Updated Google Professional-Cloud-Architect Dumps – Check Free Professional-Cloud-Architect Exam Dumps (2026)
Updated Professional-Cloud-Architect exam with Google Real Exam Questions
What It Is to Be Google Professional Cloud Architect Certified?
Earning this certificate allows an individual to gain an expert-like understanding of concepts like building the cloud solution architecture and its end-to-end implementation, managing and provisioning the cloud solution infrastructure, and security & compliance of Google cloud.
Accredited professionals are well-versed in everything related to enterprise cloud strategy, architecture planning, and solution designing. They are known to be proficient in the development of methodologies and best practices that are needed for multiple cloud or hybrid environments.
NEW QUESTION # 73
You are working in a highly secured environment where public Internet access from the Compute Engine VMs is not allowed. You do not yet have a VPN connection to access an on-premises file server. You need to install specific software on a Compute Engine instance. How should you install the software?
- A. Upload the required installation files to Cloud Source Repositories and use firewall rules to block all traffic except the IP address range for Cloud Source Repositories. Download the files to the VM using gsutil.
- B. Upload the required installation files to Cloud Source Repositories. Configure the VM on a subnet with a Private Google Access subnet. Assign only an internal IP address to the VM. Download the installation files to the VM using gcloud.
- C. Upload the required installation files to Cloud Storage and use firewall rules to block all traffic except the IP address range for Cloud Storage. Download the files to the VM using gsutil.
- D. Upload the required installation files to Cloud Storage. Configure the VM on a subnet with a Private Google Access subnet. Assign only an internal IP address to the VM. Download the installation files to the VM using gsutil.
Answer: D
Explanation:
Reference:
https://cloud.google.com/vpc/docs/private-access-options#pga-supported
NEW QUESTION # 74
Your customer runs a web service used by e-commerce sites to offer product recommendations to users. The company has begun experimenting with a machine learning model on Google Cloud Platform to improve the quality of results.
What should the customer do to improve their model's results over time?
- A. Save a history of recommendations and results of the recommendations in BigQuery, to be used as training data.
- B. Export Cloud Machine Learning Engine performance metrics from Stackdriver to BigQuery, to be used to analyze the efficiency of the model.
- C. Build a roadmap to move the machine learning model training from Cloud GPUs to Cloud TPUs, which offer better results.
- D. Monitor Compute Engine announcements for availability of newer CPU architectures, and deploy the model to them as soon as they are available for additional performance.
Answer: A
Explanation:
Explanation
https://cloud.google.com/solutions/building-a-serverless-ml-model
NEW QUESTION # 75
You are deploying an application on App Engine that needs to integrate with an on-premises database. For security purposes, your on-premises database must not be accessible through the public Internet. What should you do?
- A. Deploy your application on App Engine standard environment and use Cloud VPN to limit access to the onpremises database.
- B. Deploy your application on App Engine flexible environment and use App Engine firewall rules to limit access to the on-premises database.
- C. Deploy your application on App Engine standard environment and use App Engine firewall rules to limit access to the open on-premises database.
- D. Deploy your application on App Engine flexible environment and use Cloud VPN to limit access to the onpremises database.
Answer: C
NEW QUESTION # 76
Your company wants to track whether someone is present in a meeting room reserved for a scheduled meeting. There are 1000 meeting rooms across 5 offices on 3 continents. Each room is equipped with a motion sensor that reports its status every second. You want to support the data upload and collection needs of this sensor network. The receiving infrastructure needs to account for the possibility that the devices may have inconsistent connectivity. Which solution should you design?
- A. Have devices poll for connectivity to Cloud SQL and insert the latest messages on a regular interval to a device specific table.
- B. Have each device create a persistent connection to a Compute Engine instance and write messages to a custom application.
- C. Have devices create a persistent connection to an App Engine application fronted by Cloud Endpoints, which ingest messages and write them to Cloud Datastore.
- D. Have devices poll for connectivity to Cloud Pub/Sub and publish the latest messages on a regular interval to a shared topic for all devices.
Answer: D
Explanation:
A is not correct because having a persistent connection does not handle the case where the device is disconnected.
B is not correct because Cloud SQL is a relational database and not the best fit for sensor data.
Additionally, the frequency of the writes has the potential to exceed the supported number of concurrent connections.
C is correct because Cloud Pub/Sub can handle the frequency of this data, and consumers of the data can pull from the shared topic for further processing.
D is not correct because having a persistent connection does not handle the case where the device is disconnected.
https://cloud.google.com/sql/
https://cloud.google.com/pubsub/
NEW QUESTION # 77
Your company has a support ticketing solution that uses App Engine Standard. The project that contains the App Engine application already has a Virtual Private Cloud (VPC) network fully connected to the company's on-premises environment through a Cloud VPN tunnel. You want to enable the App Engine application to communicate with a database that is running in the company's on-premises environment. What should you do?
- A. Configure private Google access for on-premises hosts only.
- B. Configure private services access.
- C. Configure serverless VPC access.
- D. Configure private Google access.
Answer: C
Explanation:
https://cloud.google.com/vpc/docs/serverless-vpc-access#use_cases
NEW QUESTION # 78
For this question, refer to the TerramEarth case study.
To speed up data retrieval, more vehicles will be upgraded to cellular connections and be able to transmit data to the ETL process. The current FTP process is error-prone and restarts the data transfer from the start of the file when connections fail, which happens often. You want to improve the reliability of the solution and minimize data transfer time on the cellular connections. What should you do?
- A. Directly transfer the files to different Google Cloud Multi-Regional Storage bucket locations in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process using the data in the bucket.
- B. Directly transfer the files to a different Google Cloud Regional Storage bucket location in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process to retrieve the data from each Regional bucket.
- C. Use one Google Container Engine cluster of FTP servers. Save the data to a Multi-Regional bucket. Run the ETL process using data in the bucket.
- D. Use multiple Google Container Engine clusters running FTP servers located in different regions. Save the data to Multi-Regional buckets in us, eu, and asia. Run the ETL process using the data in the bucket.
Answer: B
Explanation:
Explanation
https://cloud.google.com/storage/docs/locations
NEW QUESTION # 79
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. A Compute Engine autoscaling managed instance group and Cloud Bigtable
- B. Cloud Run and Cloud Bigtable
- C. Cloud Run and BigQuery
- D. A Compute Engine autoscaling managed instance group and BigQuery
Answer: B
Explanation:
Explanation
https://cloud.google.com/run/docs/about-instance-autoscaling
https://cloud.google.com/blog/topics/developers-practitioners/bigtable-vs-bigquery-whats-difference
NEW QUESTION # 80
An application development team believes their current logging tool will not meet their needs for their new cloud-based product. They want a better tool to capture errors and help them analyze their historical log data.
You want to help them find a solution that meets their needs.
What should you do?
- A. Help them define their requirements and assess viable logging tools
- B. Direct them to download and install the Google StackDriver logging agent
- C. Help them upgrade their current tool to take advantage of any new features
- D. Send them a list of online resources about logging best practices
Answer: B
Explanation:
The Stackdriver Logging agent streams logs from your VM instances and from selected third party software packages to Stackdriver Logging. Using the agent is optional but we recommend it. The agent runs under both Linux and Microsoft Windows.
Note: Stackdriver Logging allows you to store, search, analyze, monitor, and alert on log data and events from Google Cloud Platform and Amazon Web Services (AWS). Our API also allows ingestion of any custom log data from any source. Stackdriver Logging is a fully managed service that performs at scale and can ingest application and system log data from thousands of VMs. Even better, you can analyze all that log data in real time.
Reference: https://cloud.google.com/logging/docs/agent/installation
https://medium.com/google-cloud/hidden-super-powers-of-stackdriver-logging-ca110dae7e74
NEW QUESTION # 81
For this question, refer to the TerramEarth case study. To be compliant with European GDPR regulation, TerramEarth is required to delete data generated from its European customers after a period of 36 months when it contains personal data. In the new architecture, this data will be stored in both Cloud Storage and BigQuery. What should you do?
- A. Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.
- B. Create a BigQuery time-partitioned table for the European data, and set the partition expiration period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.
- C. Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action when with an Age condition of 36 months.
- D. Create a BigQuery time-partitioned table for the European data, and set the partition period to 36 months.
For Cloud Storage, use gsutil to create a SetStorageClass to NONE action with an Age condition of 36 months.
Answer: A
NEW QUESTION # 82
Your company is planning to upload several important files to Cloud Storage. After the upload is completed, they want to verify that the upload content is identical to what they have on- premises. You want to minimize the cost and effort of performing this check. What should you do?
- A. 1)Use gsutil -m to upload all the files to Cloud Storage.
2)Use gsutil hash -c FILE_NAME to generate CRC32C hashes of all on-premises files
3)Use gsutil ls -L gs://[YOUR_BUCKET_NAME] to collect CRC32C hashes of the uploaded files
4)Compare the hashes - B. 1) Use Linux shasum to compute a digest of files you want to upload
2) Use gsutil -m to upload all the files to the Cloud Storage
3) Use gsutil cp to download the uploaded files
4) Use Linux shasum to compute a digest of the downloaded files 5.Compre the hashes - C. 1) Use gsutil -m to upload all the files to Cloud Storage.
2) Develop a custom Java application that computes CRC32C hashes
3) Use gsutil ls -L gs://[YOUR_BUCKET_NAME] to collect CRC32C hashes of the uploaded files
4)Compare the hashes - D. 1) Use gsutil -m to upload all the files to Cloud Storage.
2) Use gsutil cp to download the uploaded files
3) Use Linux diff to compare the content of the files
Answer: A
Explanation:
Explanation
https://cloud.google.com/storage/docs/gsutil/commands/hash
NEW QUESTION # 83
For this question, refer to the Helicopter Racing League (HRL) case study. Your team is in charge of creating a payment card data vault for card numbers used to bill tens of thousands of viewers, merchandise consumers, and season ticket holders. You need to implement a custom card tokenization service that meets the following requirements:
* It must provide low latency at minimal cost.
* It must be able to identify duplicate credit cards and must not store plaintext card numbers.
* It should support annual key rotation.
Which storage approach should you adopt for your tokenization service?
- A. Store the card data in Secret Manager after running a query to identify duplicates.
- B. Encrypt the card data with a deterministic algorithm and shard it across multiple Memorystore instances.
- C. Use column-level encryption to store the data in Cloud SQL.
- D. Encrypt the card data with a deterministic algorithm stored in Firestore using Datastore mode.
Answer: D
NEW QUESTION # 84
For this question, refer to the Mountkirk Games case study. You are in charge of the new Game Backend Platform architecture. The game communicates with the backend over a REST API.
You want to follow Google-recommended practices. How should you design the backend?
- A. Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L4 load balancer.
- B. Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L7 load balancer.
- C. Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L4 load balancer.
- D. Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L7 load balancer.
Answer: B
Explanation:
Reference:
https://cloud.google.com/solutions/gaming/cloud-game-infrastructure#dedicated_game_server
NEW QUESTION # 85
Case Study: 2 - TerramEarth Case Study
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries: About
80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in 100 countries. Their mission is to build products that make their customers more productive.
Company Background
TerramEarth formed in 1946, when several small, family owned companies combined to retool after World War II. The company cares about their employees and customers and considers them to be extended members of their family.
TerramEarth is proud of their ability to innovate on their core products and find new markets as their customers' needs change. For the past 20 years trends in the industry have been largely toward increasing productivity by using larger vehicles with a human operator.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second.
Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced.
The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second, with 22 hours of operation per day.
TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux-based systems that reside in a data center. These systems gzip CSV files from the field and upload via FTP, transform and aggregate them, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
- Decrease unplanned vehicle downtime to less than 1 week, without
increasing the cost of carrying surplus inventory
- Support the dealer network with more data on how their customers use
their equipment IP better position new products and services.
- Have the ability to partner with different companies-especially with
seed and fertilizer suppliers in the fast-growing agricultural
business-to create compelling joint offerings for their customers
CEO Statement
We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of our customers. Technological change is occurring rapidly and TerramEarth has taken advantage of connected devices technology to provide our customers with better services, such as our intelligent farming equipment. With this technology, we have been able to increase farmers' yields by 25%, by using past trends to adjust how our vehicles operate. These advances have led to the rapid growth of our agricultural product line, which we expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process with our ability to build better vehicles for tower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. Unfortunately, our CEO doesn't take technology obsolescence seriously and he considers the many new companies in our industry to be niche players. My goals are to build our skills while addressing immediate market needs through incremental innovations.
For this question, refer to the TerramEarth case study. TerramEarth has equipped unconnected trucks with servers and sensors to collet telemetry dat
- A. Push the telemetry data in Real-time to a streaming dataflow job that compresses the data, and store it in Google BigQuery.
- B. Have the vehicle' computer compress the data in hourly snapshots, and store it in a Google Cloud storage (GCS) Nearline bucket.
- C. Next year they want to use the data to train machine learning models. They want to store this data in the cloud while reducing costs. What should they do?
- D. Have the vehicle's computer compress the data in hourly snapshots, a Store it in a GCS Coldline bucket.
- E. Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Cloud Bigtable.
Answer: E
Explanation:
Storage is the best choice for data that you plan to access at most once a year, due to its slightly lower availability, 90-day minimum storage duration, costs for data access, and higher per- operation costs. For example:
Cold Data Storage - Infrequently accessed data, such as data stored for legal or regulatory reasons, can be stored at low cost as Coldline Storage, and be available when you need it.
Disaster recovery - In the event of a disaster recovery event, recovery time is key. Cloud Storage provides low latency access to data stored as Coldline Storage.
References: https://cloud.google.com/storage/docs/storage-classes
NEW QUESTION # 86
Mountkirk Games wants to set up a continuous delivery pipeline. Their architecture includes many small services that they want to be able to update and roll back quickly. Mountkirk Games has the following requirements:
* Services are deployed redundantly across multiple regions in the US and Europe
* Only frontend services are exposed on the public internet
* They can provide a single frontend IP for their fleet of services
* Deployment artifacts are immutable
Which set of products should they use?
- A. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
- B. Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager
- C. Google Cloud Storage, Google App Engine, Google Network Load Balancer
- D. Google Kubernetes Registry, Google Container Engine, Google HTTP(S) Load Balancer
Answer: D
NEW QUESTION # 87
You have created several preemptible Linux virtual machine instances using Google Compute Engine. You want to properly shut down your application before the virtual machines are preempted. What should you do?
- A. Create a shutdown script, registered as a xinetd service in Linux, and use the gcloud compute instances add-metadata command to specify the service URL as the value for a new metadata entry with the key shutdown-script-url
- B. Create a shutdown script registered as a xinetd service in Linux and configure a Stackdnver endpoint check to call the service.
- C. Create a shutdown script named k99.shutdown in the /etc/rc.6.d/ directory.
- D. Create a shutdown script and use it as the value for a new metadata entry with the key shutdown-script in the Cloud Platform Console when you create the new virtual machine instance.
Answer: D
NEW QUESTION # 88
For this question, refer to the Dress4Win case study.
As part of their new application experience, Dress4Wm allows customers to upload images of themselves.
The customer has exclusive control over who may view these images. Customers should be able to upload images with minimal latency and also be shown their images quickly on the main application page when they log in. Which configuration should Dress4Win use?
- A. Store image files in a Google Cloud Storage bucket. Add custom metadata to the uploaded images in Cloud Storage that contains the customer's unique ID.
- B. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Assign each customer a unique ID, which sets each file's owner attribute, ensuring privacy of images.
- C. Store image files in a Google Cloud Storage bucket. Use Google Cloud Datastore to maintain metadata that maps each customer's ID and their image files.
- D. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Use a Google Cloud SQL database to maintain metadata that maps each customer's ID to their image files.
Answer: C
NEW QUESTION # 89
You are designing a large distributed application with 30 microservices. Each of your distributed microservices needs to connect to a database back-end. You want to store the credentials securely. Where should you store the credentials?
- A. In an environment variable
- B. In the source code
- C. In a secret management system
- D. In a config file that has restricted access through ACLs
Answer: A
NEW QUESTION # 90
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The Google Certified Professional - Cloud Architect (GCP) certification is intended for individuals who have experience working with cloud architecture and Google Cloud Platform, including cloud architects, solution architects, infrastructure architects, and cloud developers. It is also suitable for professionals who work with cloud technologies and want to enhance their knowledge and skills in designing and managing cloud solutions.
Google Professional-Cloud-Architect certification is a valuable credential for IT professionals and cloud architects who want to demonstrate their expertise in designing, developing, and managing cloud solutions using GCP. Google Certified Professional - Cloud Architect (GCP) certification exam covers a range of topics and is designed to evaluate the candidate's ability to design and deploy scalable, reliable, and cost-effective cloud solutions that meet the needs of their organization.
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