PCD Practice Test 2 — 25 Questions

Question 1

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?

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

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 2

A company needs to perform complex transformations and join data from Cloud SQL, Cloud Storage, and Pub/Sub to load into BigQuery. Which Google Cloud service is designed for this ETL/ELT workload?

Accepted Answer

Dataflow

Answer

Cloud Functions

Answer

Cloud Run

Answer

Dataproc

Question 3

A company runs an e-commerce application with a relational database (PostgreSQL) for orders and inventory. They need to store clickstream data for real-time personalization, with a flexible schema and sub-second read latency. Which database best suits the clickstream workload?

Accepted Answer

Firestore

Answer

BigQuery

Answer

Cloud Spanner

Answer

Cloud Bigtable

Question 4

A company runs a microservices application on Google Kubernetes Engine. They use Cloud SQL for persistent data. Recently, during a traffic spike, the application experienced increased latency and some requests failed with timeout errors. The team observed that the Cloud SQL CPU utilization spiked to 100%, and the GKE pods had high memory usage. They are using a standard Cloud SQL tier (db-n1-standard-2). Which course of action would best improve the application's performance and reliability?

Accepted Answer

Implement caching with Memorystore for frequently accessed data.. The primary bottleneck is the Cloud SQL CPU spiking to 100% under heavy read traffic. Implementing Memorystore (Redis) caching offloads repeated read queries from the database, reducing CPU load and query latency. This directly addresses the root cause—database CPU exhaustion—without requiring a larger database instance or adding replicas that would still be limited by the same CPU.

Answer

Upgrade Cloud SQL to a higher tier with more CPU.

Answer

Increase the number of replicas in GKE to reduce load per pod.

Answer

Add read replicas to Cloud SQL.

Question 5

Refer to the exhibit. The Cloud Build fails with an error that the image name is invalid. What is the most likely cause?

Accepted Answer

The substitution variable $MY_PROJECT is not a valid substitution because it is not prefixed with underscore.. In Cloud Build, user-defined substitution variables must be prefixed with an underscore. The variable `$MY_PROJECT` lacks the required underscore prefix, making it invalid. This causes the image name to be malformed, leading to the 'invalid image name' error.

Answer

The push step should be after the deploy step.

Answer

The Docker build step fails because the Dockerfile is missing.

Answer

The image name contains uppercase letters that are not allowed.

Question 6

An engineer is designing a Cloud Spanner schema for a social media application. The Users table and the Posts table have a parent-child relationship. To optimize read performance for fetching all posts of a user, which schema design approach should be used?

Accepted Answer

Use interleaved tables with Users as parent and Posts as child. Interleaved tables store child rows (Posts) with their parent row (User) in the same split, enabling locality and faster joins. Global or local indexes are separate structures.

Answer

Denormalize by storing post data as a repeated field in Users table

Answer

Use a local secondary index on user_id in the Posts table

Answer

Create a global secondary index on user_id in the Posts table

Question 7

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 8

A company wants to deploy a non-relational database for a real-time bidding application that requires low latency (under 10ms) and high throughput (millions of requests per second). The data model is key-value with a timestamp component. Which Google Cloud database is most appropriate?

Accepted Answer

Cloud Bigtable. Cloud Bigtable is designed for high-throughput, low-latency key-value workloads with time-series data, such as real-time bidding.

Answer

Cloud Spanner

Answer

Firestore

Answer

Cloud SQL

Question 9

An organization wants to design a serverless data processing pipeline that is highly available and can automatically scale based on the number of incoming requests. The pipeline processes JSON messages from a Cloud Pub/Sub topic and writes results to BigQuery. Which service should be used as the compute component?

Accepted Answer

Cloud Run. Cloud Run is the correct compute component because it is a fully managed serverless platform that automatically scales from zero based on incoming HTTP requests, supports event-driven processing via Pub/Sub push subscriptions, and integrates natively with BigQuery. It provides high availability by default across zones and can handle burst traffic without provisioning overhead, making it ideal for a serverless pipeline that processes JSON messages and writes results to BigQuery.

Answer

Cloud Dataflow

Answer

Cloud Functions

Answer

Compute Engine with managed instance groups

Question 10

You are designing a serverless application using Cloud Functions that processes events from Cloud Storage and Cloud Pub/Sub. The function must be idempotent and handle duplicate events. Which three best practices should you implement? (Choose THREE.)

Accepted Answer

Generate a unique idempotency key for each event and store processed keys in a database.. Generating a unique idempotency key for each event and storing processed keys in a database (such as Cloud Firestore) ensures that if the same event is delivered multiple times (e.g., due to at-least-once delivery semantics in Cloud Pub/Sub or Cloud Storage notifications), the function can check the key before processing and skip duplicates. This pattern is essential for idempotent serverless functions, as Cloud Functions may be retried on failure or receive duplicate events from the source.

Answer

Invoke the function synchronously to avoid duplicates.

Answer

Set the function timeout to maximum (540 seconds) to ensure processing completes.

Question 11

An application running on GKE uses a custom metric to track order processing time. The metric is exported via Prometheus and ingested by Cloud Monitoring using the Managed Service for Prometheus. The team wants to create an alert when the 95th percentile latency exceeds 2 seconds over a 5-minute window. Which PromQL query should be used?

Accepted Answer

histogram_quantile(0.95, rate(order_processing_duration_seconds_bucket[5m])). `histogram_quantile(0.95, rate(order_processing_duration_seconds_bucket[5m]))` computes the 95th percentile latency over a 5-minute window using Prometheus histogram buckets. The `rate()` function calculates the per-second increase of each bucket, which is required for accurate quantile estimation from cumulative histograms, and the result directly gives the latency threshold below which 95% of requests fall.

Answer

avg(rate(order_processing_duration_seconds_sum[5m])) / avg(rate(order_processing_duration_seconds_count[5m]))

Answer

histogram_quantile(0.95, sum(rate(order_processing_duration_seconds_bucket[5m])))

Answer

histogram_quantile(0.95, order_processing_duration_seconds_bucket)

Question 12

An organization has Cloud Bigtable for real-time ad serving and BigQuery for analytics. They want to synchronize data changes from Bigtable to BigQuery every hour with a Dataflow pipeline. However, they notice that some updates are missed. What is the most likely cause?

Accepted Answer

Bigtable does not support change data capture natively. Bigtable does not have built-in change data capture (CDC) like some databases. Dataflow can read Bigtable snapshots but not incremental changes unless using Dataflow's streaming insert, which is not native. The common approach is to use Bigtable replication or export, but missed updates often occur because Bigtable does not log changes. A custom solution using Cloud Bigtable change streams (beta) or using a separate logging table is needed.

Answer

The Dataflow pipeline reads from Bigtable using a snapshot read

Answer

The Bigtable table has no primary key

Answer

The Dataflow pipeline is using the wrong sink

Question 13

A developer is designing a chat application using Cloud Firestore. They need to ensure that updates to messages are propagated to all clients in real-time. Which feature should they use?

Accepted Answer

Real-time listeners. Real-time listeners (onSnapshot) in Cloud Firestore allow clients to subscribe to document or query changes, receiving updates immediately when data is modified. This ensures all connected clients see message updates in real-time without polling, which is essential for a chat application.

Answer

Firestore indexes

Answer

Security rules

Answer

Offline persistence

Question 14

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?

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 15

A company plans to migrate an on-premises Oracle database to Cloud SQL for PostgreSQL. They need to minimize downtime and ensure continuous sync during migration. Which migration approach should they use?

Accepted Answer

Use DMS with a continuous migration job, allowing CDC replication until cutover.. Database Migration Service (DMS) with a continuous migration job enables ongoing Change Data Capture (CDC) replication from the source Oracle database to Cloud SQL for PostgreSQL. This approach keeps the target database synchronized with minimal downtime, allowing a controlled cutover when the migration is complete. It is the only option that satisfies the requirements of continuous sync and minimal downtime.

Answer

Export the Oracle database as a dump file and import it into Cloud SQL manually.

Answer

Use DMS with a one-time migration job, then manually sync changes before cutover.

Answer

Use Cloud SQL Auth Proxy to connect Oracle to Cloud SQL and replicate data using a custom script.

Question 16

You need to select a Google Cloud database for a global e-commerce platform that requires strong consistency for inventory updates, but can tolerate eventual consistency for product reviews. Which THREE services would you consider appropriate for the different parts of the platform?

Accepted Answer

Bigtable for real-time user behavior tracking. Bigtable is correct for real-time user behavior tracking as it is a fully managed, scalable NoSQL database designed for high-throughput, low-latency workloads, providing strong consistency for single-row operations. Firestore is suitable for product reviews because it supports eventual consistency for multi-region queries, meeting the tolerance requirement, while offering strong consistency within a single region. Cloud Spanner is ideal for inventory data because it provides global strong consistency and ACID transactions, crucial for inventory accuracy across regions.

Answer

BigQuery for storing product reviews

Answer

Cloud SQL for inventory

Question 17

Refer to the exhibit. A developer runs the above command to deploy a Cloud Function triggered by Pub/Sub. The function fails to execute when a message is published. The logs show: "Function execution took 60001 ms, finished with status: 'timeout'". What should the developer do?

Accepted Answer

Check the function code for long-running operations. The timeout error indicates the Cloud Function is exceeding its maximum execution duration. The default timeout for Cloud Functions is 60 seconds, and the logs confirm the function ran for 60001 ms before being forcibly terminated. The most likely cause is that the function code contains long-running operations (e.g., synchronous HTTP calls, database queries, or heavy computation) that do not complete within the allotted time. Therefore, the developer should inspect and optimize the function code to reduce execution time, such as by using asynchronous processing or breaking the work into smaller chunks.

Answer

Change the trigger to HTTP

Answer

Reduce the number of function instances

Answer

Increase the function timeout to 9 minutes

Question 18

Refer to the exhibit. A Cloud Build config deploys a new image to GKE. After the build succeeds, the pods restart with the new image but the application configuration is unchanged. What is the most likely cause?

Accepted Answer

The ConfigMap is not updated with the new configuration values.. A is correct because a Cloud Build config that deploys a new image to GKE does not automatically update the ConfigMap. The pods restart with the new image, but the application configuration remains unchanged because the ConfigMap still holds the old values. To apply new configuration, the ConfigMap must be updated separately, and the pods must be restarted or redeployed to pick up the changes.

Answer

The deployment rollout strategy is set to Recreate, causing downtime.

Answer

The new image is not being pulled because of imagePullPolicy: IfNotPresent.

Answer

The GKE cluster does not have sufficient permissions to pull from Container Registry.

Question 19

A company runs a Java microservice on GKE that processes financial transactions. The service is critical and must meet a 99.9% availability SLO. They have set up Cloud Monitoring alerting policies based on request latency and error rate. Recently, the team noticed that the alerting policy for high latency fires too frequently with false positives, causing alert fatigue. They want to reduce false positives without compromising real issues. The latency metric is collected from the application's custom metric via Prometheus. Which approach should they take?

Accepted Answer

Increase the alert duration to require sustained latency over a longer period.. Increasing the alert duration requires the high latency to be sustained over a longer period, which filters out transient spikes that cause false positives. This approach preserves the ability to detect genuine, prolonged performance degradation that could impact the 99.9% availability SLO, without raising the threshold and risking missed real issues.

Answer

Change the metric to use median instead of average.

Answer

Increase the alert threshold to a higher latency value.

Answer

Disable the alert and rely on manual checks.

Question 20

A team is designing a disaster recovery plan for a critical application on Google Cloud. The application runs on Compute Engine with a regional persistent disk. They want to minimize data loss in case of a regional outage. Which strategy should they use?

Accepted Answer

Use persistent disk snapshot replication to another region. Persistent disk snapshot replication to another region is the correct strategy because snapshots are stored in Cloud Storage and can be replicated across regions. This allows you to restore the disk from a snapshot in a different region if the primary region experiences an outage, minimizing data loss by ensuring the backup is geographically separate. Regional persistent disks are synchronous within a region but do not provide cross-region replication, so snapshots are the recommended approach for cross-region disaster recovery.

Answer

Create a snapshot schedule and store snapshots in the same region

Answer

Use synchronous replication across regions

Answer

Configure a managed instance group with autohealing