Google Professional Cloud Architect Practice Exams
Last updated on Oct 22,2026- Exam Code: Professional Cloud Architect
- Exam Name: Google Certified Professional – Cloud Architect (GCP)
- Certification Provider: Google
- Latest update: Oct 22,2026
You are implementing the infrastructure for a web service on Google Cloud. The web service needs to receive and store the data from 500,000 requests per second. The data will be queried later in real time, based on exact matches of a known set of attributes. There will be periods where the web service will not receive any requests. The business wants to keep costs low.
Which web service platform and database should you use for the application?
- A . Cloud Run and BigQuery
- B . Cloud Run and Cloud Bigtable
- C . A Compute Engine autoscaling managed instance group and BigQuery
- D . A Compute Engine autoscaling managed instance group and Cloud Bigtable
B
Explanation:
https://cloud.google.com/run/docs/about-instance-autoscaling
https://cloud.google.com/blog/topics/developers-practitioners/bigtable-vs-bigquery-whats-difference
You are implementing the infrastructure for a web service on Google Cloud. The web service needs to receive and store the data from 500,000 requests per second. The data will be queried later in real time, based on exact matches of a known set of attributes. There will be periods where the web service will not receive any requests. The business wants to keep costs low.
Which web service platform and database should you use for the application?
- A . Cloud Run and BigQuery
- B . Cloud Run and Cloud Bigtable
- C . A Compute Engine autoscaling managed instance group and BigQuery
- D . A Compute Engine autoscaling managed instance group and Cloud Bigtable
B
Explanation:
https://cloud.google.com/run/docs/about-instance-autoscaling
https://cloud.google.com/blog/topics/developers-practitioners/bigtable-vs-bigquery-whats-difference
Use App Engine default credentials to sign requests against Cloud Storage.
You company has a Kubernetes application that pulls messages from Pub/Sub and stores them in Firestore. Because the application is simple, it was deployed as a single pod. The infrastructure team has analyzed Pub/Sub metrics and discovered that the application cannot process the messages in real time. Most of them wait for minutes before being processed. You need to scale the elaboration process that is I/O-intensive.
What should you do?
- A . Configure a Kubernetes autoscaling based on the subscription/push_request metric.
- B . Use the Cenable- autoscaling flag when you create the Kubernetes cluster
- C . Configure a Kubernetes autoscaling based on the subscription/num_undelivered message metric.
- D . Use kubectl autoscale deployment APP_NAME Cmax 6 Cmin 2 Ccpu- percent 50 to configure Kubernetes autoscaling deployment
A
Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/custom-and-external-metrics#external_metrics
For this question, refer to the Mountkirk Games case study.
Mountkirk Games’ gaming servers are not automatically scaling properly. Last month, they rolled out a new feature, which suddenly became very popular. A record number of users are trying to use the service, but many of them are getting 503 errors and very slow response times.
What should they investigate first?
- A . Verify that the database is online.
- B . Verify that the project quota hasn’t been exceeded.
- C . Verify that the new feature code did not introduce any performance bugs.
- D . Verify that the load-testing team is not running their tool against production.
B
Explanation:
503 is service unavailable error. If the database was online everyone would get the 503 error. https://cloud.google.com/docs/quota#capping_usage
Your company’s test suite is a custom C++ application that runs tests throughout each day on Linux virtual machines. The full test suite takes several hours to complete, running on a limited number of on premises servers reserved for testing. Your company wants to move the testing infrastructure to the cloud, to reduce the amount of time it takes to fully test a change to the system, while changing the tests as little as possible.
Which cloud infrastructure should you recommend?
- A . Google Compute Engine unmanaged instance groups and Network Load Balancer
- B . Google Compute Engine managed instance groups with auto-scaling
- C . Google Cloud Dataproc to run Apache Hadoop jobs to process each test
- D . Google App Engine with Google Stackdriver for logging
B
Explanation:
https://cloud.google.com/compute/docs/instance-groups/
Google Compute Engine enables users to launch virtual machines (VMs) on demand. VMs can be launched from the standard images or custom images created by users.
Managed instance groups offer autoscaling capabilities that allow you to automatically add or remove instances from a managed instance group based on increases or decreases in load. Autoscaling helps your applications gracefully handle increases in traffic and reduces cost when the need for resources is lower.
For this question, refer to the Mountkirk Games case study.
Mountkirk Games wants to set up a real-time analytics platform for their new game. The new platform must meet their technical requirements.
Which combination of Google technologies will meet all of their requirements?
- A . Container Engine, Cloud Pub/Sub, and Cloud SQL
- B . Cloud Dataflow, Cloud Storage, Cloud Pub/Sub, and BigQuery
- C . Cloud SQL, Cloud Storage, Cloud Pub/Sub, and Cloud Dataflow
- D . Cloud Dataproc, Cloud Pub/Sub, Cloud SQL, and Cloud Dataflow
- E . Cloud Pub/Sub, Compute Engine, Cloud Storage, and Cloud Dataproc
B
Explanation:
A real time requires Stream / Messaging so Pub/Sub, Analytics by Big Query.
Ingest millions of streaming events per second from anywhere in the world with Cloud Pub/Sub, powered by Google’s unique, high-speed private network. Process the streams with Cloud Dataflow to ensure reliable, exactly-once, low-latency data transformation. Stream the transformed data into BigQuery, the cloud-native data warehousing service, for immediate analysis via SQL or popular visualization tools.
From scenario: They plan to deploy the game’s backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics.
Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity
Process incoming data on the fly directly from the game servers
Process data that arrives late because of slow mobile networks
Allow SQL queries to access at least 10 TB of historical data
Process files that are regularly uploaded by users’ mobile devices
Use only fully managed services
Reference: https://cloud.google.com/solutions/big-data/stream-analytics/
Your company acquired a healthcare startup and must retain its customers’ medical information for up to 4 more years, depending on when it was created. Your corporate policy is to securely retain this data, and then delete it as soon as regulations allow.
Which approach should you take?
- A . Store the data in Google Drive and manually delete records as they expire.
- B . Anonymize the data using the Cloud Data Loss Prevention API and store it indefinitely.
- C . Store the data using the Cloud Storage and use lifecycle management to delete files when they expire.
- D . Store the data in Cloud Storage and run a nightly batch script that deletes all expired datA.
C
Explanation:
https://cloud.google.com/storage/docs/lifecycle
Your company has announced that they will be outsourcing operations functions. You want to allow developers to easily stage new versions of a cloud-based application in the production environment and allow the outsourced operations team to autonomously promote staged versions to production. You want to minimize the operational overhead of the solution.
Which Google Cloud product should you migrate to?
- A . App Engine
- B . GKE On-Prem
- C . Compute Engine
- D . Google Kubernetes Engine
D
Explanation:
Reference: https://cloud.google.com/security/compliance/eba-outsourcing-mapping-gcp
Your web application uses Google Kubernetes Engine to manage several workloads. One workload requires a consistent set of hostnames even after pod scaling and relaunches.
Which feature of Kubernetes should you use to accomplish this?
- A . StatefulSets
- B . Role-based access control
- C . Container environment variables
- D . Persistent Volumes
A
Explanation:
https://kubernetes.io/docs/tutorials/stateful-application/basic-stateful-set/