PCD Practice Test 33 — 15 Questions

Question 1

Your team runs an order-processing service on Cloud Run (fully managed) in europe-west1. Traffic is spiky, and during peak shopping events the service occasionally returns HTTP 503 errors while new instances are starting. You want to reduce cold-start latency for this Java service without changing the container's behavior. What should you do?

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

Accepted Answer

Configure a minimum number of instances on the Cloud Run service so warm instances are always available.. Cold-start latency on a fully managed Cloud Run service is best mitigated by keeping a baseline of warm instances, which the minimum instance count setting provides. That way, burst traffic is absorbed by already-initialized containers rather than triggering new cold starts. Scaling limits, timeouts, and caching do not address Java runtime initialization delays for dynamic order requests.

Answer

Enable Cloud CDN in front of the Cloud Run service to cache responses during peak events.

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Increase the Cloud Run maximum number of instances so more containers can be created during spikes.

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Raise the Cloud Run request timeout so slow-starting instances have more time to respond.

Question 2

A company has a monorepo with multiple services. They want to only build and test the services that have changed in a given commit. Which Cloud Build feature should they use?

Accepted Answer

Build triggers with filepath filters. Cloud Build triggers with filepath filters allow you to specify glob patterns that match changed files in a commit. When a commit includes changes only to files matching the filter, the trigger runs; otherwise, it is skipped. This enables selective building and testing of only the services that have changed in a monorepo, avoiding unnecessary builds for unaffected services.

Answer

Use a custom builder image

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Build triggers with branch filters

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Use Cloud Build substitutions

Question 3

A development team deploys a containerized web application to Cloud Run. Users in Europe and Asia report high latency, although the service is healthy. The team wants the lowest possible latency for a global audience without managing clusters or rewriting the application. What should they do?

Accepted Answer

Deploy the Cloud Run service to multiple regions and place a global external Application Load Balancer in front of it.. Placing a global external Application Load Balancer in front of Cloud Run services deployed in multiple regions combines anycast edge termination with regional execution. Users connect to the nearest Google edge and are routed to the closest healthy backend, cutting round-trip latency. This needs no cluster management and no application rewrite.

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Deploy the Cloud Run service with the --region flag set to a single region close to the majority of users.

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Enable Cloud CDN on the Cloud Run service and configure a cache TTL for all responses.

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Deploy the container to a GKE Autopilot cluster with a multi-zone node pool and a global external load balancer.

Question 4

A financial analytics platform ingests market data into Cloud Bigtable and serves point reads to a trading dashboard. The application currently uses a single-cluster instance in us-central1. The business requires that the dashboard remain readable even if the entire us-central1 region becomes unavailable, with a recovery point objective of zero. Which Bigtable configuration should the team implement?

Accepted Answer

Configure a multi-cluster routing instance with clusters in us-east1 and us-west1, and use an application profile with cluster group routing.. Bigtable achieves cross-region availability by placing clusters in multiple regions within one multi-cluster instance; replication is synchronous, so the recovery point objective is zero. The application profile's routing policy determines whether clients actually use the other clusters. Cluster group routing sends requests to any cluster in the group, enabling automatic failover when a region is lost, whereas single-cluster routing would keep clients pinned to the failed region.

Answer

Export nightly snapshots of the Bigtable tables to Cloud Storage in us-east1 and restore them if us-central1 fails.

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Enable a read replica in us-east1 on the existing single-cluster instance and point the dashboard at the replica endpoint.

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Create a multi-cluster routing instance with clusters in us-east1 and us-west1, and configure the application profile with single-cluster routing.

Question 5

A development team is deploying a containerized microservices application on Google Kubernetes Engine (GKE). They need to ensure that the application remains available even if a single node fails, and that pods are automatically rescheduled onto healthy nodes. They also want to minimize manual operational overhead. Which configuration should they use?

Accepted Answer

Create a regional GKE cluster with multiple node pools across zones and rely on the Kubernetes scheduler and ReplicaSet controller to reschedule pods.. A regional GKE cluster distributes nodes across multiple zones, so a single node or even an entire zone failure does not take down the application. The ReplicaSet controller ensures the desired number of pod replicas exists, and the Kubernetes scheduler places replacement pods on healthy nodes. This built-in automation minimizes manual intervention and directly addresses the availability and operational overhead requirements.

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Create a zonal GKE cluster and manually create standby nodes in a second zone that can be added to the cluster during a failure.

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Create a regional GKE cluster and configure each pod to use a node selector that pins it to a specific node for predictable performance.

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Create a zonal GKE cluster with a single node pool and configure pod anti-affinity to spread pods across nodes.

Question 6

A media company streams video metadata through a Cloud Run service in us-central1. The service writes to a Firestore database in the same region. A new requirement says the service must survive a full regional outage in us-central1 with a recovery time objective (RTO) of 15 minutes. The team wants the least operational overhead while keeping a consistent global view of the data. Which design should they choose?

Accepted Answer

Deploy the Cloud Run service to multiple regions behind a global external Application Load Balancer and use Firestore in Native mode with a multi-region location.. The goal is automatic regional failover with a single consistent data view and minimal operations. A global external Application Load Balancer sends traffic to a surviving Cloud Run region, and a multi-region Firestore Native location keeps one logical database replicated across regions. This removes manual failover and meets the 15-minute RTO with little operational effort.

Answer

Deploy the Cloud Run service to multiple regions and use Firestore in Datastore mode with a single-region location in us-central1, relying on scheduled exports for recovery.

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Deploy the Cloud Run service to multiple regions and use Cloud SQL for PostgreSQL with a cross-region replica, promoting the replica during an outage.

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Keep the Cloud Run service in us-central1 and add a Cloud Storage bucket in a dual-region as a write-ahead log that the service replays after an outage.

Question 7

A media streaming company runs a read-heavy API on Cloud Run (fully managed) serving a global audience. The service reads from Cloud Storage and occasionally writes user playback history to Cloud Firestore. Users in Asia report high latency, while users in North America experience fast responses. The team wants to reduce latency for all users without changing the application code. What should they do?

Accepted Answer

Deploy the Cloud Run service to multiple regions and use a global external HTTP(S) load balancer to route users to the nearest region.. Deploying the Cloud Run service in multiple regions and using a global external HTTP(S) load balancer ensures that users are routed to the nearest regional deployment, minimizing network latency. This approach requires no application code changes and leverages Google Cloud's global load balancing and Cloud Run's regional scalability. It also improves availability because traffic can fail over to another region if one becomes unhealthy.

Answer

Increase the maximum number of instances for the Cloud Run service and set concurrency to 1.

Answer

Enable Cloud CDN with a global external HTTP(S) load balancer in front of the Cloud Run service and cache the API responses.

Answer

Enable Cloud Run's CPU always allocated and set the minimum instance count to a high value.

Question 8

A team is designing a new microservices application on Cloud Run and wants to maximize reliability and availability without over-engineering. Which TWO practices should they adopt? (Choose two.)

Accepted Answer

Configure each service with a minimum instance count greater than zero and a health-check-compatible startup so cold starts do not cause request failures during traffic ramp-up.. Reliability on Cloud Run comes from reducing cold-start exposure and handling transient failures gracefully. Warm minimum instances smooth the ramp-up so requests are not rejected while containers start, and client-side retries with backoff and jitter combined with idempotent operations let the system recover from brief failures without duplicating effects. Together these practices raise availability with modest cost and complexity.

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Set the container concurrency to 1 for every service so each instance handles exactly one request at a time.

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Disable Cloud Run's built-in health checks and rely on client-side timeouts to detect unhealthy instances.

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Pin every Cloud Run service to a single region to reduce cross-region latency and operational complexity.

Question 9

A developer is building a container image for a Cloud Run service using Cloud Build. The build uses a Dockerfile that copies application code and runs tests. The tests fail intermittently due to network timeouts when accessing an external API. The developer wants to make the build reliable and fast by mocking the external API during the build. Which approach should they take?

Accepted Answer

Add a build step that starts a local mock server and configure the application to use its URL via an environment variable during tests.. Mocking the external API during the build eliminates network dependencies and makes tests deterministic. Running a local mock server in a Cloud Build step and injecting its URL via environment variable allows the application to use the mock seamlessly, ensuring fast and reliable builds.

Answer

Configure the tests to retry on failure up to three times, and add a delay between retries.

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Increase the timeout for the test step in the cloudbuild.yaml to allow more time for external API calls.

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Use a Cloud Build private pool to run the build in a VPC network with a NAT gateway for stable outbound connectivity.

Question 10

A startup deploys a stateless containerized web application on Google Kubernetes Engine (GKE) Autopilot. The application must remain available even if a single zone fails. The cluster is regional with nodes spread across three zones. What should the team do to ensure the application survives a zone failure?

Accepted Answer

Set the Deployment's replica count to at least three and configure topology spread constraints to spread pods evenly across zones.. For a stateless application on a regional GKE cluster, zone resilience comes from running enough replicas and using topology spread constraints so that no single zone hosts all pods. If a zone fails, the remaining replicas continue serving requests, and the Deployment controller reschedules pods onto healthy nodes in the surviving zones.

Answer

Configure a PodDisruptionBudget that requires at least one pod to be available at all times.

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Create a second GKE cluster in another region and use Multi Cluster Ingress to route traffic to both clusters.

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Enable node auto-repair and node auto-upgrade on the cluster's node pools.

Question 11

You are deploying a stateless API on Google Kubernetes Engine (GKE) that must survive a zone outage in a single region without manual intervention. The cluster is regional, and the Deployment runs three replicas. What should you configure to ensure pods are spread across zones and that the Deployment maintains availability?

Accepted Answer

Configure topology spread constraints with topologyKey set to the zone label and a balanced skew policy.. Topology spread constraints are the native GKE mechanism for spreading pods across zones in a regional cluster. By targeting the zone topology key with a balanced skew policy, the scheduler distributes replicas evenly, so a zone outage degrades capacity rather than taking the whole Deployment offline. Disruption budgets and autoscalers address different availability concerns.

Answer

Set a PodDisruptionBudget with minAvailable: 1 on the Deployment.

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Create a horizontal Pod autoscaler that scales the Deployment based on CPU utilization.

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Add pod anti-affinity rules that require pods to run on nodes in different zones.

Question 12

A team is building a highly available application on Google Cloud that must survive a zonal failure. The application runs on Compute Engine and uses a managed instance group. They want to ensure that the application remains available if a single zone becomes unavailable. (Choose two.)

Accepted Answer

Distribute the managed instance group across multiple zones in the region.. To survive a zonal failure, compute capacity must exist in multiple zones, and traffic must be routed only to healthy instances. A regional managed instance group distributes instances across zones, and an HTTP(S) load balancer with health checks automatically avoids failed zones. Together they provide continuous availability during a zonal outage.

Answer

Attach a persistent disk to each instance and configure the disks to replicate across zones.

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Set the instance group's autoscaling policy to scale based on CPU utilization.

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Use a single-zone managed instance group and enable autoscaling.

Question 13

A developer is creating a Cloud Build pipeline to run unit tests for a Python application before building a container image. The tests are in a separate directory and require installing dependencies from requirements.txt. Which build step should they use?

Accepted Answer

A step using the python:3.9 image with entrypoint 'bash' and args ['-c', 'pip install -r requirements.txt && pytest tests/'].. To run unit tests in Cloud Build, the build step must install dependencies and execute the test command. Using a Python image with a bash command that chains pip install and pytest achieves this in a single step. This ensures the test environment has all necessary libraries and runs the tests, which is essential for a reliable CI pipeline.

Answer

A step using the python:3.9 image with entrypoint 'pytest' and args ['tests/'].

Answer

A step using the gcr.io/cloud-builders/gcloud image with args ['test', 'run'].

Answer

A step using the python:3.9 image with entrypoint 'pip' and args ['install', '-r', 'requirements.txt'].

Question 14

A logistics company runs an event-driven order-tracking service on Cloud Run that consumes messages from a Pub/Sub push subscription. During traffic spikes, the service returns HTTP 500 errors for some messages, and the subscription's dead-letter topic is filling up. The team wants failed messages to be retried automatically before being sent to the dead-letter topic, and they want to avoid duplicate processing. What should they do?

Accepted Answer

Configure a retry policy with exponential backoff on the subscription and make the consumer idempotent using a message ID deduplication store.. A retry policy with exponential backoff lets Pub/Sub redeliver failed messages with increasing delays before the dead-letter threshold is reached, giving the service time to recover. Idempotent consumers keyed on message ID prevent duplicates from redelivery. Together they ensure reliable retries without duplicate order processing.

Answer

Set the dead-letter topic's max delivery attempts to one so messages move to the dead-letter topic before any retry occurs.

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Increase the subscription's ack deadline to the maximum and disable the dead-letter topic so messages are retried indefinitely.

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Switch from a push subscription to a pull subscription and have each Cloud Run instance acknowledge messages immediately upon receipt.

Question 15

A developer is writing integration tests for a Cloud Run service that connects to Cloud SQL. The tests will run in a Cloud Build pipeline. The developer wants to minimize test flakiness and ensure the database is in a known state before each test. What should the developer do?

Accepted Answer

Use the Cloud SQL Auth Proxy in a build step to connect to a dedicated test database instance, and run a script to reset the database before tests.. Using a dedicated test Cloud SQL instance with the Cloud SQL Auth Proxy and resetting the database before tests ensures isolation, known state, and realistic connectivity. This minimizes flakiness and accurately tests the integration. Other options either use the wrong database engine, risk production data, or rely on a non-existent emulator.

Answer

Use a Cloud SQL emulator that mimics the Cloud SQL API for local testing.

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Embed a SQLite database in the Cloud Run service for testing, and switch to Cloud SQL in production.

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Connect directly to the production Cloud SQL instance from Cloud Build and run tests against it.