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Google Professional Cloud Architect Exam Questions
- Topic 1: Designing and planning a cloud solution architecture: This section evaluates the skills of cloud architects in designing infrastructures that align with both business and technical requirements. It encompasses understanding business use cases, cost optimization, application support, external system integration, data movement, and making informed design decisions. Additionally, it involves creating migration plans, integrating solutions with existing systems, and anticipating future improvements based on evolving business needs and technological advancements.
- Topic 2: Managing and provisioning a solution infrastructure: Targeting system administrators, this section assesses the ability to configure network topologies, storage systems, and compute resources. It includes extending networks to on-premises or multi-cloud environments, ensuring security measures, managing data storage allocation, provisioning compute resources, and orchestrating infrastructure effectively.
- Topic 3: Designing for security and compliance: This section focuses on security engineers' expertise in designing secure and compliant cloud solutions. It covers identity and access management, resource hierarchy structuring, data security practices like encryption and key management, separation of duties, and implementing security controls. Additionally, it addresses designing for compliance with various legislative, commercial, and industry standards, ensuring that solutions meet necessary certifications and audit requirements.
- Topic 4: Analyzing and optimizing technical and business processes: Aimed at business analysts, this section evaluates the analysis and definition of technical and business processes. It includes understanding the software development life cycle, continuous integration and deployment practices, troubleshooting methodologies, testing and validation, service provisioning, and disaster recovery planning. Furthermore, it involves stakeholder management, change management, team skill assessments, decision-making processes, customer success strategies, and cost optimization efforts.
- Topic 5: Managing implementation: This section assesses project managers' abilities to oversee the successful deployment of cloud solutions. It involves advising development and operations teams, understanding application development, adhering to API best practices, utilizing testing frameworks, managing data and system migrations, and interacting with Google Cloud programmatically using tools like Cloud Shell and Cloud SDK.
- Topic 6: Ensuring solution and operations reliability: Focusing on site reliability engineers, this section evaluates the implementation of monitoring, logging, profiling, and alerting solutions to maintain operational reliability. It includes managing deployment and release processes, supporting deployed solutions, and evaluating quality control measures to ensure the robustness and reliability of cloud operations.
Free Google Professional Cloud Architect Exam Actual Questions
Note: Premium Questions for Professional Cloud Architect were last updated On Mar. 18, 2025 (see below)
Your company has an application that is running on multiple instances of Compute Engine. It generates 1 TB per day of logs. For compliance reasons, the logs need to be kept for at least two years. The logs need to be available for active query for 30 days. After that, they just need to be retained for audit purposes. You want to implement a storage solution that is compliant, minimizes costs, and follows Google-recommended practices. What should you do?
The practice for managing logs generated on Compute Engine on Google Cloud is to install the Cloud Logging agent and send them to Cloud Logging.
The sent logs will be aggregated into a Cloud Logging sink and exported to Cloud Storage.
The reason for using Cloud Storage as the destination for the logs is that the requirement in question requires setting up a lifecycle based on the storage period.
In this case, the log will be used for active queries for 30 days after it is saved, but after that, it needs to be stored for a longer period of time for auditing purposes.
If the data is to be used for active queries, we can use BigQuery's Cloud Storage data query feature and move the data past 30 days to Coldline to build a cost-optimal solution.
Therefore, the correct answer is as follows
1. Install the Cloud Logging agent on all instances.
Create a sync that exports the logs to the region's Cloud Storage bucket.
3. Create an Object Lifecycle rule to move the files to the Coldline Cloud Storage bucket after one month. 4.
4. set up a bucket-level retention policy using bucket locking.'
Your company has an enterprise application running on Compute Engine that requires high availability and high performance. The application has been deployed on two instances in two zones in the same region m active passive mode. The application writes data to a persistent disk in the case of a single zone outage that data should be immediately made available to the other instance in the other zone. You want to maximize performance while minimizing downtime and data loss. What should you do?
For this question, refer to the TerramEarth case study. You are building a microservice-based application for TerramEarth. The application is based on Docker containers. You want to follow Google-recommended practices to build the application continuously and store the build artifacts. What should you do?
Your company has a Google Cloud project that uses BigQuery for data warehousing on a pay-per-use basis. You want to monitor queries in real time to discover the most costly queries and which users spend the most. What should you do?
https://cloud.google.com/blog/products/data-analytics/taking-a-practical-approach-to-bigquery-cost-monitoring
You are configuring the cloud network architecture for a newly created project m Google Cloud that will host applications in Compote Engine Compute Engine virtual machine instances will be created in two different subnets (sub-a and sub-b) within a single region
* Instances in sub-a win have public IP addresses
* Instances in sub-b will have only private IP addresses
To download updated packages, instances must connect to a public repository outside the boundaries of Google Cloud You need to allow sub-b to access the external repository. What should you do?
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