PCD Practice Test 11 — 15 Questions

Question 1

Your application runs on Compute Engine and uses Cloud Pub/Sub to receive messages from a third-party service. Recently, the message delivery latency has increased significantly. The third-party reports no issues on their end. You notice that the Pub/Sub subscription's 'ackDeadlineSeconds' is set to 10. What is the most likely cause of the latency?

Accepted Answer

The ackDeadlineSeconds is too short, causing frequent message redelivery.. A is correct because a 10-second ackDeadlineSeconds is very short. If your subscriber cannot process and acknowledge messages within 10 seconds, Pub/Sub will consider them unacknowledged and redeliver them. This redelivery causes duplicate processing and increases overall latency as messages are repeatedly sent back to the subscriber, delaying their final consumption.

Answer

The topic's message retention duration is too long.

Answer

The push endpoint is not responding, causing Pub/Sub to retry.

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The subscription has an exponential backoff policy that is too aggressive.

Question 2

You are designing a data pipeline that ingests streaming data from IoT devices using Cloud IoT Core, processes it with Dataflow, and stores results in BigQuery. The data volume is expected to be 10 GB per day with occasional spikes. You need to minimize processing latency and cost. Which configuration should you choose for the Dataflow pipeline?

Accepted Answer

Use streaming mode with streaming engine enabled and 2 workers.. Option C is correct because streaming mode with Streaming Engine is designed for low-latency, continuous data ingestion from IoT Core, and setting 2 workers minimizes cost while handling the expected 10 GB/day volume with occasional spikes through autoscaling. Streaming Engine offloads state management to the backend, reducing worker overhead and improving latency, making it ideal for this use case.

Answer

Use streaming mode with autoscaling and maximum workers set to 10.

Answer

Use Dataflow Prime for automatic optimization.

Answer

Use batch mode with a fixed number of workers to reduce cost.

Question 3

Your company uses Cloud SQL for MySQL to store transactional data. You need to perform a point-in-time recovery (PITR) to recover from a logical error that occurred 30 minutes ago. Which two prerequisites must be met? (Choose TWO.)

Accepted Answer

Binary logging is enabled.. Point-in-time recovery (PITR) for Cloud SQL for MySQL relies on binary logs to replay transactions up to a specific timestamp. Binary logging must be enabled because it records all changes to the database, allowing you to restore to any point within the retention period. Automated backups are also required because PITR uses the most recent full backup as a base, then applies binary logs from that backup to the target time. Without automated backups, there is no base image to start the recovery process.

Answer

High availability (HA) is configured.

Answer

The backup window is set to a time before the incident.

Answer

A read replica is configured.

Question 4

A company is migrating a legacy monolithic application to Google Cloud. They want to minimize code changes and operational overhead while improving scalability. The application currently uses a relational database and stores user-uploaded images on a local filesystem. Which combination of Google Cloud services should they use?

Accepted Answer

Cloud SQL for the database and Cloud Storage with Cloud CDN for images. Option C is correct because Cloud SQL provides a fully managed relational database that requires minimal code changes when migrating from an existing relational database, while Cloud Storage with Cloud CDN handles user-uploaded images with scalable object storage and low-latency content delivery. This combination minimizes operational overhead by eliminating the need to manage database servers or file servers, and improves scalability through automatic replication and global edge caching.

Answer

Cloud Spanner for the database and Cloud Storage for images

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Cloud Firestore for the database and Cloud Storage with Cloud CDN for images

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Compute Engine with attached SSD persistent disks for both database and images

Question 5

A DevOps team is designing a CI/CD pipeline for a microservices application deployed on Google Kubernetes Engine (GKE). They want to automatically build and deploy each service when a new tag is pushed to its repository. They also need to run integration tests against a staging environment before promoting to production. Which service should they use to orchestrate the pipeline?

Accepted Answer

Cloud Build with a build trigger on tag push. Cloud Build with a build trigger on tag push is the correct choice because it natively supports event-driven pipelines triggered by Git tags, enabling automatic build and deployment of each microservice. Combined with Cloud Build's ability to run integration tests in a staging environment and then promote to production, it provides a complete CI/CD solution for GKE without additional orchestration services.

Answer

Deployment Manager with a template

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Cloud Deploy with a delivery pipeline

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Cloud Run with continuous deployment

Question 6

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 7

Which TWO actions are best practices for managing application performance monitoring in Google Cloud?

Accepted Answer

Set appropriate sampling rates for Cloud Trace to balance cost and insight.. Option A is correct because Cloud Trace charges based on the number of spans ingested and retained. Setting an appropriate sampling rate (e.g., 1 in 10 requests for high-traffic services) reduces cost while still providing statistically significant latency data for performance analysis. This balances the need for actionable insights against budget constraints.

Answer

Enable debug logging in production to capture detailed errors.

Answer

Log all application activity at INFO level for complete visibility.

Answer

Configure alerts to send emails to the entire development team.

Question 8

A developer is deploying a new version of a microservice to Cloud Run. The developer wants to ensure that the new revision is tested with a small percentage of traffic before rolling out to all users. Which TWO approaches can the developer use?

Accepted Answer

Use the 'gcloud run deploy' command with '--no-traffic' and then use 'gcloud run services update-traffic --to-revisions=REVISION=5' to send 5% of traffic.. Option A is correct because the '--no-traffic' flag deploys the new revision without serving any traffic, and then 'gcloud run services update-traffic --to-revisions=REVISION=5' allows you to send exactly 5% of traffic to that revision for canary testing. Option B is also correct because it describes the same two-step process: deploy with '--no-traffic' to avoid immediate traffic, then use 'update-traffic' to gradually increase the percentage, which is the standard canary deployment pattern on Cloud Run.

Answer

Set the 'max-instances' parameter to limit the number of instances handling requests.

Answer

Use the 'gcloud run deploy' command with '--tag' to assign a tag to the new revision, then direct test traffic to that tag.

Answer

Deploy the new revision with the same revision name as the old one to overwrite it, then roll back if issues occur.

Question 9

Which TWO are best practices for setting up alerting policies in Cloud Monitoring? (Choose two.)

Accepted Answer

Include documentation in the alert policy to guide responders. Option A is correct because including documentation in alert policies provides responders with immediate context, runbooks, and troubleshooting steps directly within the alert notification. This reduces mean time to resolution (MTTR) by ensuring responders have the necessary information without needing to search external sources. Cloud Monitoring supports embedding Markdown documentation in alert policies, which is a best practice for operational efficiency.

Answer

Create separate alerts for each condition rather than combining them

Answer

Avoid using notification channels to reduce noise

Answer

Set all alerts to high severity to ensure visibility

Question 10

A team is building a mobile backend on Google Cloud using Cloud Endpoints with Firebase Authentication. They want to protect their API from abuse by implementing rate limiting per user. What approach should they take?

Accepted Answer

Use Apigee API Management as a proxy to enforce rate limiting per developer app.. Apigee API Management is the correct choice because it provides built-in rate limiting policies that can be enforced per developer app, which maps directly to per-user rate limiting when Firebase Authentication is used. Cloud Endpoints does not natively support per-user rate limiting; it relies on the backend to implement such logic, which is not a managed solution. Apigee acts as a proxy that can inspect the Firebase-issued JWT token to identify the user and apply rate limits accordingly, offloading this concern from the backend code.

Answer

Implement rate limiting in the backend code and enforce it via Cloud Endpoints.

Answer

Configure Cloud Armor with a rule to block requests from users exceeding a threshold.

Answer

Use Cloud CDN with a cache key based on the user ID.

Question 11

Your company runs a multi-tier web application on Google Kubernetes Engine (GKE). The application consists of a frontend service, a backend API service, and a PostgreSQL database managed by Cloud SQL. Recently, users have been reporting intermittent slow response times during peak hours (10 AM - 12 PM). You have set up Cloud Monitoring dashboards and alerts. Cloud Trace shows that the backend API service has high latency, but only for certain requests. You notice that the backend service's CPU utilization is around 60% during peak hours, and memory usage is normal. The Cloud SQL instance's CPU utilization is at 90% and the query latency is high. You have also observed that the backend service makes multiple database queries per request, some of which are repeated. What is the most effective course of action to reduce latency?

Accepted Answer

Increase the CPU and memory of the Cloud SQL instance to handle the load. The primary bottleneck is the Cloud SQL instance, which is running at 90% CPU with high query latency. Since the backend service's CPU is only at 60% and memory is normal, scaling the database directly addresses the root cause. Increasing the Cloud SQL instance's CPU and memory provides more processing power and connection capacity to handle the peak load, reducing query latency and overall response times.

Answer

Scale up the backend API service by increasing the number of replicas

Answer

Scale up the frontend service by increasing the number of replicas

Answer

Implement a caching layer using Memorystore for Redis to cache database query results

Question 12

An application running on Compute Engine uses Cloud Storage for storing user-uploaded images. During load testing, the application experiences high latency when reading images. The developer suspects that the application is making too many small read requests. Which approach should the developer take to optimize performance?

Accepted Answer

Increase the read size to reduce the number of API requests.. Option C is correct because the high latency is caused by many small read requests, each incurring API overhead. By increasing the read size (e.g., reading larger chunks or using range requests), the application reduces the number of API calls, which lowers cumulative latency and improves throughput. This directly addresses the root cause of excessive small reads.

Answer

Enable Cloud CDN to cache the images at edge locations.

Answer

Rewrite the objects to use a different storage class.

Answer

Mount the Cloud Storage bucket using Cloud Storage FUSE and read files from the local filesystem.

Question 13

A team wants to monitor custom application metrics from a Compute Engine instance. They use the Cloud Monitoring agent. Which metric type should they use to report a gauge measurement like current memory usage?

Accepted Answer

gauge. Option D is correct because a gauge metric type is specifically designed to report a value that can arbitrarily increase or decrease over time, such as current memory usage. The Cloud Monitoring agent supports gauge metrics for point-in-time measurements, and they are reported as a single data point without any aggregation window, making them ideal for snapshot-like observations.

Answer

histogram

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delta

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cumulative

Question 14

Drag and drop the steps to set up a Firestore database in native mode in the correct order.

Question 15

Drag and drop the steps to troubleshoot a failed Cloud Build in the correct order.