Google Professional Cloud Developer Practice Exams
Last updated on Oct 22,2026- Exam Code: Professional Cloud Developer
- Exam Name: Professional Cloud Developer
- Certification Provider: Google
- Latest update: Oct 22,2026
Your team is developing a Cloud Function triggered by Cloud Storage Events. You want to accelerate testing and development of your Cloud Function while following Google-recommended best practices.
What should you do?
- A . Install the Functions Frameworks library, and configure the Cloud Function on localhost. Make a copy of the function, and make edits to the new version Test the new version using cur1.
- B . Make a copy of the Cloud Function, and rewrite the code to be HTTP-triggered Edit and test the new version by triggering the HTTP endpoint. Send mock requests to the new function to evaluate the functionality.
- C . Make a copy of the Cloud Function in the Google Cloud Console Use the Cloud console’s in-line editor to make source code changes to the new function Modify your web application to call the new function and test the new version in production.
- D . Create a new Cloud Function that is triggered when Cloud Audit Logs detects the cloud functions. functions. source CodeSet operation in the original Cloud Function Send mock requests to the new function to evaluate the functionality.
Your team is developing a Cloud Function triggered by Cloud Storage Events. You want to accelerate testing and development of your Cloud Function while following Google-recommended best practices.
What should you do?
- A . Install the Functions Frameworks library, and configure the Cloud Function on localhost. Make a copy of the function, and make edits to the new version Test the new version using cur1.
- B . Make a copy of the Cloud Function, and rewrite the code to be HTTP-triggered Edit and test the new version by triggering the HTTP endpoint. Send mock requests to the new function to evaluate the functionality.
- C . Make a copy of the Cloud Function in the Google Cloud Console Use the Cloud console’s in-line editor to make source code changes to the new function Modify your web application to call the new function and test the new version in production.
- D . Create a new Cloud Function that is triggered when Cloud Audit Logs detects the cloud functions. functions. source CodeSet operation in the original Cloud Function Send mock requests to the new function to evaluate the functionality.
You are deploying your application on a Compute Engine instance that communicates with Cloud SQL. You will use Cloud SQL Proxy to allow your application to communicate to the database using the service account associated with the application’s instance. You want to follow the Google-recommended best practice of providing minimum access for the role assigned to the service account.
What should you do?
- A . Assign the Project Editor role.
- B . Assign the Project Owner role.
- C . Assign the Cloud SQL Client role.
- D . Assign the Cloud SQL Editor role.
C
Explanation:
Reference: https://cloud.google.com/sql/docs/mysql/sql-proxy
You are configuring a continuous integration pipeline using Cloud Build to automate the deployment of new container images to Google Kubernetes Engine (GKE). The pipeline builds the application from its source code, runs unit and integration tests in separate steps, and pushes the container to Container Registry. The application runs on a Python web server.
The Dockerfile is as follows:
FROM python:3.7-alpine –
COPY. /app –
WORKDIR /app –
RUN pip install -r requirements.txt
CMD [ "gunicorn", "-w 4", "main:app" ]
You notice that Cloud Build runs are taking longer than expected to complete. You want to decrease the build time.
What should you do? (Choose two.)
- A . Select a virtual machine (VM) size with higher CPU for Cloud Build runs.
- B . Deploy a Container Registry on a Compute Engine VM in a VPC, and use it to store the final images.
- C . Cache the Docker image for subsequent builds using the — cache-from argument in your build config file.
- D . Change the base image in the Dockerfile to ubuntu:latest, and install Python 3.7 using a package manager utility.
- E . Store application source code on Cloud Storage, and configure the pipeline to use gsutil to download the source code.
AC
Explanation:
https://cloud.google.com/build/docs/optimize-builds/increase-vcpu-for-builds
By default, Cloud Build runs your builds on a standard virtual machine (VM). In addition to the standard VM, Cloud Build provides several high-CPU VM types to run builds. To increase the speed of your build, select a machine with a higher vCPU to run builds. Keep in mind that although selecting a high vCPU machine increases your build speed, it may also increase the startup time of your build as Cloud Build only starts non-standard machines on demand.
https://cloud.google.com/build/docs/optimize-builds/speeding-up-builds#using_a_cached_docker_image
The easiest way to increase the speed of your Docker image build is by specifying a cached image that can be used for subsequent builds. You can specify the cached image by adding the –cache-from argument in your build config file, which will instruct Docker to build using that image as a cache source.
You are using Cloud Build to build and test application source code stored in Cloud Source Repositories. The build process requires a build tool not available in the Cloud Build environment.
What should you do?
- A . Download the binary from the internet during the build process.
- B . Build a custom cloud builder image and reference the image in your build steps.
- C . Include the binary in your Cloud Source Repositories repository and reference it in your build scripts.
- D . Ask to have the binary added to the Cloud Build environment by filing a feature request against the Cloud Build public Issue Tracker.
You are using Cloud Build to build and test application source code stored in Cloud Source Repositories. The build process requires a build tool not available in the Cloud Build environment.
What should you do?
- A . Download the binary from the internet during the build process.
- B . Build a custom cloud builder image and reference the image in your build steps.
- C . Include the binary in your Cloud Source Repositories repository and reference it in your build scripts.
- D . Ask to have the binary added to the Cloud Build environment by filing a feature request against the Cloud Build public Issue Tracker.
Your company wants to expand their users outside the United States for their popular application. The
company wants to ensure 99.999% availability of the database for their application and also wants to minimize the read latency for their users across the globe.
Which two actions should they take? (Choose two.)
- A . Create a multi-regional Cloud Spanner instance with "nam-asia-eur1" configuration.
- B . Create a multi-regional Cloud Spanner instance with "nam3" configuration.
- C . Create a cluster with at least 3 Spanner nodes.
- D . Create a cluster with at least 1 Spanner node.
- E . Create a minimum of two Cloud Spanner instances in separate regions with at least one node.
- F . Create a Cloud Dataflow pipeline to replicate data across different databases.
You are developing a microservice-based application that will run on Google Kubernetes Engine (GKE). Some of the services need to access different Google Cloud APIs.
How should you set up authentication of these services in the cluster following Google-recommended best practices? (Choose two.)
- A . Use the service account attached to the GKE node.
- B . Enable Workload Identity in the cluster via the gcloud command-line tool.
- C . Access the Google service account keys from a secret management service.
- D . Store the Google service account keys in a central secret management service.
- E . Use gcloud to bind the Kubernetes service account and the Google service account using roles/iam.workloadIdentity.
BE
Explanation:
https://cloud.google.com/kubernetes-engine/docs/how-to/workload-identity
Your company’s product team has a new requirement based on customer demand to autoscale your stateless and distributed service running in a Google Kubernetes Engine (GKE) duster. You want to find a solution that minimizes changes because this feature will go live in two weeks.
What should you do?
- A . Deploy a Vertical Pod Autoscaler, and scale based on the CPU load.
- B . Deploy a Vertical Pod Autoscaler, and scale based on a custom metric.
- C . Deploy a Horizontal Pod Autoscaler, and scale based on the CPU toad.
- D . Deploy a Horizontal Pod Autoscaler, and scale based on a custom metric.
C
Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/horizontalpodautoscaler
The Horizontal Pod Autoscaler changes the shape of your Kubernetes workload by automatically increasing or decreasing the number of Pods in response to the workload’s CPU or memory consumption, or in response to custom metrics reported from within Kubernetes or external metrics from sources outside of your cluster.
Your team is building an application for a financial institution. The application’s frontend runs on
Compute Engine, and the data resides in Cloud SQL and one Cloud Storage bucket. The application
will collect data containing PII, which will be stored in the Cloud SQL database and the Cloud Storage
bucket. You need to secure the PII data.
What should you do?
- A . 1) Create the relevant firewall rules to allow only the frontend to communicate with the Cloud SQL database
2) Using IAM, allow only the frontend service account to access the Cloud Storage bucket - B . 1) Create the relevant firewall rules to allow only the frontend to communicate with the Cloud SQL database
2) Enable private access to allow the frontend to access the Cloud Storage bucket privately - C . 1) Configure a private IP address for Cloud SQL
2) Use VPC-SC to create a service perimeter
3) Add the Cloud SQL database and the Cloud Storage bucket to the same service perimeter - D . 1) Configure a private IP address for Cloud SQL
2) Use VPC-SC to create a service perimeter
3) Add the Cloud SQL database and the Cloud Storage bucket to different service perimeters