PCD Practice Test 44 — 15 Questions

Question 1

A company is deploying Cloud Bigtable for a high-throughput write-heavy workload. They need high availability and read scalability across two GCP regions. Which TWO actions should they take? (Choose 2.)

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

Accepted Answer

Add a secondary cluster in a different region.. Adding a secondary cluster in a different region provides high availability and read scalability for Cloud Bigtable. With a multi-cluster instance, if the primary cluster fails, the secondary cluster can serve traffic, and read requests can be routed to the closest cluster for lower latency and load distribution.

Answer

Create the instance with HDD storage to reduce costs.

Answer

Use a development instance type.

Answer

Enable autoscaling for the primary cluster only.

Question 2

A team is designing a cloud-native application that must be highly available and resilient to zone failures. Which three practices should they follow? (Choose three.)

Accepted Answer

Deploy resources across multiple zones.. Deploying resources across multiple zones ensures that the application remains available even if an entire zone fails. In Google Cloud, zones are independent failure domains, and distributing workloads across them is a fundamental pattern for achieving high availability and resilience to zone-level outages.

Answer

Use a single Load Balancer with multiple backends.

Answer

Use zonal managed instance groups with 100% target utilization.

Question 3

You are designing a global user-facing application that requires strong consistency, horizontal scalability, and 99.999% availability across multiple continents. Which database service should you choose?

Accepted Answer

Cloud Spanner. Cloud Spanner is the only Google Cloud database service that provides strong consistency, horizontal scalability, and 99.999% availability across multiple continents. It uses synchronous replication and the TrueTime API to deliver external consistency across globally distributed nodes, making it ideal for global user-facing applications that require ACID transactions at scale.

Answer

Cloud SQL

Answer

Firestore

Answer

Bigtable

Question 4

A company is designing a highly available application on Google Cloud using multiple regions. Which TWO strategies should they implement to achieve this?

Accepted Answer

Use a global load balancer to distribute traffic across regions.. A global load balancer (e.g., Google Cloud External HTTPS Load Balancer) can distribute traffic across multiple regions, providing cross-region failover and low-latency routing. This is a fundamental pattern for multi-region high availability, as it allows traffic to be directed to healthy backends in any region, even if an entire region fails.

Answer

Use zonal persistent disks for stateful data.

Answer

Deploy a single instance group in one region for simplicity.

Answer

Store all data in a single Cloud Storage bucket.

Question 5

A company wants to automate the deployment of a microservice application to Cloud Run using Cloud Build. They want to ensure zero-downtime deployments and traffic migration. Which three features should they utilize? (Choose three.)

Accepted Answer

Cloud Build triggers to build and deploy on code changes.. Cloud Build triggers can be configured to automatically build and deploy a microservice to Cloud Run whenever code changes are pushed to a repository. This enables continuous delivery and ensures that the latest code is deployed without manual intervention, supporting zero-downtime deployments when combined with traffic management features.

Answer

Cloud Run min and max instance settings.

Answer

Cloud Run managed continuous deployment from a repository.

Question 6

A company is migrating a Snowflake data warehouse to BigQuery. They need to convert Snowflake SQL to BigQuery SQL. Which TWO tools or services can assist with this conversion?

Accepted Answer

BigQuery Migration Service. The BigQuery Migration Service (option E) is the dedicated tool for converting Snowflake SQL to BigQuery SQL, handling schema, DDL, and DML translations. The BigQuery Data Transfer Service (option B) does not support Snowflake as a source and does not perform SQL conversion; it is used for scheduling data transfers from supported sources. Therefore, only option E is correct.

Answer

gcloud bigquery copy

Answer

BigQuery Data Transfer Service

Answer

Cloud SQL Auth Proxy

Answer

Cloud Dataflow

Question 7

You are migrating a PostgreSQL database to Cloud SQL. The database currently uses custom functions and PostGIS extensions. The target must support these extensions. Which database version and tier should you choose?

Accepted Answer

Cloud SQL for PostgreSQL 15 with standard machine type. Cloud SQL for PostgreSQL supports PostGIS and custom functions. The machine type depends on performance needs, but any tier works as long as PostgreSQL is chosen.

Answer

Cloud SQL for MySQL 8.0 with highmem machine type

Answer

Cloud Spanner with PostgreSQL dialect

Answer

Cloud SQL for SQL Server 2019 with lightweight machine type

Question 8

Refer to the exhibit. You have the above cloudbuild.yaml file. The build succeeds but the call to the function fails with a permission error. What is the most likely cause?

Accepted Answer

The function call is occurring before the deployment is fully complete, and the function is not yet ready to serve requests. The most likely cause is that the Cloud Build step deploys the function, but the subsequent test call occurs before the function's HTTP endpoint is fully provisioned and serving requests. Cloud Functions deployment is asynchronous; after the `gcloud functions deploy` command returns, the function may still be in a 'DEPLOYING' or 'ACTIVE' state but not yet ready to handle traffic. A permission error in this context typically arises because the function's IAM policy (e.g., `--allow-unauthenticated`) is applied only after the deployment completes, and the function's runtime endpoint may return a 403 until fully ready.

Answer

The function is using the wrong trigger type

Answer

The runtime 'nodejs16' is not supported

Answer

The '--allow-unauthenticated' flag is not allowed in Cloud Build

Question 9

A team is deploying a microservices application on Google Kubernetes Engine (GKE). They want to ensure that if a pod fails, Kubernetes automatically replaces it and maintains the desired number of replicas. Which Kubernetes resource should they use?

Accepted Answer

Deployment. A Deployment is the correct Kubernetes resource for managing stateless microservices that require automatic pod replacement to maintain a desired replica count. It uses a ReplicaSet to ensure the specified number of pod replicas are running, and if a pod fails, the ReplicaSet controller immediately creates a new pod to restore the desired state.

Answer

StatefulSet

Answer

Job

Answer

DaemonSet

Question 10

A team uses Cloud Source Repositories for version control and Cloud Build for CI. The build configuration file (cloudbuild.yaml) includes a step that runs unit tests. The team wants to ensure that the build fails if any test fails. What should the developer do?

Accepted Answer

Ensure the test command in the build step returns a non-zero exit code when tests fail.. Cloud Build executes each step as a container, and the build step's success or failure is determined by the exit code of the command run inside that container. If the test command (e.g., `npm test` or `pytest`) returns a non-zero exit code when tests fail, Cloud Build will automatically mark that step as failed and stop the build. No special configuration or custom builder is required beyond ensuring the test command itself propagates the failure exit code.

Answer

Use Cloud Build's built-in test runner that automatically fails the build on test failure.

Answer

Create a custom builder that runs tests and emits a non-zero exit code on failure.

Answer

Add a pre-build step that checks test results and triggers a build failure if needed.

Question 11

A company uses Cloud Monitoring with custom metrics. They have a custom metric called 'requests_total' with labels 'endpoint', 'status_code'. They want to create an alert that fires if the error rate (status_code >=500) for any endpoint exceeds 5% over a 5-minute window. Which MQL query should they use?

Accepted Answer

fetch custom::requests_total | { filter status_code >= 500 ; group_by [endpoint], sum() } / { group_by [endpoint], sum() } | condition gt 0.05. It first filters for error responses (status_code >= 500), then groups by endpoint and sums the error count, and divides that by the total count per endpoint (also grouped and summed). This computes the error rate per endpoint, and the condition fires when that rate exceeds 0.05 (5%) over the 5-minute window. The use of two separate group_by operations within a join (the `{ ... } / { ... }` syntax) is the correct MQL pattern for calculating a ratio per label.

Answer

fetch custom::requests_total | filter status_code < 500 | ratio | condition gt 0.05

Answer

fetch custom::requests_total | group_by [endpoint], sum() | filter status_code >= 500 | ratio | condition gt 0.05

Answer

fetch custom::requests_total | filter status_code >= 500 | ratio | condition gt 0.05

Question 12

A company uses Cloud Run for a serverless application. They notice that cold starts are causing high latency for some requests. What is the best strategy to reduce cold starts?

Accepted Answer

Set a minimum number of instances to keep containers always warm. Setting a minimum number of instances ensures that Cloud Run keeps a baseline of container instances always warm and ready to serve requests. This eliminates cold starts for the first requests that hit those pre-warmed instances, directly addressing the latency issue. Cloud Run automatically scales to zero when idle, but a minimum instance setting overrides that behavior for the specified number of containers.

Answer

Increase the max instances setting

Answer

Migrate the application to Cloud Functions

Answer

Reduce the container concurrency setting

Question 13

Which THREE common issues cause deployment failures on App Engine? (Choose 3.)

Accepted Answer

Using a runtime version that is not available in the app's region.. App Engine requires that the runtime version specified in your app.yaml is available in the region where the application is deployed. If you select a runtime version that has been deprecated or is not yet rolled out to that region, the deployment will fail with an error indicating the runtime is unavailable. This is a common issue when using newer runtime versions that are only available in certain regions.

Answer

Setting the app to scale to 0 instances.

Answer

Creating a resource with backend type set to 'backend' instead of 'frontend'.

Question 14

Your team is using Cloud Build to build and test a Java application. The build includes unit tests, integration tests, and static code analysis. The build is failing intermittently due to flaky tests. You want to automatically retry the failed steps without rebuilding everything. Which Cloud Build feature should you use?

Accepted Answer

Set the 'allowFailure: false' and 'retry: 2' options on the test steps in the cloudbuild.yaml. Cloud Build supports the `retry` option on individual build steps, which allows a step to be automatically retried a specified number of times upon failure without re-executing previous steps. This is ideal for handling flaky tests, as it only reruns the failed step, preserving build artifacts and avoiding a full rebuild.

Answer

Configure a Cloud Build trigger to rerun the build on failure

Answer

Use build substitutions to pass different test parameters on failure

Answer

Increase the timeout for the build to allow retries

Question 15

A development team wants to implement a CI/CD pipeline for a containerized application on Google Cloud. They are using Cloud Build and Cloud Deploy. The application requires canary deployments with automatic rollback if the error rate increases by more than 10% within 5 minutes after deployment. Which Cloud Deploy feature should they configure?

Accepted Answer

Define a Cloud Deploy deployment policy with a rollout policy that uses a canary strategy and a verification phase with automated rollback. Cloud Deploy's deployment policies allow you to define a canary rollout strategy with an automated verification phase. When the verification phase detects that the error rate exceeds the defined threshold (e.g., 10% increase within 5 minutes), Cloud Deploy automatically initiates a rollback to the previous stable revision, meeting the team's requirement without additional custom code.

Answer

Configure a Pub/Sub notification on the rollout to trigger a rollback via a Cloud Function

Answer

Use Cloud Monitoring to create an alert policy that triggers a Cloud Function to rollback the deployment

Answer

Set up a Cloud Build trigger to rebuild the previous image on error