
Google Certified Professional - Cloud Architect (GCP) - Professional-Cloud-Architect Exam Questions
QUESTION NO: 1
Case Study: 12 - Altostrat Media
Company Overview
Altostrat is a prominent player in the media industry, with an extensive collection of audio and video content that comprises podcasts, interviews, news broadcasts, and documentaries. Their success in delivering premium content to a diverse audience requires a content management system that can keep pace with the dynamic media landscape.
Solution Concept
Altostrat seeks to modernize its content management and user engagement strategies using Google Cloud's generative AI. They want a platform that empowers customers with personalized recommendations, natural language interactions and seamless self-service support.
Simultaneously, they want to drive revenue growth through dynamic pricing targeted marketing, and personalized product suggestions.
The seamless integration of AI-powered tools into the existing Google Cloud environment will enable Altostrat to efficiently manage their vast media library, enhance user experiences, and unlock new revenue streams. Google Cloud's generative AI will solidify their leadership in the media industry.
Existing Technical Environment
Altostrat's content management and delivery platform leverages GKE for scalability and high availability, essential for handling their vast media library. Their extensive media library spanning various documents, audio and video formats is stored in Cloud Storage. To gain valuable insights into user behavior, content consumption patterns, and audience demographics, Altostrat leverages BigQuery as their primary data warehouse. Additionally, they use Cloud Run functions for serverless execution of event-driven tasks such as video transcoding metadata extraction, and personalized content recommendations.
While Altostrat has made significant strides in cloud adoption, they also maintain some legacy on- premises systems for specific workflows like content ingestion and archival. These systems are slated for modernization and migration to Google Cloud in the near future. User management and authentication are currently handled through a combination of Google Identity and third-party identity providers. For monitoring and observability, Altostrat relies on a mix of native Google Cloud tools like Cloud Monitoring and open-source solutions like Prometheus, with alerts primarily delivered via email notifications.
Business Requirements
- Accelerate and enhance the reliability of operational workflows across all environments. [Google
Cloud + On-premises]
- Simplify infrastructure management for rapid application deployment.
- Optimize cloud storage costs while maintaining high availability and scalability for media
content.
- Enable natural language interaction with the platform with 24/7 user support.
- Automatically generate concise summaries of media content.
- Extract rich metadata from media assets using NLP and computer vision.
- Detect and filter inappropriate content.
- Analyze media content to identify trends and extract insights.
- Inform content strategy and decision making with data.
Technical Requirements
- Modernize CI/CD for containerized deployments with a centralized management platform.
- Secure, high-performance hybrid cloud connectivity for data ingestion.
- Provide scalable, performant kubernetes environments both on-premises and in the cloud.
- Optimize cloud storage costs for growing media volumes.
- Design AI-powered detection of harmful content.
- Ensure that AI systems are auditable and their decisions can be explained.
- Leverage LLMs and conversational AI for personalized experiences and content virality.
- Develop advanced chatbots with natural language understanding to provide personalized
assistance.
- Automated summarization for diverse media.
Executive Statement
At Altostrat, we are embracing the next frontier of artificial intelligence to revolutionize our content strategy. By harnessing the power of generative AI, we will create an unparalleled user experience by empowering our audience with intelligent toots for content discovery, personalized recommendations, and seamless interaction. Reliability and cost management are our top priorities. This strategic initiative will deepen engagement, foster customer loyalty, and unlock new revenue streams through targeted marketing and tailored content offerings. We see a future where Al-driven innovation is central to our business, leading to greater success for our company and delivering exceptional value to our customers.
For this question, refer to the Altostrat Media case study. Altostrat is concerned about sophisticated, multi-vector Distributed Denial of Service (DDoS) attacks targeting various layers of their infrastructure. DDoS attacks could potentially disrupt video streaming and cause financial losses. You need to mitigate this risk. What should you do?
Case Study: 12 - Altostrat Media
Company Overview
Altostrat is a prominent player in the media industry, with an extensive collection of audio and video content that comprises podcasts, interviews, news broadcasts, and documentaries. Their success in delivering premium content to a diverse audience requires a content management system that can keep pace with the dynamic media landscape.
Solution Concept
Altostrat seeks to modernize its content management and user engagement strategies using Google Cloud's generative AI. They want a platform that empowers customers with personalized recommendations, natural language interactions and seamless self-service support.
Simultaneously, they want to drive revenue growth through dynamic pricing targeted marketing, and personalized product suggestions.
The seamless integration of AI-powered tools into the existing Google Cloud environment will enable Altostrat to efficiently manage their vast media library, enhance user experiences, and unlock new revenue streams. Google Cloud's generative AI will solidify their leadership in the media industry.
Existing Technical Environment
Altostrat's content management and delivery platform leverages GKE for scalability and high availability, essential for handling their vast media library. Their extensive media library spanning various documents, audio and video formats is stored in Cloud Storage. To gain valuable insights into user behavior, content consumption patterns, and audience demographics, Altostrat leverages BigQuery as their primary data warehouse. Additionally, they use Cloud Run functions for serverless execution of event-driven tasks such as video transcoding metadata extraction, and personalized content recommendations.
While Altostrat has made significant strides in cloud adoption, they also maintain some legacy on- premises systems for specific workflows like content ingestion and archival. These systems are slated for modernization and migration to Google Cloud in the near future. User management and authentication are currently handled through a combination of Google Identity and third-party identity providers. For monitoring and observability, Altostrat relies on a mix of native Google Cloud tools like Cloud Monitoring and open-source solutions like Prometheus, with alerts primarily delivered via email notifications.
Business Requirements
- Accelerate and enhance the reliability of operational workflows across all environments. [Google
Cloud + On-premises]
- Simplify infrastructure management for rapid application deployment.
- Optimize cloud storage costs while maintaining high availability and scalability for media
content.
- Enable natural language interaction with the platform with 24/7 user support.
- Automatically generate concise summaries of media content.
- Extract rich metadata from media assets using NLP and computer vision.
- Detect and filter inappropriate content.
- Analyze media content to identify trends and extract insights.
- Inform content strategy and decision making with data.
Technical Requirements
- Modernize CI/CD for containerized deployments with a centralized management platform.
- Secure, high-performance hybrid cloud connectivity for data ingestion.
- Provide scalable, performant kubernetes environments both on-premises and in the cloud.
- Optimize cloud storage costs for growing media volumes.
- Design AI-powered detection of harmful content.
- Ensure that AI systems are auditable and their decisions can be explained.
- Leverage LLMs and conversational AI for personalized experiences and content virality.
- Develop advanced chatbots with natural language understanding to provide personalized
assistance.
- Automated summarization for diverse media.
Executive Statement
At Altostrat, we are embracing the next frontier of artificial intelligence to revolutionize our content strategy. By harnessing the power of generative AI, we will create an unparalleled user experience by empowering our audience with intelligent toots for content discovery, personalized recommendations, and seamless interaction. Reliability and cost management are our top priorities. This strategic initiative will deepen engagement, foster customer loyalty, and unlock new revenue streams through targeted marketing and tailored content offerings. We see a future where Al-driven innovation is central to our business, leading to greater success for our company and delivering exceptional value to our customers.
For this question, refer to the Altostrat Media case study. Altostrat is concerned about sophisticated, multi-vector Distributed Denial of Service (DDoS) attacks targeting various layers of their infrastructure. DDoS attacks could potentially disrupt video streaming and cause financial losses. You need to mitigate this risk. What should you do?
Correct Answer: D
Explanation: Only visible for Pass4Test members. You can sign-up / login (it's free).
QUESTION NO: 2
Your company wants to migrate their 10-TB on-premises database export into Cloud Storage.
You want to minimize the time it takes to complete this activity and the overall cost. The bandwidth between the on-premises environment and Google Cloud is 1 Gbps. You want to follow Google-recommended practices. What should you do?
Your company wants to migrate their 10-TB on-premises database export into Cloud Storage.
You want to minimize the time it takes to complete this activity and the overall cost. The bandwidth between the on-premises environment and Google Cloud is 1 Gbps. You want to follow Google-recommended practices. What should you do?
Correct Answer: B
QUESTION NO: 3
Your ecommerce platform uses a regional Cloud SQL for PostgreSQL database to store critical order information. The business requests a recovery time objective (RTO) of less than 10 minutes and a recovery point objective (RPO) of 2 minutes to ensure business continuity in the event of a full regional outage. You need to design a disaster recovery strategy for the Cloud SQL database that meets the business's strict RTO and RPO requirements. Your design must avoid operational complexity. What should you do?
Your ecommerce platform uses a regional Cloud SQL for PostgreSQL database to store critical order information. The business requests a recovery time objective (RTO) of less than 10 minutes and a recovery point objective (RPO) of 2 minutes to ensure business continuity in the event of a full regional outage. You need to design a disaster recovery strategy for the Cloud SQL database that meets the business's strict RTO and RPO requirements. Your design must avoid operational complexity. What should you do?
Correct Answer: D
Explanation: Only visible for Pass4Test members. You can sign-up / login (it's free).
QUESTION NO: 4
Case Study: 11 - TerramEarth
Company overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. They currently have over 500 dealers and service centers in 100 countries.
Their mission is to build products that make their customers more productive.
Solution concept
There are 2 million TerramEarth vehicles in operation currently, and we see 20% yearly growth.
Vehicles collect telemetry data from many sensors during operation. A small subset of critical data is transmitted from the vehicles in real time to facilitate fleet management. The rest of the sensor data is collected, compressed, and uploaded daily when the vehicles return to home base.
Each vehicle usually generates 200 to 500 megabytes of data per day.
Existing technical environment
TerramEarth's vehicle data aggregation and analysis infrastructure resides in Google Cloud and serves clients from all around the world. A growing amount of sensor data is captured from their two main manufacturing plants and sent to private data centers that contain their legacy inventory and logistics management systems. The private data centers have multiple network interconnects configured to Google Cloud. The web frontend for dealers and customers is running in Google Cloud and allows access to stock management and analytics.
Business requirements
- Predict and detect vehicle malfunction and rapidly ship parts to dealerships for just-in-time repair where possible.
- Decrease cloud operational costs and adapt to seasonality.
- Increase speed and reliability of development workflow.
- Allow remote developers to be productive without compromising code or data security.
- Create a flexible and scalable platform for developers to create custom API services for dealers and partners.
Technical requirements
- Create a new abstraction layer for HTTP API access to their legacy systems to enable a gradual move into the cloud without disrupting operations.
- Modernize all CI/CD pipelines to allow developers to deploy container-based workloads in highly scalable environments.
- Allow developers to run experiments without compromising security and governance requirements.
- Create a self-service portal for internal and partner developers to create new projects, request resources for data analytics jobs, and centrally manage access to the API endpoints.
- Use cloud-native solutions for keys and secrets management and optimize for identity-based access.
- Improve and standardize tools necessary for application and network monitoring and troubleshooting.
Executive statement
Our competitive advantage has always been our focus on the customer, with our ability to provide excellent customer service and minimize vehicle downtimes.
After moving multiple systems into Google Cloud, we are seeking new ways to provide best-in- class online fleet management services to our customers and improve operations of our dealerships. Our 5-year strategic plan is to create a partner ecosystem of new products by enabling access to our data, increasing autonomous operation capabilities of our vehicles, and creating a path to move the remaining legacy systems to the cloud.
You start to build a new application that uses a few Cloud Functions for the backend. One use case requires a Cloud Function func_display to invoke another Cloud Function func_query. You want func_query only to accept invocations from func_display. You also want to follow Google's recommended best practices. What should you do?
Case Study: 11 - TerramEarth
Company overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. They currently have over 500 dealers and service centers in 100 countries.
Their mission is to build products that make their customers more productive.
Solution concept
There are 2 million TerramEarth vehicles in operation currently, and we see 20% yearly growth.
Vehicles collect telemetry data from many sensors during operation. A small subset of critical data is transmitted from the vehicles in real time to facilitate fleet management. The rest of the sensor data is collected, compressed, and uploaded daily when the vehicles return to home base.
Each vehicle usually generates 200 to 500 megabytes of data per day.
Existing technical environment
TerramEarth's vehicle data aggregation and analysis infrastructure resides in Google Cloud and serves clients from all around the world. A growing amount of sensor data is captured from their two main manufacturing plants and sent to private data centers that contain their legacy inventory and logistics management systems. The private data centers have multiple network interconnects configured to Google Cloud. The web frontend for dealers and customers is running in Google Cloud and allows access to stock management and analytics.
Business requirements
- Predict and detect vehicle malfunction and rapidly ship parts to dealerships for just-in-time repair where possible.
- Decrease cloud operational costs and adapt to seasonality.
- Increase speed and reliability of development workflow.
- Allow remote developers to be productive without compromising code or data security.
- Create a flexible and scalable platform for developers to create custom API services for dealers and partners.
Technical requirements
- Create a new abstraction layer for HTTP API access to their legacy systems to enable a gradual move into the cloud without disrupting operations.
- Modernize all CI/CD pipelines to allow developers to deploy container-based workloads in highly scalable environments.
- Allow developers to run experiments without compromising security and governance requirements.
- Create a self-service portal for internal and partner developers to create new projects, request resources for data analytics jobs, and centrally manage access to the API endpoints.
- Use cloud-native solutions for keys and secrets management and optimize for identity-based access.
- Improve and standardize tools necessary for application and network monitoring and troubleshooting.
Executive statement
Our competitive advantage has always been our focus on the customer, with our ability to provide excellent customer service and minimize vehicle downtimes.
After moving multiple systems into Google Cloud, we are seeking new ways to provide best-in- class online fleet management services to our customers and improve operations of our dealerships. Our 5-year strategic plan is to create a partner ecosystem of new products by enabling access to our data, increasing autonomous operation capabilities of our vehicles, and creating a path to move the remaining legacy systems to the cloud.
You start to build a new application that uses a few Cloud Functions for the backend. One use case requires a Cloud Function func_display to invoke another Cloud Function func_query. You want func_query only to accept invocations from func_display. You also want to follow Google's recommended best practices. What should you do?
Correct Answer: A
Explanation: Only visible for Pass4Test members. You can sign-up / login (it's free).
QUESTION NO: 5
A development team at your company has created a dockerized HTTPS web application. You need to deploy the application on Google Kubernetes Engine (GKE) and make sure that the application scales automatically. How should you deploy to GKE?
A development team at your company has created a dockerized HTTPS web application. You need to deploy the application on Google Kubernetes Engine (GKE) and make sure that the application scales automatically. How should you deploy to GKE?
Correct Answer: D
Explanation: Only visible for Pass4Test members. You can sign-up / login (it's free).
QUESTION NO: 6
You created a pipeline that can deploy your source code changes to your infrastructure in instance groups for self-healing. One of the changes negatively affects your key performance indicator. You are not sure how to fix it, and investigation could take up to a week. What should you do?
You created a pipeline that can deploy your source code changes to your infrastructure in instance groups for self-healing. One of the changes negatively affects your key performance indicator. You are not sure how to fix it, and investigation could take up to a week. What should you do?
Correct Answer: C
Explanation: Only visible for Pass4Test members. You can sign-up / login (it's free).
QUESTION NO: 7
Case Study: 3 - JencoMart Case Study
Company Overview
JencoMart is a global retailer with over 10,000 stores in 16 countries. The stores carry a range of goods, such as groceries, tires, and jewelry. One of the company's core values is excellent customer service. In addition, they recently introduced an environmental policy to reduce their carbon output by 50% over the next 5 years.
Company Background
JencoMart started as a general store in 1931, and has grown into one of the world's leading brands known for great value and customer service. Over time, the company transitioned from only physical stores to a stores and online hybrid model, with 25% of sales online. Currently, JencoMart has little presence in Asia, but considers that market key for future growth.
Solution Concept
JencoMart wants to migrate several critical applications to the cloud but has not completed a technical review to determine their suitability for the cloud and the engineering required for migration. They currently host all of these applications on infrastructure that is at its end of life and is no longer supported.
Existing Technical Environment
JencoMart hosts all of its applications in 4 data centers: 3 in North American and 1 in Europe, most applications are dual-homed.
JencoMart understands the dependencies and resource usage metrics of their on-premises architecture.
Application Customer loyalty portal
LAMP (Linux, Apache, MySQL and PHP) application served from the two JencoMart-owned U.S.
data centers.
Database
* Oracle Database stores user profiles
- 20 TB
- Complex table structure
- Well maintained, clean data
- Strong backup strategy
* PostgreSQL database stores user credentials
- Single-homed in US West
- No redundancy
- Backed up every 12 hours
- 100% uptime service level agreement (SLA)
- Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
- Twin, dual core CPUs
- 32GB of RAM
- Twin 250 GB HDD (RAID 1)
* 20 machines in US East Coast, each machine has:
- Single dual-core CPU
- 24 GB of RAM
- Twin 250 GB HDD (RAID 1)
Storage
* Access to shared 100 TB SAN in each location
* Tape backup every week
Business Requirements
* Optimize for capacity during peak periods and value during off-peak periods
* Guarantee service availably and support
* Reduce on-premises footprint and associated financial and environmental impact.
* Move to outsourcing model to avoid large upfront costs associated with infrastructure purchase
* Expand services into Asia.
Technical Requirements
* Assess key application for cloud suitability.
* Modify application for the cloud.
* Move applications to a new infrastructure.
* Leverage managed services wherever feasible
* Sunset 20% of capacity in existing data centers
* Decrease latency in Asia
CEO Statement
JencoMart will continue to develop personal relationships with our customers as more people access the web. The future of our retail business is in the global market and the connection between online and in-store experiences. As a large global company, we also have a responsibility to the environment through 'green' initiatives and polices.
CTO Statement
The challenges of operating data centers prevents focus on key technologies critical to our long- term success. Migrating our data services to a public cloud infrastructure will allow us to focus on big data and machine learning to improve our service customers.
CFO Statement
Since its founding JencoMart has invested heavily in our data services infrastructure. However, because of changing market trends, we need to outsource our infrastructure to ensure our long- term success. This model will allow us to respond to increasing customer demand during peak and reduce costs.
For this question, refer to the JencoMart case study.
The JencoMart security team requires that all Google Cloud Platform infrastructure is deployed using a least privilege model with separation of duties for administration between production and development resources. What Google domain and project structure should you recommend?
Case Study: 3 - JencoMart Case Study
Company Overview
JencoMart is a global retailer with over 10,000 stores in 16 countries. The stores carry a range of goods, such as groceries, tires, and jewelry. One of the company's core values is excellent customer service. In addition, they recently introduced an environmental policy to reduce their carbon output by 50% over the next 5 years.
Company Background
JencoMart started as a general store in 1931, and has grown into one of the world's leading brands known for great value and customer service. Over time, the company transitioned from only physical stores to a stores and online hybrid model, with 25% of sales online. Currently, JencoMart has little presence in Asia, but considers that market key for future growth.
Solution Concept
JencoMart wants to migrate several critical applications to the cloud but has not completed a technical review to determine their suitability for the cloud and the engineering required for migration. They currently host all of these applications on infrastructure that is at its end of life and is no longer supported.
Existing Technical Environment
JencoMart hosts all of its applications in 4 data centers: 3 in North American and 1 in Europe, most applications are dual-homed.
JencoMart understands the dependencies and resource usage metrics of their on-premises architecture.
Application Customer loyalty portal
LAMP (Linux, Apache, MySQL and PHP) application served from the two JencoMart-owned U.S.
data centers.
Database
* Oracle Database stores user profiles
- 20 TB
- Complex table structure
- Well maintained, clean data
- Strong backup strategy
* PostgreSQL database stores user credentials
- Single-homed in US West
- No redundancy
- Backed up every 12 hours
- 100% uptime service level agreement (SLA)
- Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
- Twin, dual core CPUs
- 32GB of RAM
- Twin 250 GB HDD (RAID 1)
* 20 machines in US East Coast, each machine has:
- Single dual-core CPU
- 24 GB of RAM
- Twin 250 GB HDD (RAID 1)
Storage
* Access to shared 100 TB SAN in each location
* Tape backup every week
Business Requirements
* Optimize for capacity during peak periods and value during off-peak periods
* Guarantee service availably and support
* Reduce on-premises footprint and associated financial and environmental impact.
* Move to outsourcing model to avoid large upfront costs associated with infrastructure purchase
* Expand services into Asia.
Technical Requirements
* Assess key application for cloud suitability.
* Modify application for the cloud.
* Move applications to a new infrastructure.
* Leverage managed services wherever feasible
* Sunset 20% of capacity in existing data centers
* Decrease latency in Asia
CEO Statement
JencoMart will continue to develop personal relationships with our customers as more people access the web. The future of our retail business is in the global market and the connection between online and in-store experiences. As a large global company, we also have a responsibility to the environment through 'green' initiatives and polices.
CTO Statement
The challenges of operating data centers prevents focus on key technologies critical to our long- term success. Migrating our data services to a public cloud infrastructure will allow us to focus on big data and machine learning to improve our service customers.
CFO Statement
Since its founding JencoMart has invested heavily in our data services infrastructure. However, because of changing market trends, we need to outsource our infrastructure to ensure our long- term success. This model will allow us to respond to increasing customer demand during peak and reduce costs.
For this question, refer to the JencoMart case study.
The JencoMart security team requires that all Google Cloud Platform infrastructure is deployed using a least privilege model with separation of duties for administration between production and development resources. What Google domain and project structure should you recommend?
Correct Answer: C
Explanation: Only visible for Pass4Test members. You can sign-up / login (it's free).
QUESTION NO: 8
You work in a multinational company that is migrating to Google Cloud. The head office has the largest data center and manages a connection network to offices in various countries around the world. Each country has its own projects to manage the specific procedures of each location, but the management wants to create an integrated organization while maintaining the independence of the projects for the various branches. How do you plan to organize Networking?
You work in a multinational company that is migrating to Google Cloud. The head office has the largest data center and manages a connection network to offices in various countries around the world. Each country has its own projects to manage the specific procedures of each location, but the management wants to create an integrated organization while maintaining the independence of the projects for the various branches. How do you plan to organize Networking?
Correct Answer: A
Explanation: Only visible for Pass4Test members. You can sign-up / login (it's free).
QUESTION NO: 9
You have developed an application using Cloud ML Engine that recognizes famous paintings from uploaded images. You want to test the application and allow specific people to upload images for the next 24 hours. Not all users have a Google Account. How should you have users upload images?
You have developed an application using Cloud ML Engine that recognizes famous paintings from uploaded images. You want to test the application and allow specific people to upload images for the next 24 hours. Not all users have a Google Account. How should you have users upload images?
Correct Answer: D
Explanation: Only visible for Pass4Test members. You can sign-up / login (it's free).
QUESTION NO: 10
Your team will start developing a new application using microservices architecture on Kubernetes Engine. As part of the development lifecycle, any code change that has been pushed to the remote develop branch on your GitHub repository should be built and tested automatically. When the build and test are successful, the relevant microservice will be deployed automatically in the development environment. You want to ensure that all code deployed in the development environment follows this process. What should you do?
Your team will start developing a new application using microservices architecture on Kubernetes Engine. As part of the development lifecycle, any code change that has been pushed to the remote develop branch on your GitHub repository should be built and tested automatically. When the build and test are successful, the relevant microservice will be deployed automatically in the development environment. You want to ensure that all code deployed in the development environment follows this process. What should you do?
Correct Answer: D
Explanation: Only visible for Pass4Test members. You can sign-up / login (it's free).
QUESTION NO: 11
You need to build and deploy a containerized web application to Google Cloud. The application is very write-heavy and requires a relational database as its data store. The application needs to be highly available in multiple cloud regions. You want to minimize operational overhead while following Google-recommended practices. What should you do?
You need to build and deploy a containerized web application to Google Cloud. The application is very write-heavy and requires a relational database as its data store. The application needs to be highly available in multiple cloud regions. You want to minimize operational overhead while following Google-recommended practices. What should you do?
Correct Answer: B
Explanation: Only visible for Pass4Test members. You can sign-up / login (it's free).




