PCD Practice Test 25 — 15 Questions

Question 1

A gaming company uses Cloud Spanner for its global leaderboard. The leaderboard is updated frequently by millions of users. They notice that write latency spikes during peak hours due to hotspotting on the leaderboard table. Which schema change would best mitigate this?

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

Accepted Answer

Prefix the primary key with a server ID or hash of the user ID. Prefixing the primary key with a server ID or hash of the user ID distributes writes across multiple splits, eliminating the hotspot caused by monotonically increasing or highly concentrated key ranges. Cloud Spanner shards data by primary key ranges, so a well-distributed key prefix spreads write load across nodes. This directly mitigates the hotspotting that causes write latency spikes during peak hours.

Answer

Use UUID as the primary key

Answer

Add a secondary index on the rank column

Answer

Enable leaderboard caching with Memorystore

Question 2

You are building a data pipeline using Cloud Dataflow (Apache Beam). The pipeline reads from Pub/Sub, performs aggregations, and writes to BigQuery. Occasionally, you see duplicates in the BigQuery output, even though the pipeline uses .withInsertId() in the BigQuery write transform. What could be causing these duplicates?

Accepted Answer

The pipeline is using at-least-once mode and bundles are being retried, but the insertId is not being reused across retry attempts. Cloud Dataflow (Apache Beam) operates in at-least-once mode by default, meaning bundles may be retried during processing. When a bundle is retried, the insertId set via .withInsertId() must be reused across retry attempts to enable BigQuery's deduplication. If the insertId is not reused (e.g., because it's generated per attempt or not properly propagated), BigQuery treats each write as a separate row, resulting in duplicates.

Answer

You are not using the exactly-once sink option for BigQuery

Answer

You have set .withOutputParallelization() to false

Answer

You need to enable Dataflow's built-in deduplication using the .withIdAttribute() in Pub/Sub read

Question 3

You are troubleshooting a web application deployed on Compute Engine instances behind a target pool. Users report intermittent timeouts when accessing the application via the forwarding rule's IP address. Based on the exhibit, what is the most likely cause of the issue?

Accepted Answer

The target pool lacks health checks, causing traffic to be sent to unhealthy instances.. The target pool in a legacy HTTP(S) load balancer does not automatically perform health checks unless they are explicitly configured. Without health checks, the load balancer continues to send traffic to all instances in the pool, including those that are unhealthy or unresponsive. This causes intermittent timeouts when users hit an unhealthy instance, as the forwarding rule distributes connections across the entire pool without verifying instance health.

Answer

The forwarding rule is missing a backend service.

Answer

The port range is set to 80-80, which restricts traffic to port 80 only.

Answer

The forwarding rule should use a backend service instead of a target pool for HTTP traffic.

Question 4

A team is developing a REST API on Cloud Run. They need to ensure that only authenticated requests from their corporate domain (example.com) are allowed. Which configuration should they use?

Accepted Answer

Set the Cloud Run service to require authentication and allow only the domain 'example.com' in the IAM policy. Cloud Run's IAM integration allows you to require authentication (via the `--no-allow-unauthenticated` flag) and then use IAM conditions to restrict access to principals from a specific domain (e.g., `request.auth.claims.email` ends with `@example.com`). This ensures only authenticated requests from the corporate domain are permitted, leveraging Google Cloud's identity-aware proxy (IAP) capabilities without additional infrastructure.

Answer

Implement custom authentication using Firestore to validate user tokens

Answer

Use Cloud Endpoints with an API key that is shared only with corporate users

Answer

Use Cloud Armor to deny traffic except from the corporate IP range

Question 5

Which Google Cloud database service is serverless, supports mobile and web apps with offline data synchronization, and provides document-level security rules?

Accepted Answer

Firestore. Firestore is a serverless, NoSQL document database that automatically scales, supports mobile and web clients with offline data persistence and synchronization via its SDKs, and enforces document-level security rules through Firebase Security Rules. This combination of serverless scaling, offline sync, and granular security makes it the correct choice for the described requirements.

Answer

Memorystore

Answer

Cloud Bigtable

Answer

Cloud Spanner

Question 6

A web application uses Cloud SQL for MySQL. The team expects a sudden spike in read-only traffic from a reporting tool. What should they use to offload read queries?

Accepted Answer

Read replicas. Read replicas in Cloud SQL for MySQL allow you to offload read traffic from the primary instance by creating one or more read-only copies. This is the correct approach for handling a sudden spike in read-only queries from a reporting tool, as it distributes the load without affecting write performance or requiring application changes beyond updating the connection string.

Answer

Automatic storage increase

Answer

Cross-region replication

Answer

Failover replica

Question 7

A company wants to perform cross-cloud analytics, querying data stored in both Google Cloud BigQuery and Amazon S3. Which BigQuery feature enables this?

Accepted Answer

BigQuery Omni. BigQuery Omni allows querying data across clouds (AWS and Azure) using BigQuery, without moving data.

Answer

Cloud Data Fusion

Answer

BigQuery Data Transfer Service

Answer

BigQuery federated queries

Question 8

A developer is writing unit tests for a Python Cloud Run service that uses Cloud Firestore. They want to avoid hitting the real Firestore during tests. What should they use?

Accepted Answer

Mock the Firestore client using a library like unittest.mock.. Unit tests should isolate the code under test from external dependencies. Using `unittest.mock` to mock the Firestore client allows the developer to simulate Firestore calls and return controlled responses without any network I/O, ensuring tests are fast, deterministic, and independent of the real Firestore service.

Answer

Use a real Firestore database but with a test project.

Answer

Disable network access during tests.

Answer

Use the Firestore emulator for unit tests.

Question 9

A company is using Cloud Bigtable for a time-series application. They need to ensure that if one zone fails, the database remains available for reads and writes with minimal downtime. Which configuration should they use?

Accepted Answer

Add a secondary cluster in a different zone within the same region. Adding a secondary cluster in a different zone within the same region provides replication and automatic failover for both reads and writes.

Answer

Enable auto-scaling on the cluster

Answer

Use a development instance type

Answer

Use a single-cluster instance with SSD storage

Question 10

An application running on Cloud Run experiences cold starts causing latency spikes. What is the most cost-effective solution to reduce cold starts?

Accepted Answer

Set a minimum number of instances. Setting a minimum number of instances ensures that Cloud Run always keeps at least one instance warm (idle) to serve incoming requests instantly, eliminating cold start latency. This is the most cost-effective solution because you only pay for the minimum instances when they are idle (at a reduced rate), whereas other options increase per-request cost or do not address the root cause of cold starts.

Answer

Increase the container's CPU allocation

Answer

Enable HTTP keep-alive connections

Answer

Use a larger container memory size

Question 11

A team is migrating a legacy application database to Cloud SQL. They want to implement versioned schema changes as part of their CI/CD pipeline. Which tool should they use?

Accepted Answer

Liquibase. Liquibase is a dedicated database schema change management tool that tracks versioned changesets (changelogs) and integrates natively with CI/CD pipelines to apply ordered, idempotent migrations across environments. It supports Cloud SQL (MySQL, PostgreSQL, SQL Server) and provides rollback, diff, and audit capabilities that a raw import command cannot. This makes it the correct choice for implementing versioned schema changes as part of a CI/CD workflow.

Answer

gcloud sql import

Answer

Cloud Deployment Manager

Answer

Cloud Build

Question 12

Your Bigtable cluster is experiencing high latency for a table that stores IoT sensor data. The row key format is deviceID#timestamp. You discover that most reads query the last hour of data for a few devices. How can you optimize row key design to improve read performance?

Accepted Answer

Reverse the timestamp in the row key (e.g., deviceID#MAXTIME - timestamp). Reversing the timestamp (e.g., deviceID#MAXTIME - timestamp) ensures that for a given deviceID, the most recent data appears first in the lexicographic order of row keys. This allows reads querying the last hour of data to perform a contiguous range scan on a small set of rows, reducing read latency. It does not improve write distribution (all rows for a device still hash to the same tablet), but the read performance benefit is significant for this workload.

Answer

Separate frequently accessed data into a different column family

Answer

Use a single table with a composite key including device type

Answer

Add a salt prefix to the row key

Question 13

You are designing a global user-facing application that requires strong consistency, horizontal scalability, and 99.999% availability across multiple continents. Which database service should you choose?

Accepted Answer

Cloud Spanner. Cloud Spanner is the only Google Cloud database service that provides strong consistency, horizontal scalability, and 99.999% availability across multiple continents. It uses synchronous replication and the TrueTime API to deliver external consistency across globally distributed nodes, making it ideal for global user-facing applications that require ACID transactions at scale.

Answer

Cloud SQL

Answer

Firestore

Answer

Bigtable

Question 14

An organization wants to create custom metrics based on application logs to track business KPIs. They need to ensure these metrics are available for alerting within minutes. Which approach should they use?

Accepted Answer

Write logs to Cloud Logging and use log-based metrics. Log-based metrics in Cloud Logging allow you to define custom metrics from log entries using filters or regular expressions. These metrics are ingested and available for alerting within minutes because they are processed in near real-time by the Cloud Monitoring backend, without requiring external data pipelines or custom code.

Answer

Export logs to BigQuery and use scheduled queries

Answer

Use OpenTelemetry collector to send metrics directly

Answer

Use Cloud Functions to parse logs and push custom metrics via API

Question 15

A company runs a stateful microservice that requires read-after-write consistency but can tolerate some latency for writes. They are currently using a single Cloud SQL instance and want to scale read traffic. Which approach should they take?

Accepted Answer

Enable Cloud SQL read replicas. Cloud SQL read replicas are the correct choice because they provide an asynchronous read-only copy of the primary instance, which can scale read traffic without compromising the read-after-write consistency required by the stateful microservice. The primary instance handles all writes, ensuring strong consistency for writes, while replicas serve stale reads that eventually become consistent, which aligns with the tolerance for write latency.

Answer

Use Cloud Memorystore to cache reads

Answer

Shard the database manually

Answer

Use Cloud Bigtable

Answer

Migrate to Cloud Spanner