Google Professional Cloud Developer Practice Exams
Last updated on Oct 24,2026- Exam Code: Professional Cloud Developer
- Exam Name: Professional Cloud Developer
- Certification Provider: Google
- Latest update: Oct 24,2026
Your application requires service accounts to be authenticated to GCP products via credentials stored on its host Compute Engine virtual machine instances. You want to distribute these credentials to the host instances as securely as possible.
What should you do?
- A . Use HTTP signed URLs to securely provide access to the required resources.
- B . Use the instance’s service account Application Default Credentials to authenticate to the required resources.
- C . Generate a P12 file from the GCP Console after the instance is deployed, and copy the credentials to the host instance before starting the application.
- D . Commit the credential JSON file into your application’s source repository, and have your CI/CD process package it with the software that is deployed to the instance.
B
Explanation:
Reference: https://cloud.google.com/compute/docs/api/how-tos/authorization
Your team develops services that run on Google Kubernetes Engine. You need to standardize their log data using Google-recommended practices and make the data more useful in the fewest number of steps.
What should you do? (Choose two.)
- A . Create aggregated exports on application logs to BigQuery to facilitate log analytics.
- B . Create aggregated exports on application logs to Cloud Storage to facilitate log analytics.
- C . Write log output to standard output (stdout) as single-line JSON to be ingested into Cloud Logging as structured logs.
- D . Mandate the use of the Logging API in the application code to write structured logs to Cloud Logging.
- E . Mandate the use of the Pub/Sub API to write structured data to Pub/Sub and create a Dataflow streaming pipeline to normalize logs and write them to BigQuery for analytics.
AC
Explanation:
https://cloud.google.com/stackdriver/docs/solutions/gke/managing-logs#best_practices
Set up a VPN connection between the two projects. Configure Cloud Run to use the connector to access the VM hosting PostgreSQL
Explanation:
https://cloud.google.com/sql/docs/postgres/connect-run#private-ip
Your application is composed of a set of loosely coupled services orchestrated by code executed on Compute Engine. You want your application to easily bring up new Compute Engine instances that find and use a specific version of a service.
How should this be configured?
- A . Define your service endpoint information as metadata that is retrieved at runtime and used to connect to the desired service.
- B . Define your service endpoint information as label data that is retrieved at runtime and used to connect to the desired service.
- C . Define your service endpoint information to be retrieved from an environment variable at runtime and used to connect to the desired service.
- D . Define your service to use a fixed hostname and port to connect to the desired service. Replace the service at the endpoint with your new version.
A
Explanation:
https://cloud.google.com/service-infrastructure/docs/service-metadata/reference/rest#service-endpoint
Your application is composed of a set of loosely coupled services orchestrated by code executed on Compute Engine. You want your application to easily bring up new Compute Engine instances that find and use a specific version of a service.
How should this be configured?
- A . Define your service endpoint information as metadata that is retrieved at runtime and used to connect to the desired service.
- B . Define your service endpoint information as label data that is retrieved at runtime and used to connect to the desired service.
- C . Define your service endpoint information to be retrieved from an environment variable at runtime and used to connect to the desired service.
- D . Define your service to use a fixed hostname and port to connect to the desired service. Replace the service at the endpoint with your new version.
A
Explanation:
https://cloud.google.com/service-infrastructure/docs/service-metadata/reference/rest#service-endpoint
Your company needs a database solution that stores customer purchase history and meets the following requirements:
– Customers can query their purchase immediately after submission.
– Purchases can be sorted on a variety of fields.
– Distinct record formats can be stored at the same time.
Which storage option satisfies these requirements?
- A . Firestore in Native mode
- B . Cloud Storage using an object read
- C . Cloud SQL using a SQL SELECT statement
- D . Firestore in Datastore mode using a global query
You want to use the Stackdriver Logging Agent to send an application’s log file to Stackdriver from a Compute Engine virtual machine instance.
After installing the Stackdriver Logging Agent, what should you do first?
- A . Enable the Error Reporting API on the project.
- B . Grant the instance full access to all Cloud APIs.
- C . Configure the application log file as a custom source.
- D . Create a Stackdriver Logs Export Sink with a filter that matches the application’s log entries.
For this question, refer to the HipLocal case study.
Which Google Cloud product addresses HipLocal’s business requirements for service level indicators and objectives?
- A . Cloud Profiler
- B . Cloud Monitoring
- C . Cloud Trace
- D . Cloud Logging
B
Explanation:
https://cloud.google.com/stackdriver/docs/solutions/slo-monitoring#defn-sli
You are developing a marquee stateless web application that will run on Google Cloud. The rate of the incoming user traffic is expected to be unpredictable, with no traffic on some days and large spikes on other days. You need the application to automatically scale up and down, and you need to minimize the cost associated with running the application.
What should you do?
- A . Build the application in Python with Firestore as the database. Deploy the application to Cloud Run.
- B . Build the application in C# with Firestore as the database. Deploy the application to App Engine flexible environment.
- C . Build the application in Python with CloudSQL as the database. Deploy the application to App Engine standard environment.
- D . Build the application in Python with Firestore as the database. Deploy the application to a Compute Engine managed instance group with autoscaling.
You are developing an application that consists of several microservices running in a Google Kubernetes Engine cluster. One microservice needs to connect to a third-party database running on-premises. You need to store credentials to the database and ensure that these credentials can be rotated while following security best practices.
What should you do?
- A . Store the credentials in a sidecar container proxy, and use it to connect to the third-party database.
- B . Configure a service mesh to allow or restrict traffic from the Pods in your microservice to the database.
- C . Store the credentials in an encrypted volume mount, and associate a Persistent Volume Claim with the client Pod.
- D . Store the credentials as a Kubernetes Secret, and use the Cloud Key Management Service plugin to handle encryption and decryption.
D
Explanation:
https://cloud.google.com/kubernetes-engine/docs/how-to/encrypting-secrets
By default, Google Kubernetes Engine (GKE) encrypts customer content stored at rest, including Secrets. GKE handles and manages this default encryption for you without any additional action on your part.
Application-layer secrets encryption provides an additional layer of security for sensitive data, such as Secrets, stored in etcd. Using this functionality, you can use a key managed with Cloud KMS to encrypt data at the application layer. This encryption protects against attackers who gain access to an offline copy of etcd.