PCD Practice Test 2 — 10 Questions

Question 1

A company uses Cloud Run for a serverless application that processes user uploads. Users report that sometimes the first request after a period of inactivity takes very long (cold start). The application is stateless. They want to minimize cold start latency while keeping costs low. The application is deployed with default settings: min instances = 0, max instances = 100, CPU always off, and a container image of 1GB. What should they do to reduce cold start latency?

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

Accepted Answer

Set min instances to 1 to keep a warm instance.. Setting min instances to 1 ensures that at least one instance is always warm and ready to serve requests, eliminating the cold start for the first request after a period of inactivity. Since the application is stateless and the default min instances is 0, Cloud Run scales down to zero, causing a cold start on the next request. By keeping one instance warm, you minimize latency without significantly increasing cost, as you only pay for the single idle instance.

Answer

Increase container memory from the default to reduce startup time.

Answer

Use a larger container image to include more dependencies.

Answer

Enable CPU always on allocation.

Question 2

A team is deploying a microservices application on Cloud Run and needs to implement canary deployments with traffic splitting. They are using Cloud Deploy. What is the correct configuration to gradually shift traffic from the old revision to the new revision?

Accepted Answer

Use a Cloud Deploy delivery pipeline with a canary strategy that specifies percentages like [5, 10, 50, 100] and includes a verification step.. Cloud Deploy natively supports canary deployments with traffic splitting for Cloud Run. By defining a canary strategy with incremental percentages (e.g., [5, 10, 50, 100]) and including a verification step, the pipeline automatically shifts traffic in stages, pausing for verification at each phase to ensure the new revision is healthy before progressing. This approach integrates directly with Cloud Deploy's delivery pipeline, eliminating the need for manual scripts or external API calls.

Answer

Use Cloud Build to deploy with a script that gradually increases traffic using the Cloud Run API.

Answer

Use a Cloud Deploy pipeline with a blue-green strategy that swaps all traffic at once.

Answer

Use Cloud Run's built-in traffic splitting with `gcloud run deploy --traffic` and manage manually.

Question 3

A developer is writing unit tests for a Cloud Function that reads from Firestore. They want to avoid real Firestore calls in tests. Which approach is best?

Accepted Answer

Mock the Firestore client library in the test code. Mocking the Firestore client library allows testing the function logic without dependencies on external services, which is the essence of unit testing.

Answer

Use Cloud Functions local emulator with Firestore emulator

Answer

Create a test project with real Firestore and use real calls

Answer

Use Firestore emulator for tests

Question 4

A development team is using Cloud Build to deploy containerized applications to GKE. They want to ensure that only containers that have passed security scans and unit tests are deployed to production. Which approach should they use?

Accepted Answer

Use Cloud Build with a multi-step pipeline that includes test and security scan steps, and only promote to production after successful completion.. Using a multi-step Cloud Build pipeline with test and security scan steps, and then promoting to production only after success, ensures only validated containers are deployed. Direct deployment to production on every push is risky. Manual promotion defeats automation. Cloud Deploy adds unnecessary complexity for this simple requirement. Thus, option B is correct.

Answer

Deploy to a staging cluster first, then manually promote to production using kubectl.

Answer

Use Cloud Deploy to automate delivery with approval gates.

Answer

Configure Cloud Build triggers to deploy directly to production on every push.

Question 5

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 6

A financial trading application on Compute Engine requires an RPO of 5 seconds and RTO of 1 minute for zone failures. Which architecture should they use?

Accepted Answer

Regional persistent disk attached to a single instance. Regional persistent disks provide synchronous replication of data between two zones within a region, ensuring an RPO of effectively zero (typically under 5 seconds) and enabling rapid failover to a secondary zone. By attaching the regional disk to a single Compute Engine instance, the application can quickly resume operations in the other zone upon failure, meeting the 1-minute RTO without data loss or complex replication overhead.

Answer

Persistent disk with periodic snapshots to a different zone

Answer

Managed instance group with autoscaling and health checks

Answer

Two instances in different zones with data replicated via rsync

Question 7

A company is using Cloud Deploy to manage canary deployments to GKE. They want to automatically promote a release to the 'production' target if the canary deployment in the 'staging' target passes a set of automated smoke tests. What is the required configuration?

Accepted Answer

Define a deployment verifier in the pipeline that runs smoke tests and promotes on success.. Cloud Deploy supports deployment verifiers, which are custom Cloud Build jobs that run as part of a rollout. By defining a verifier in the pipeline that executes automated smoke tests, the canary deployment in the staging target can be automatically promoted to production only if the verifier succeeds. This integrates testing directly into the delivery pipeline without manual intervention.

Answer

Create a Cloud Build trigger to redeploy on test success.

Answer

Configure a manual approval gate between staging and production in the delivery pipeline.

Answer

Set the 'automaticPromotion' flag to true on the staging target.

Question 8

A company is migrating a monolithic application to microservices on Google Cloud. They have strict requirements for service-to-service communication: requests must be authenticated, authorized, and encrypted in transit. They also need to enforce fine-grained access control based on the requesting service identity. Which Google Cloud service should they use to achieve these goals?

Accepted Answer

Cloud Service Mesh (Anthos Service Mesh). Cloud Service Mesh (Anthos Service Mesh) provides mutual TLS, fine-grained authorization policies, and service identity. Option A is for API management, option B is for DDoS protection, and option D is for serverless ingress control.

Answer

Cloud Run with ingress control

Answer

Cloud Armor with IAM

Answer

Cloud Endpoints with API keys

Question 9

A developer is building a serverless application that processes user-uploaded images. The images are stored in Cloud Storage, and each upload should trigger a Cloud Function that performs image analysis and stores the result in Firestore. Which TWO Google Cloud services are essential for this integration? (Choose 2)

Accepted Answer

Cloud Pub/Sub. Cloud Storage is the source of events (uploaded images). Cloud Pub/Sub is used to deliver notifications from Cloud Storage to the Cloud Function. Cloud Tasks, Cloud Scheduler, and Eventarc are not required for this pattern.

Answer

Cloud Tasks

Answer

Eventarc

Answer

Cloud Scheduler

Question 10

A company wants to trigger a Cloud Run job every time a new file is uploaded to a Cloud Storage bucket. Which integration should be used?

Accepted Answer

Use Eventarc to create a trigger that routes Cloud Storage events to the Cloud Run job.. Eventarc can route Cloud Storage events (like object finalize) to Cloud Run jobs via CloudEvents. Option A is wrong because Cloud Scheduler is time-based, not event-based. Option B is wrong because Cloud Functions can be triggered by storage events, but the question asks for Cloud Run job. Option D is wrong because Pub/Sub alone cannot directly trigger a Cloud Run job without a subscription or push endpoint.

Answer

Use Cloud Pub/Sub notifications from the bucket and create a push subscription to the Cloud Run job.

Answer

Use Cloud Scheduler to poll the bucket and invoke the Cloud Run job every minute.

Answer

Use Cloud Functions to listen for storage events and then call the Cloud Run job via HTTP.