for PostgreSQL

Answer

Cloud Data Fusion

Answer

Cloud Composer