Google Cloud Architect 认证考试错题集7
Google Cloud Architect 认证考试错题集7
Option B is the correct answer for this scenario. Here's why:
B. Mount a Local SSD volume as the backup location. After the backup is complete, use gsutil to move the backup to Google Cloud Storage.
- Local SSD volumes provide high-performance, low-latency storage that is ideal for temporary data that needs to be accessed frequently. By using a Local SSD volume as the backup location, the backup activity can complete quickly without impacting disk performance. Once the backup is complete, using gsutil to move the backup to Google Cloud Storage ensures that the data is securely stored in the cloud for long-term retention and disaster recovery purposes.将本地SSD卷挂载为备份位置。备份完成后，使用gsutil将备份移至Google Cloud Storage。本地SSD卷提供高性能、低延迟存储，非常适合需要频繁访问的临时数据。通过将本地SSD卷作为备份位置，可以快速完成备份活动而不会影响磁盘性能。备份完成后，使用gsutil将备份移至Google Cloud Storage，以确保数据在云端安全存储以便长期保留和灾难恢复。，。；‘可以拿mcvdxf’
Now, let's explain why the other options are incorrect:
A. Configure a cron job to use the gcloud tool to take regular backups using persistent disk snapshots.
This option involves taking backups using persistent disk snapshots, which can impact disk performance during the snapshot creation process. While persistent disk snapshots are useful for creating point-in-time backups, they may not be the best choice if the goal is to minimize impact on disk performance during backup activities.配置cron作业以使用gcloud工具定期备份，使用持久磁盘快照。这个选项涉及使用持久磁盘快照进行备份，在创建快照的过程中会影响磁盘性能。虽然持久磁盘快照对于创建时间点备份非常有用，但如果目标是尽量减少备份活动期间对磁盘性能的影响，可能不是最佳选择。
总体解释 正确答案是D. 配置无服务器VPC访问。
By configuring serverless VPC access, you can allow your App Engine application to communicate with resources in your on-premises environment via a VPC network. This means that your App Engine application will be able to access the database running in the company's on-premises environment securely through the Cloud VPN tunnel.通过配置无服务器VPC访问，您可以让您的App Engine应用程序通过VPC网络与本地环境中的资源进行通信。这意味着您的App Engine应用程序将能够通过Cloud VPN隧道安全地访问公司本地环境中运行的数据库。
为什么其他选项不正确：
A. 仅为本地主机配置私人Google访问：
此选项仅允许本地主机私下访问Google Cloud服务。它并没有解决使App Engine应用程序能够与本地环境中的数据库通信的要求。 This option would only allow on-premises hosts to access Google Cloud services privately. It does not address the requirement of enabling the App Engine application to communicate with the database in the on-premises environment.
B. 配置私人Google访问：
此选项允许Google Cloud资源私下访问Google API和服务。它不能使App Engine应用程序与本地环境中的数据库进行通信。
C. 配置私人服务访问：
此选项用于启用从VPC网络到Google服务的私有连接。它并没有提供一种直接的方法，使App Engine应用程序能够与本地环境中的数据库通信。
什么是serverless VPC access
无服务器VPC访问（Serverless VPC Access）是一种使无服务器应用程序（如Google App Engine、Cloud Functions、Cloud Run）可以安全地访问专用网络（VPC）中的资源的技术。这种访问方式提供了许多优点：
- 安全连接
：无服务器VPC访问允许您的无服务器应用程序通过VPC（虚拟私有云）安全地与其他服务和资源进行通信，比如数据库或存储在本地数据中心的应用。
- 网络隔离
：使用VPC可以将您的应用与互联网隔离，仅允许特定的网络流量，增强了安全性。
- 简单配置
：配置无服务器VPC访问相对简单，可以通过Google Cloud Console或者命令行工具进行设置。
这使得您的应用程序能够轻松访问需要额外安全保护的资源，同时无需复杂的网络配置和维护工作。您可以获得高性能、低延迟的连接，同时享受无服务器架构带来的成本效益和灵活性。
B is the correct answer for this question. Here's the explanation:
- Org viewer, project viewer (Option B): By assigning the Org viewer role to the security team, they will have detailed visibility of all projects within the organization at the organizational level. This role allows them to view all resources and configurations within the organization. Additionally, assigning the project viewer role at the project level will provide them with read-only access to view resources within individual projects, ensuring they have visibility at both organizational and project levels.
The correct answers are D. Enable code signing and a trusted binary repository integrated with your CI/CD pipeline and E. Run a vulnerability security scanner as part of your continuous-integration /continuous-delivery (CI/CD) pipeline.
D. Enable code signing and a trusted binary repository integrated with your CI/CD pipeline: This action helps in ensuring that the code being deployed is authentic and has not been tampered with. Code signing adds a layer of security by verifying the integrity and origin of the code. Integrating a trusted binary repository with the CI/CD pipeline ensures that only approved and secure dependencies are used in the software development process, reducing the risk of security errors. 启用代码签名和与CI/CD管道集成的受信任的二进制存储库：此操作有助于确保正在部署的代码是可信的，并且没有被篡改。代码签名通过验证代码的完整性和来源增加了一层安全性。将受信任的二进制存储库与CI/CD管道集成，确保在软件开发过程中仅使用经过批准的安全依赖项，从而降低安全错误的风险。
E. Run a vulnerability security scanner as part of your continuous-integration /continuous-delivery (CI/CD) pipeline: Running a vulnerability security scanner as part of the CI/CD pipeline helps in identifying security vulnerabilities in the code early in the development process. This proactive approach allows for quick detection and resolution of security issues, aligning with the company's objective of being responsive and meeting customer needs quickly.
B. Use source code security analyzers as part of the CI/CD pipeline: While using source code security analyzers is a good practice for identifying security vulnerabilities in the code, it may not directly address the need for quick responsiveness and meeting customer needs in a fast-paced environment. Source code security analyzers can add overhead to the development process and may not align with the primary business objectives of release speed and agility.
A. Use Google App Engine to serve the website and Google Cloud Datastore to store user data: This option is recommended because Google App Engine is a fully managed platform that automatically scales based on the incoming traffic. It eliminates the need for direct operational management as it handles the scaling and deployment automatically. Google Cloud Datastore is a NoSQL database that can handle the user data storage efficiently. Together, they provide a scalable and low-maintenance solution for the promotional email campaign.使用Google App Engine来服务网站并使用Google Cloud Datastore来存储用户数据：此选项推荐使用，因为Google App Engine是一个全托管的平台，会根据传入的流量自动扩展。它消除了直接操作管理的需要，因为它会自动处理扩展和部署。Google Cloud Datastore是一个NoSQL数据库，可以有效地处理用户数据存储。它们一起提供了一个可扩展且低维护的电子邮件推广活动解决方案。
C. Use a managed instance group to serve the website and Google Cloud Bigtable to store user data: Managed instance groups allow for automatic scaling and load balancing of virtual machine instances. This helps in handling the wide range of possible customer responses without manual intervention. Google Cloud Bigtable is a highly scalable NoSQL database service that can efficiently store and manage large amounts of data. This combination provides a scalable and reliable infrastructure for the campaign.使用托管实例组来服务网站并使用Google Cloud Bigtable来存储用户数据：托管实例组允许虚拟机实例的自动扩展和负载均衡。这有助于在不需要人工干预的情况下处理客户可能的各种响应。Google Cloud Bigtable是一个高度可扩展的NoSQL数据库服务，可以有效地存储和管理大量数据。这种组合为活动提供了可扩展且可靠的基础架构。
D. Use a single Compute Engine virtual machine (VM) to host a web server, backed by Google Cloud SQL: This option involves manual management of the virtual machine and web server, which goes against the requirement of minimizing direct operational management. Using a single VM may not be able to handle the wide range of customer responses efficiently. Google Cloud SQL, while a managed relational database service, may not be the best choice for handling large amounts of user data and preferences in this scenario.使用单个Compute Engine虚拟机（VM）托管一个网络服务器，支持Google Cloud SQL：此选项涉及手动管理虚拟机和网络服务器，这违背了尽量减少直接操作管理的要求。使用单个VM可能无法有效地处理客户响应的广泛范围。尽管Google Cloud SQL是一个托管关系数据库服务，但在这种情况下，它可能不是处理大量用户数据和偏好的最佳选择。
- Google Kubernetes Engine (GKE) with containers is a suitable choice for a cloud-native solution that is no-ops and auto-scaling. GKE is a managed Kubernetes service provided by Google Cloud that allows you to deploy, manage, and scale containerized applications using Kubernetes. With GKE, you can automate the management of your containerized applications, including auto-scaling based on resource usage or custom metrics.
- Google App Engine Standard Environment is another suitable choice for a cloud-native solution that is no-ops and auto-scaling. App Engine Standard Environment is a fully managed platform that allows you to build and deploy applications without worrying about infrastructure management. It automatically scales based on traffic and provides a no-ops experience for developers.
Now, let's explain why the other options are incorrect:
- A. Compute Engine with containers: While Compute Engine can be used to run containerized workloads, it does not provide the same level of automation and auto-scaling capabilities as GKE or App Engine Standard Environment. To achieve a more cloud-native, no-ops, and auto-scaling solution, it is better to choose a managed service like GKE or App Engine.
- D. Compute Engine with custom instance types: Custom instance types in Compute Engine allow you to create virtual machine instances with custom configurations, but they do not inherently provide auto-scaling or no-ops capabilities. Custom instance types are more focused on optimizing the performance and cost of individual VMs, rather than providing a fully managed and scalable solution.
- E. Compute Engine with managed instance groups: Managed instance groups in Compute Engine allow you to create groups of virtual machine instances that are automatically managed and scaled based on load balancing and autoscaling policies. While managed instance groups offer some level of automation and scalability, they do not provide the same level of cloud-native, no-ops experience as GKE or App Engine Standard Environment. These options are more suitable for traditional VM-based workloads rather than cloud-native solutions.
所以GCE不是Cloud Native，不建议。
A. Set up a filter in Cloud Logging and a Cloud Storage bucket as an export target for the logs you want to save. ——开放性结尾，不限制到哪里
Setting up a filter in Cloud Logging allows you to specify the logs you want to save, in this case, the Cloud VPN log events. By configuring a Cloud Storage bucket as an export target, you can save these logs for one year. Cloud Storage provides a scalable and durable storage solution for long-term retention of logs.
C. Setting up a Cloud Logging Dashboard and adding a chart for VPN metrics does not address the requirement of saving Cloud VPN log events for one year. Dashboards are used for monitoring and visualizing data, not long-term storage of logs. ——临时查看可以，但不建议长期这样用
The correct answer is A. Create an aggregated export on the Production folder. Set the log sink to be a Cloud Storage bucket in an operations project.
By creating an aggregated export on the Production folder, you ensure that logs from all production projects within that folder are captured automatically. This approach simplifies log management and ensures that new production projects are included without additional configuration.通过在生产文件夹上创建聚合导出，您可以确保该文件夹中所有生产项目的日志都被自动捕获。这种方法简化了日志管理，并确保新生产项目无需额外配置即可包含在内。
Why the other options are incorrect:
B. Creating an aggregated export on the Organization resource and setting the log sink to a Cloud Storage bucket in an operations project would capture logs from all resources in the organization, not just the production projects. This option does not meet the requirement of only capturing logs from production projects.在组织资源上创建聚合导出并将日志接收器设置为操作项目中的Cloud Storage桶，将捕获组织中所有资源的日志，而不仅仅是生产项目的日志。此选项不符合仅捕获生产项目日志的要求。
C. Creating log exports in the production projects and setting the log sinks to a Cloud Storage bucket in an operations project would require manual configuration for each production project. This approach is not scalable and does not ensure that new production projects are automatically included.在生产项目中创建日志导出，并将日志接收器设置为操作项目中的Cloud Storage桶，将需要为每个生产项目手动配置。这种方法不可扩展，并且无法确保新生产项目自动包含在内。
D. Creating log exports in the production projects and setting the log sinks to be BigQuery datasets in the production projects would capture logs in BigQuery, not Cloud Storage. Additionally, granting IAM access to the operations team to run queries on the datasets adds complexity and may not be necessary for log storage purposes.在生产项目中创建日志导出，并将日志接收器设置为生产项目中的BigQuery数据集，将在BigQuery中捕获日志，而不是Cloud Storage。此外，授予操作团队运行查询的数据集的IAM访问权限增加了复杂性，并且可能不必要用于日志存储。
The correct answer is D. Here's why:
1. Create a managed instance group with Compute Engine instances: By creating a managed instance group, you ensure that your application can scale based on demand. This means that as more users try to play popular songs, additional instances can be automatically provisioned to handle the load.
2. Create a global load balancer and configure it with two backends:
- Managed instance group: By configuring the load balancer with a managed instance group as one of the backends, the load balancer can distribute incoming traffic among the instances in the group, ensuring better load distribution and availability.
- Cloud Storage bucket: By also configuring the load balancer with a Cloud Storage bucket as a backend, you can serve static content (like music files) directly from Cloud Storage. This can help reduce the load on your Compute Engine instances and improve performance.
3. Enable Cloud CDN on the bucket backend: Cloud CDN (Content Delivery Network) caches content at Google's globally distributed edge locations, reducing latency for users by serving content from a location closer to them. This can significantly improve performance by delivering content more quickly to users trying to play popular songs.
B. Create a Cloud Filestore NFS volume and attach it to the backend Compute Engine instances:
- Similar to option A, this option does not address the scalability issue or the performance improvement needed when serving popular songs to multiple users.
C is the correct answer for the question because it follows Google-recommended practices and meets the requirements provided in the scenario. Here's why Option C is correct:
1. Create folders under the Organization resource named "Development" and "Production": By creating separate folders for development and production projects under the same Organization, you can logically group projects based on their purpose.在组织资源下创建名为“Development”和“Production”的文件夹：通过在同一组织下为开发项目和生产项目创建单独的文件夹，您可以根据项目的用途逻辑地对其进行分组。
2. Grant all developers the Project Creator IAM role on the "Development" folder: This step allows developers to create projects within the "Development" folder, giving them the necessary permissions to work on non-production projects.为所有开发人员授予“Development”文件夹上的项目创建者（Project Creator）IAM角色：此步骤允许开发人员在“Development”文件夹中创建项目，给他们必要的权限来处理非生产项目。
3. Move the developer projects into the "Development" folder: This ensures that all developer-created projects are organized within the appropriate folder, making it easier to manage and apply policies.将开发人员的项目移至“Development”文件夹：这确保所有开发人员创建的项目都组织在适当的文件夹中，便于管理和应用策略。
4. Set the policies for all projects on the Organization: By setting policies at the Organization level, you can centrally manage and enforce policies across all projects within the Organization, including those in the "Development" and "Production" folders.为组织中的所有项目设置策略：通过在组织级别设置策略，您可以集中管理并强制执行整个组织中所有项目的策略，包括“Development”和“Production”文件夹中的项目
5. Additionally, set the production policies on the "Production" folder: This step allows you to apply more restrictive policies specifically to production projects while maintaining a separate set of policies for non-production projects.另外，在“Production”文件夹上设置生产策略：此步骤允许您对生产项目应用更严格的策略，同时为非生产项目保留单独的一套策略。