PCD Practice Test 42 — 15 Questions

Question 1

Based on the Cloud Trace exhibit, which service is the primary contributor to the overall request latency?

Accepted Answer

The auth service. The Cloud Trace exhibit shows that the auth service accounts for the largest segment of the overall request latency, as indicated by the longest span duration in the trace waterfall. In Google Cloud Trace, each span represents a service's contribution to the total latency, and the service with the highest cumulative span time is the primary contributor. Since the auth service span is the longest, it is the correct answer.

Answer

The productcatalog service

Answer

The frontend service itself

Answer

The recommendations service

Question 2

A financial services company uses Cloud Spanner for transactional data. They need to perform complex analytical queries that aggregate large volumes of data without affecting the performance of transaction processing. Which approach should they take?

Accepted Answer

Export data from Spanner to BigQuery periodically and run analytic queries there.. BigQuery is a serverless, highly scalable data warehouse designed for complex analytical queries on large datasets. By exporting Spanner transactional data to BigQuery, the company can run heavy aggregations without impacting Spanner's OLTP performance, as Spanner is optimized for high-throughput, low-latency transactions, not analytical workloads.

Answer

Use Spanner's read-only transactions to run analytic queries.

Answer

Enable Cloud Spanner's query optimizer for analytical workloads.

Answer

Create secondary indexes on the Spanner tables to speed up analytical queries.

Question 3

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 4

A developer deployed the above Cloud Run service YAML. The service deploys successfully but any request fails with a 503 error. What is the most likely cause?

Accepted Answer

The container is not listening on the expected port.. A 503 error from Cloud Run indicates that the service is failing to respond to health checks or requests. The most common cause is that the container is not listening on the port specified in the `containerPort` field of the YAML (default 8080). Cloud Run sends requests to that port, and if the application is bound to a different port (e.g., 3000 or 80), the request never reaches the application, resulting in a 503.

Answer

The service has no ingress setting.

Answer

The container image has a different entrypoint.

Answer

containerConcurrency is set too high.

Question 5

Which three are valid ways to authenticate a service account when using the Google Cloud client libraries? (Choose three.)

Accepted Answer

Attaching a service account to a Compute Engine instance and letting the metadata server provide credentials.. Options A, B, and D are correct. These are standard methods for Application Default Credentials (ADC). Attaching a service account to a Compute Engine instance allows the metadata server to provide credentials (A). Setting the GOOGLE_APPLICATION_CREDENTIALS environment variable to point to a service account key file is another valid method (B). Using the gcloud CLI default application credentials is also a valid approach (D). Option C is incorrect because OAuth 2.0 client IDs for web applications are used for user authentication, not service account authentication. Option E is incorrect because API keys are not used for service account authentication; they are used for simple API access without a service account.

Answer

Using OAuth 2.0 client IDs for web applications.

Answer

Using an API key in the client library initialization.

Question 6

A company uses Cloud Functions to process events from Pub/Sub. They notice that occasionally the same message is processed more than once. What can they do to ensure idempotent processing?

Accepted Answer

Make the function idempotent using a deduplication field. Making the function idempotent using a deduplication field ensures that even if the same Pub/Sub message is delivered more than once (Pub/Sub offers at-least-once delivery), the function processes it only once. By checking a unique message ID or a custom deduplication key before processing, the function can skip or safely reapply the operation, preventing duplicate side effects.

Answer

Configure retry policies to only retry once

Answer

Use Cloud Tasks instead

Answer

Use Cloud Scheduler

Answer

Increase the acknowledgement deadline for the subscription

Question 7

A company is migrating an on-premises MySQL 8.0 OLTP application to Google Cloud. The application requires high availability with automatic failover and zero RPO. Which Google Cloud database and configuration should they use?

Accepted Answer

Cloud SQL for MySQL with HA configuration. Cloud SQL for MySQL with HA configuration provides synchronous replication to a standby instance in the same region, automatic failover, and zero RPO.

Answer

Cloud Spanner with multi-region configuration

Answer

Cloud SQL for MySQL with read replicas

Answer

AlloyDB for PostgreSQL with HA

Question 8

A team deploys a containerized web application on Google Kubernetes Engine (GKE) using a Deployment. They need to expose the application externally via a stable IP address and enable SSL termination. Which resource should they use?

Accepted Answer

Ingress with Google-managed SSL certificate. An Ingress with a Google-managed SSL certificate is the correct choice because it provides a single stable IP address via a global forwarding rule, terminates SSL at the Google Cloud HTTP(S) load balancer, and routes traffic to the GKE Deployment. This approach offloads SSL decryption from the application pods and uses a managed certificate that auto-renews, meeting both the stable IP and SSL termination requirements.

Answer

HorizontalPodAutoscaler

Answer

Service type NodePort

Answer

Service type LoadBalancer

Question 9

Which TWO actions should a developer take to ensure that a Cloud Run service can access a Cloud SQL instance securely?

Accepted Answer

Use the Cloud SQL Auth Proxy as a sidecar container in the same pod.. The Cloud SQL Auth Proxy, when deployed as a sidecar container in the same pod, provides encrypted connections and IAM-based authentication to Cloud SQL without requiring a public IP or complex network configuration. It automatically handles TLS 1.3 encryption and uses the service account's IAM permissions to authorize connections, ensuring secure access from Cloud Run.

Answer

Use a Cloud NAT to provide outbound internet access for the service.

Answer

Assign a public IP to the Cloud SQL instance and allow all traffic from Cloud Run.

Answer

Create a service account with the cloudsql.instances.connect permission.

Question 10

During a rolling update, the new pods are failing to start because they require more memory than available on nodes. What is the most likely cause?

Accepted Answer

The resource requests and limits are misconfigured.. The most likely cause of pods failing to start due to insufficient memory is misconfigured resource requests and limits. If the memory request (spec.containers[].resources.requests.memory) is set too high, the scheduler cannot find a node with enough allocatable memory, leaving pods in a Pending state. Similarly, if the limit is set too low, the pod may be OOMKilled after starting, but the question specifically states 'failing to start,' pointing to a scheduling failure due to requests exceeding node capacity.

Answer

The maxSurge value is too low.

Answer

The replicas count is too high.

Answer

The strategy type is wrong.

Question 11

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.

Answer

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

Answer

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

Answer

The memory is insufficient for the concurrency level

Question 12

A company wants to replicate data from an on-premises Oracle database to BigQuery for analytics. They need serverless, near-real-time CDC with minimal operational overhead. Which service should they use?

Accepted Answer

Datastream. Datastream is a serverless, fully managed change data capture (CDC) and replication service that streams data from Oracle (and other sources) into BigQuery with near-real-time latency. It uses log-based CDC (Oracle Redo Logs) to capture changes without impacting source performance, and it handles schema mapping and data transformation automatically, minimizing operational overhead.

Answer

Cloud Data Fusion with Oracle plugin

Answer

Cloud Composer with scheduled jobs

Answer

Dataflow with a Java transformation

Question 13

A company has an application using Cloud SQL MySQL and wants to add a caching layer. They also need the cache to persist data across restarts. Which Memorystore tier should they choose?

Accepted Answer

Memorystore for Redis Standard tier. Memorystore for Redis Standard tier is the correct choice because it provides replication (a replica node) and automatic failover, which enables data persistence across restarts. Unlike the Basic tier, which is a single node with no persistence guarantees, the Standard tier uses append-only file (AOF) persistence to ensure data survives node restarts. This meets the requirement for a caching layer that persists data across restarts.

Answer

Memorystore for Redis Basic tier

Answer

Memorystore for Memcached

Answer

Cloud Bigtable

Question 14

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 15

Refer to the exhibit. The Cloud Run service is experiencing high tail latency under moderate load. Which change would most effectively reduce latency?

Accepted Answer

Reduce containerConcurrency to 10.. High tail latency under moderate load often indicates that requests are queuing behind each other due to excessive concurrency. Reducing `containerConcurrency` to 10 limits the number of simultaneous requests each container instance handles, which reduces queueing delay and improves per-request response time. This is the most effective change because it directly controls the request multiplexing level, preventing a single instance from being overwhelmed.

Answer

Increase CPU limit to 2.

Answer

Increase containerConcurrency to 250.

Answer

Increase timeoutSeconds to 600.