Professional-Cloud-Architect対応問題集 & Professional-Cloud-Architect問題例

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Google Professional-Cloud-Architect Exam Syllabus Topics:

SectionObjectives
Topic 1: Ensuring solution and operations reliability- Evaluating quality control measures
- Monitoring/logging/profiling/alerting solution
  • 1. Cloud Monitoring and Cloud Logging
  • 2. Performance profiling and tracing
  • 3. Error reporting and alerting
- Deployment and release management
  • 1. Release management and versioning
  • 2. Deployment strategies and rollback
- Assisting with support
  • 1. Capacity planning and scaling
  • 2. Incident response and troubleshooting
Topic 2: Analyzing and optimizing technical and business processes- Analyzing and defining technical processes
  • 1. Incident management and troubleshooting
  • 2. Software development lifecycle (SDLC)
  • 3. CI/CD pipeline design
- Analyzing and defining business processes
  • 1. Business KPIs and metrics
  • 2. Cost management and optimization
  • 3. Stakeholder communication
Topic 3: Managing and provisioning a solution infrastructure- Configuring network topologies
  • 1. VPC design and peering
  • 2. Hybrid and multi-cloud connectivity
  • 3. Private access and VPN configuration
- Configuring compute systems
  • 1. GKE configuration and management
  • 2. Compute Engine configuration
  • 3. Cloud Run and Cloud Functions
- Configuring individual storage systems
  • 1. Cloud Storage configuration
  • 2. Cloud SQL and Spanner
  • 3. Datastore and Bigtable
Topic 4: Designing and planning a cloud solution architecture- Enabling future cloud technology
  • 1. Designing for scalability and elasticity
  • 2. Implementing future-proof architectures
- Designing solution infrastructure that meets business requirements
  • 1. Business use cases and product strategy
  • 2. Cost optimization
  • 3. Networking and compute resources
  • 4. Migration planning
  • 5. Data and storage architecture
  • 6. Integration with existing systems
- Creating a migration plan
  • 1. Planning data migration
  • 2. Refactoring and rearchitecting applications
  • 3. Identifying workloads for migration
- Designing network, storage, and compute resources
  • 1. Compute engine selection and configuration
  • 2. Storage options and data lifecycle management
  • 3. Network design including load balancing and firewall rules
  • 4. GKE cluster and workload design
Topic 5: Managing implementation- Interacting with Google Cloud programmatically
  • 1. Infrastructure as Code (IaC)
  • 2. Cloud SDK and gcloud CLI
  • 3. APIs and client libraries
- Advising development/operation team(s) to ensure successful deployment
  • 1. Application development best practices
  • 2. Deployment strategies
  • 3. Testing and validation
Topic 6: Designing for security and compliance- Designing for security
  • 1. Data security and encryption
  • 2. Application security
  • 3. Identity and Access Management (IAM)
  • 4. Network security
- Designing for compliance
  • 1. Regulatory and compliance requirements
  • 2. Data residency and sovereignty
  • 3. Audit logging and monitoring

>> Professional-Cloud-Architect対応問題集 <<

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Google Certified Professional - Cloud Architect (GCP) 認定 Professional-Cloud-Architect 試験問題 (Q260-Q265):

質問 # 260
You need to set up Microsoft SQL Server on GCP. Management requires that there's no downtime in case of a data center outage in any of the zones within a GCP region. What should you do?

正解：D

解説：
Explanation
https://cloud.google.com/sql/docs/sqlserver/configure-ha


質問 # 261
You want to create a private connection between your instances on Compute Engine and your on-premises data center. You require a connection of at least 20 Gbps. You want to follow Google-recommended practices. How should you set up the connection?

正解：D


質問 # 262
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's development team is using a microservices architecture for their application. You need to select the most suitable testing approach to ensure that individual microservices function correctly in isolation. What should you do?

正解：B

解説：
Unit testing validates the logic and behavior of each microservice independently, ensuring it functions correctly in isolation without relying on other services or external dependencies.


質問 # 263
You are developing an application using different microservices that should remain internal to the cluster. You want to be able to configure each microservice with a specific number of replicas. You also want to be able to address a specific microservice from any other microservice in a uniform way, regardless of the number of replicas the microservice scales to. You need to implement this solution on Google Kubernetes Engine. What should you do?

正解：A

解説：
https://kubernetes.io/docs/concepts/services-networking/ingress/


質問 # 264
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?

正解：C

解説：
Explanation/Reference: https://cloud.google.com/kubernetes-engine/docs/how-to/cluster-autoscaler


質問 # 265
......

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