PCA — questions

You are managing a few hundred Ubuntu and Red Hat Enterprise Linux virtual machines running on Google Compute Engine (GCE). You need to patch the operating systems for those VMs periodically in a secure and scalable way. What should you do?

Your company uses Salesforce for customer relationship management (CRM). ServiceNow for IT service management, and a Cloud SQL database to store customer transaction data You need to seamlessly connect, map. and transform data between these systems to ensure data consistency and enable real-time reporting. You want to follow Google-recommended practices. What should you do?

You are designing the architecture for a global social media site on Google Cloud. The site serves dynamic API content, static assets such as CSS. JS. images, and user-uploaded videos for streaming. You need to minimize latency for all content types for users worldwide. What should you do? (Choose two.)

You are creating a migration plan to move your organization’s infrastructure from on-premises to Google Cloud. You want to understand and manage costs effectively after the migration is complete. Which strategies should you include in the migration plan? (Choose two.)

A Cloud Run service running your serverless application is unable to connect to an AlloyDB database created with default configurations. You need to troubleshoot and resolve the issue as quickly as possible. What should you do?

Your company is building containerized applications as part of their CI/CD pipeline. To improve the security and maintainability of the build process, you need to: • Identify potential vulnerabilities within your container images. • Generate verifiable metadata about the builds for auditing and compliance. • Create a comprehensive inventory of your application’s dependencies What should you do?

Your team is running applications on a Google Kubernetes Engine (GKE) cluster with a private endpoint. You've set up a Cloud Deploy pipeline, but deployments to the GKE cluster are failing. You need to resolve the issue. What should you do?

You are planning to migrate your on-premises compute and SAP workloads to Google Cloud. You want to follow Google-recommended practices to quickly create a cost estimate for running these workloads in Google Cloud. What should you do?

Your organization has a significant amount of log data stored in Cloud Logging. The data engineering team is accustomed to using SQL for analysis and wants the ability to create insightful dashboards for visualizing log trends and patterns. You want to follow the recommendations of the Google Cloud Well-Architected Framework to provide a solution for the data engineering team. What should you do?

You are designing the storage architecture for a financial analytics platform. The platform ingests and stores terabytes of transactional data daily, which is used for both real-time fraud detection and long-term historical analysis. Transaction data from the last 30 days must be accessible with very low latency for the fraud detection engine. Data older than 30 days is accessed infrequently for quarterly reports, where retrieval times of a few seconds are acceptable. All data must be retained for five years to meet compliance regulations. You need to design a solution as cost-effective as possible. What should you do?

You are architecting a new application feature for a healthcare provider based in Qatar. The feature needs to summarize sensitive patient notes that are submitted by clinicians. A critical requirement is that the content of these patient notes must never be processed outside of Qatar's borders. You want to use a powerful, pre-trained generative model for the summarization task while strictly adhering to the data residency constraint. What should you do?

You are migrating a critical on-premises inventory management application to Google Cloud. The application is a monolith with a traditional relational database, and the immediate business goal is a rapid data center exit. The monolith is exposing an API to other business critical applications. The long-term vision is to modernize the application into globally distributed, cloud-native services to support the company’s expansion. You need to design the initial cloud architecture to ensure that future modernization causes the least possible disruption to other applications that depend on inventory data. The future modernization might require the API to change structure. What should you do?

Your organization uses separate Google Cloud projects for shared services, development, testing, and production. • The shared services project hosts your private CI/CD runners and a central Artifact Registry • The development, testing, and production projects host the GKE clusters where applications are deployed. You need to design an architecture that allows the CI/CD runners to connect to the GKE clusters and the clusters to pull images from Artifact Registry, all using private IP addresses. However, direct network traffic between the development, testing, and production environments must be strictly prohibited. What should you do?

You are designing the network architecture for a public-facing, containerized web application deployed on Cloud Run. All incoming traffic must be inspected by a Cloud Armor web application firewall (WAF) before reaching the application You plan to use an Application Load Balancer, which will have the Cloud Armor policy attached. You must ensure that all public requests pass through the load balancer and any attempt to access the Cloud Run service directly through its default *.run.app URL is blocked. What should you do?

To improve governance and security, your organization has structured the Google Cloud environment using folders for different business units. Each business unit folder has subfolders for development, staging, and production environments, which must comply with internal security controls: • Production workloads must be protected from direct internet ingress by default unless explicitly tagged. • The application must be accessible to customers over HTTPS. You need to design a scalable and enforceable model that blocks internet ingress traffic to the production folders while selectively allowing direct HTTPS traffic to the necessary virtual machines. You must also ensure that individual project teams cannot overwrite these controls once they are implemented for all current and future production projects. What should you do?

You are designing a new insurance claims processing application that will be deployed on Google Kubernetes Engine (GKE) Your company’s compliance team requires a complete and non-repudiable audit trail for all administrative actions from day one. Your application must capture who deploys a new container image, who modifies the GKE cluster's configuration, and who interacts with running pods or Kubernetes secrets using kubectl. What should you do?

Your product team is building a critical, customer-facing application on Google Cloud. The development team wants to use Spanner for their database to take advantage of its horizontal scalability and low operational overhead However, the FinOps team is concerned about the direct monthly cost of Spanner and proposed using a self-managed PostgreSQL database on Compute Engine VMs instead. You need to resolve this conflict and ensure the project moves forward with an architecturally sound database choice that balances technical requirements with financial constraints. What should you do?

You are deploying a critical application with a stateless, containerized frontend on Cloud Run and a Cloud SQL for PostgreSQL backend. The application experiences unpredictable traffic spikes, and the business requires the ability to immediately roll back a failed deployment to the last known good state. You need to apply a deployment strategy that aligns with Site Reliability Engineering (SRE) principles for both the application code and the database schema updates, while meeting the business's requirements. What should you do?

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 stores a large library of media content, including sensitive interviews and documentaries, in Cloud Storage. They are concerned about the confidentiality of this content and want to protect it from unauthorized access. You need to implement a Google-recommended solution that is easy to integrate and provides Altostrat with control and auditability of the encryption keys. What should you do?

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 experiencing fluctuating computational demands for its batch processing jobs. These jobs are not time-critical and can tolerate occasional interruptions. You want to optimize cloud costs and address batch processing needs. What should you do?