PCD Practice Test 30 — 15 Questions

Question 1

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.. Option C is correct because 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 2

A company wants to deploy a stateless web application that needs to handle unpredictable traffic spikes with minimal operational overhead. Which Google Cloud compute service is most cost-effective and operationally simple?

Accepted Answer

Cloud Run. Cloud Run is the most cost-effective and operationally simple choice for a stateless web application with unpredictable traffic spikes because it automatically scales from zero to thousands of containers based on request load, charges only for resources used during request processing (down to 100ms increments), and eliminates infrastructure management. It supports any language or framework via container images, making it ideal for stateless HTTP workloads without the cold-start latency concerns of Cloud Functions or the cluster management overhead of GKE.

Answer

App Engine Standard

Answer

Cloud Functions

Answer

Google Kubernetes Engine (GKE)

Answer

Compute Engine with Managed Instance Group

Question 3

A company runs a microservices architecture on GKE with gRPC services. They want to implement traffic splitting for canary deployments. Which THREE components should they use?

Accepted Answer

Istio or Anthos Service Mesh. Option B is correct because Istio or Anthos Service Mesh provides fine-grained traffic splitting capabilities for canary deployments in a GKE environment. It uses Envoy sidecar proxies to route a percentage of traffic to different service versions based on HTTP headers or weight, enabling controlled rollouts without modifying application code.

Answer

ClusterIP service

Answer

Headless service

Question 4

A company is migrating a stateful application to Google Cloud. They need high availability with automatic failover across zones within a region. Which compute option should they choose?

Accepted Answer

Google Kubernetes Engine with Regional Persistent Disk. Google Kubernetes Engine (GKE) with Regional Persistent Disk is the correct choice because it provides synchronous replication of data across multiple zones within a region, enabling automatic failover for stateful applications. When a pod or node fails in one zone, the Regional Persistent Disk can be immediately attached to a pod in another zone, ensuring high availability without data loss. This meets the requirement for stateful workloads that need zone-level resilience.

Answer

App Engine Standard Environment

Answer

Cloud Run

Answer

Compute Engine with standard persistent disk

Question 5

An organization runs a critical application on Compute Engine with a regional managed instance group. They want to achieve 99.99% availability. Which architecture should they use?

Accepted Answer

Regional MIG with instances in three zones. To achieve 99.99% availability, the architecture must tolerate both a zonal failure and a single instance failure. A regional managed instance group (MIG) with instances in three zones ensures that even if one zone becomes unavailable, the remaining two zones can still serve traffic, meeting the 99.99% uptime target. Three zones provide the necessary redundancy because a two-zone regional MIG can only survive a single zone failure but not a simultaneous instance failure in the remaining zone, whereas three zones allow for a rolling update or failure of one zone while still maintaining quorum.

Answer

Regional MIG with instances in two zones

Answer

Single zone MIG with multiple instances

Answer

Multi-region deployment with global load balancer

Question 6

A company runs a critical application on Compute Engine with a stateful database. They need to achieve 99.99% availability for the database tier. Which architecture should they implement?

Accepted Answer

A Compute Engine instance group with managed instance groups and a regional persistent disk configured for synchronous replication.. Option A is correct because a managed instance group with a regional persistent disk configured for synchronous replication provides the necessary 99.99% availability by ensuring the database runs across two zones with synchronous writes to both replicas. This architecture allows automatic failover within seconds if one zone fails, meeting the high-availability requirement without data loss.

Answer

Use Cloud SQL with automatic failover and read replicas.

Answer

Two Compute Engine instances in different zones with a shared Zonal persistent disk.

Answer

Single Compute Engine instance with a persistent disk snapshot scheduled every hour.

Question 7

A Cloud Function (background function, event-driven) consistently logs this timeout error. The function processes messages from Pub/Sub. After increasing the max instances from 10 to 100, the error rate increases. What is the most likely cause of the timeouts?

Accepted Answer

The function depends on an external service that is rate-limited; scaling up causes more calls and timeouts. Option A is correct because increasing the max instances from 10 to 100 amplifies the number of concurrent function invocations. If the function depends on an external service (e.g., a third-party API or database) that enforces rate limits, the higher concurrency causes more requests to be throttled or rejected, leading to increased timeouts. This is a classic scaling anti-pattern where horizontal scaling exacerbates a bottleneck instead of relieving it.

Answer

Increase memory allocation to speed up processing

Answer

Use a larger instance type (Cloud Functions does not have instance types)

Answer

Migrate the function to Cloud Run for longer timeouts

Answer

The function timeout is set too low; increase it to 9 minutes

Question 8

A stateful service on GKE needs to persist data that must be accessible from any pod in the cluster, regardless of which node the pod runs on. Which volume type should they use?

Accepted Answer

PersistentVolumeClaim with RWX access mode. A PersistentVolumeClaim (PVC) with RWX (ReadWriteMany) access mode is correct because it allows multiple pods across different nodes to read and write to the same persistent volume simultaneously. This is essential for a stateful service where data must be accessible from any pod in the cluster, regardless of which node the pod runs on. RWX is typically backed by network filesystems like NFS or GKE Filestore, which provide shared access across nodes.

Answer

emptyDir

Answer

ConfigMap

Answer

hostPath

Question 9

A startup expects low and predictable traffic initially but wants to use containers with minimal operational overhead. Which compute service should they choose?

Accepted Answer

Cloud Run. Cloud Run is the correct choice because it runs containers in a fully managed, serverless environment that automatically scales from zero, requires no cluster management, and charges only for resources used during request processing. This matches the startup's need for minimal operational overhead and low, predictable traffic, as Cloud Run abstracts away infrastructure management entirely.

Answer

App Engine Flexible Environment

Answer

Google Kubernetes Engine (GKE)

Answer

Compute Engine

Answer

Cloud Functions

Question 10

An application uses Cloud SQL for read-heavy workloads. To scale reads, which configuration is best?

Accepted Answer

Add read replicas across zones. Read replicas in Cloud SQL allow you to offload read traffic from the primary instance to one or more replica instances, which are kept in sync using asynchronous replication. This configuration directly scales read capacity by distributing SELECT queries across replicas, making it the best choice for read-heavy workloads.

Answer

Use connection pooling

Answer

Enable high availability with standby

Answer

Enable automatic storage increase

Question 11

A media streaming company uses Cloud Storage to store video files. Users upload files through a web application, and the files are streamed directly from Cloud Storage. They want to reduce latency for users in different regions. Which configuration should they apply?

Accepted Answer

Set up Cloud CDN with the Cloud Storage bucket as origin.. Cloud CDN caches video content at edge locations worldwide, reducing latency for users by serving content from the nearest edge cache instead of the origin Cloud Storage bucket. This directly addresses the requirement to reduce latency for users in different regions without modifying the storage architecture.

Answer

Enable Object Lifecycle Management to move objects to Nearline storage.

Answer

Configure Cloud Storage transfer service to replicate data to multiple buckets.

Answer

Use a multi-region Cloud Storage bucket and enable requester-pays.

Question 12

A company is designing a scalable web application on Google Cloud. They expect variable traffic and want to automatically scale resources based on load. Which two services can automatically scale? (Choose two.)

Accepted Answer

Cloud Run. Cloud Run is a fully managed serverless compute platform that automatically scales your containerized applications based on incoming traffic, including scaling to zero when there is no traffic. This autoscaling is handled by the Knative serving layer, which adjusts the number of container instances based on request concurrency and CPU utilization.

Answer

Compute Engine unmanaged instance group

Answer

Cloud Dataproc

Answer

Cloud SQL

Question 13

A developer deploys this Cloud Run service. During a load test, each incoming request starts a new container instance, even though concurrency is set to 80. What is the reason?

Accepted Answer

The container is not designed to handle multiple concurrent requests (single-threaded). Option E is correct because Cloud Run's concurrency setting controls how many requests the runtime can send to a container instance, but the container itself must be capable of handling those requests concurrently. If the application is single-threaded or uses a blocking I/O model (e.g., a simple Flask or Express server without async workers), it can only process one request at a time. Cloud Run detects that the container is busy and starts a new instance for each incoming request, effectively ignoring the concurrency setting.

Answer

The memory limit is too low

Answer

The container is CPU-bound and cannot handle multiple requests concurrently

Answer

The CPU limit is too low

Answer

The concurrency setting of 80 is too high and Cloud Run ignores it

Question 14

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. Option A is correct because 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 15

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