AWS SAA-C03 真题演练卷 · 第 05 份

The most cost-effective solution is to configure an Auto Scaling group with the Application Load Balancer. This ensures that additional EC2 instances are launched during peak traffic and terminated during low traffic, optimizing both performance and cost. While adding more EC2 instances or upgrading the instance type might temporarily resolve the issue, these approaches do not dynamically adjust to changes in traffic patterns, which can lead to inefficient resource utilization.

最经济高效的解决方案是使用 Application Load Balancer 配置 Auto Scaling 组。这可确保在高峰流量期间启动额外的 EC2 实例，并在低流量期间终止额外的 EC2 实例，从而优化性能和成本。虽然添加更多 EC2 实例或升级实例类型可能会暂时解决该问题，但这些方法不会动态调整以适应流量模式的变化，这可能会导致资源利用效率低下。

The most suitable solution for routing traffic based on URL paths is an Application Load Balancer (ALB) with path-based routing rules. ALB operates at the application layer (Layer 7) and supports advanced routing features like path-based and host-based routing. This makes it ideal for dynamic content routing scenarios like the one described in the question.

基于 URL 路径路由流量的最合适解决方案是具有基于路径的路由规则的 Application Load Balancer (ALB)。 ALB 在应用层（第 7 层）运行，支持高级路由功能，例如基于路径和基于主机的路由。这使得它非常适合动态内容路由场景，例如问题中描述的场景。

Amazon RDS Proxy is designed to manage and pool database connections, which is particularly useful for applications experiencing high connection churn or exceeding connection limits. By reusing existing connections, it reduces the overhead of establishing new connections and improves database performance during peak traffic periods. It does not replicate databases, scale the underlying database instance, or cache query results.

Amazon RDS 代理旨在管理和池化数据库连接，这对于遇到高连接流失或超出连接限制的应用程序特别有用。通过重用现有连接，可以减少建立新连接的开销，并提高高峰流量期间的数据库性能。它不复制数据库、扩展底层数据库实例或缓存查询结果。

Amazon RDS Proxy is the best solution for managing unpredictable spikes in database connections because it pools and shares connections efficiently, reducing the risk of connection exhaustion and improving database performance. It also works seamlessly without requiring changes to the application code. Other options either do not address the core issue of connection pooling or are not cost-effective for this use case.

Amazon RDS 代理是管理不可预测的数据库连接峰值的最佳解决方案，因为它可以有效地池化和共享连接，从而降低连接耗尽的风险并提高数据库性能。它还可以无缝工作，无需更改应用程序代码。其他选项要么不能解决连接池的核心问题，要么对于该用例来说不具有成本效益。

Amazon RDS Proxy is designed to improve the performance and availability of applications that use Amazon RDS. It achieves this by pooling and sharing database connections, encrypting data in transit, and minimizing downtime during failovers. However, it does not automatically scale the database instance or enable write operations on read replicas.

Amazon RDS 代理旨在提高使用 Amazon RDS 的应用程序的性能和可用性。它通过池化和共享数据库连接、加密传输中的数据以及最大限度地减少故障转移期间的停机时间来实现这一目标。但是，它不会自动扩展数据库实例或在只读副本上启用写入操作。

Amazon RDS Proxy is designed to manage database connection pooling efficiently, which reduces the overhead of opening and closing database connections during traffic spikes. This makes it an ideal solution for applications with unpredictable or spiky workloads, as it improves scalability and minimizes the impact on the database.

Amazon RDS Proxy 旨在有效管理数据库连接池，从而减少流量高峰期间打开和关闭数据库连接的开销。这使其成为具有不可预测或尖峰工作负载的应用程序的理想解决方案，因为它提高了可扩展性并最大限度地减少对数据库的影响。

When preparing a standby environment for disaster recovery, it is critical to ensure that regional service quotas, such as EC2 instance limits, are sufficient for the anticipated workload. Quotas are managed independently for each region, so the company must request increases in the standby region where needed. Monitoring quota usage with tools like CloudWatch helps avoid throttling during failover. Additionally, verifying the default quotas ensures a proactive approach to meeting workload requirements.

在为灾难恢复准备备用环境时，确保区域服务配额（例如 EC2 实例限制）足以满足预期工作负载至关重要。每个区域的配额是独立管理的，因此公司必须在需要时请求增加备用区域。使用 CloudWatch 等工具监控配额使用情况有助于避免故障转移期间的限制。此外，验证默认配额可确保主动满足工作负载要求。

To resolve throttling issues in a standby environment, you need to address the root cause, which is the service quota limit. By using the AWS Service Quotas dashboard, you can review the current limits and request a quota increase if necessary. Monitoring tools like CloudWatch are helpful for detecting issues but do not resolve them, and changing compute resources or architectures does not impact service quotas.

要解决备环境的限流问题，需要解决根本原因，即服务配额限制。通过使用 AWS Service Quotas 仪表板，您可以查看当前限制并在必要时请求增加配额。 CloudWatch 等监控工具有助于检测问题，但不能解决问题，并且更改计算资源或架构不会影响服务配额。

Service quotas are limits set by AWS that control the maximum amount of resources a service can use. In a disaster recovery scenario, if the standby environment takes over the workload, it may exceed the default service quotas of the region, leading to throttling. Requesting a service quota increase in the standby region ensures sufficient capacity to handle the workload during failover.

服务配额是 AWS 设置的限制，用于控制服务可以使用的最大资源量。在容灾场景下，如果备环境接管工作负载，可能会超出该区域默认的服务配额，从而导致限流。请求增加备用区域中的服务配额可确保有足够的容量来处理故障转移期间的工作负载。

To ensure the standby environment can handle production workloads during failover, you must proactively manage service quotas in the secondary Region. This includes requesting quota increases, monitoring quotas using AWS Service Quotas, and pre-deploying resources with sufficient quotas. Auto Scaling groups and AWS Trusted Advisor cannot automatically adjust quotas, so they are not viable options in this scenario.

为了确保备用环境可以在故障转移期间处理生产工作负载，您必须主动管理辅助区域中的服务配额。这包括请求增加配额、使用 AWS Service Quotas 监控配额以及预部署具有足够配额的资源。 Auto Scaling 组和 AWS Trusted Advisor 无法自动调整配额，因此在这种情况下它们不是可行的选择。

Amazon S3 with Cross-Region Replication (CRR) is the best choice for storing critical financial data because it provides unmatched durability (11 9s), the ability to replicate data across regions for disaster recovery, and compliance features like versioning and audit logging. Other options, such as EFS and FSx, do not meet all the requirements, while S3 Glacier Deep Archive is focused on long-term archival storage rather than low-latency access.

具有跨区域复制 (CRR) 功能的 Amazon S3 是存储关键财务数据的最佳选择，因为它提供无与伦比的耐用性 (11 个 9)、跨区域复制数据以进行灾难恢复的能力，以及版本控制和审核日志记录等合规性功能。其他选项，例如 EFS 和 FSx，并不能满足所有要求，而 S3 Glacier Deep Archive 则专注于长期归档存储而不是低延迟访问。

Amazon S3 is the best choice for this scenario because it provides highly durable, multi-AZ object storage with built-in lifecycle management capabilities. These features make it ideal for applications requiring reliable storage and cost optimization. Other options, such as Amazon EBS and Amazon EFS, are better suited for specific use cases like block storage or file storage, but they do not meet the requirements for object storage with multi-AZ durability and lifecycle management.

Amazon S3 是该场景的最佳选择，因为它提供高度耐用的多可用区对象存储，并具有内置生命周期管理功能。这些功能使其成为需要可靠存储和成本优化的应用的理想选择。其他选项（例如 Amazon EBS 和 Amazon EFS）更适合块存储或文件存储等特定用例，但它们不能满足具有多可用区持久性和生命周期管理的对象存储的要求。

Amazon S3 Standard is the most suitable option for critical financial data storage because it provides high durability (11 nines), automatic replication across multiple Availability Zones, and encryption at rest, fulfilling all the requirements specified in the scenario.

Amazon S3 标准版是关键金融数据存储的最合适选择，因为它提供高持久性（11 个 9）、跨多个可用区的自动复制以及静态加密，满足场景中指定的所有要求。

Amazon S3 is the best choice for this scenario because it is designed for high durability and availability. It automatically replicates data across multiple Availability Zones, ensuring that critical business data remains safe and accessible even in the event of an AZ failure. The other options either lack cross-AZ replication or durability guarantees, making them unsuitable for the given requirements.

Amazon S3 是这种场景的最佳选择，因为它专为高耐用性和可用性而设计。它自动跨多个可用区复制数据，确保即使在可用区发生故障时关键业务数据仍然安全且可访问。其他选项要么缺乏跨可用区复制，要么缺乏持久性保证，使得它们不适合给定的要求。

AWS X-Ray is the correct choice because it is specifically designed to provide distributed tracing for applications. X-Ray enables developers to trace requests as they travel through the application and build a detailed service map to debug issues, identify bottlenecks, and optimize performance. Other options like CloudWatch Logs, VPC Flow Logs, and CloudTrail are useful for logging and monitoring but do not offer the same level of visibility into request flows as X-Ray does.

AWS X-Ray 是正确的选择，因为它专门设计用于为应用程序提供分布式跟踪。 X-Ray 使开发人员能够在请求穿过应用程序时跟踪请求，并构建详细的服务图来调试问题、识别瓶颈并优化性能。 CloudWatch Logs、VPC Flow Logs 和 CloudTrail 等其他选项对于日志记录和监控非常有用，但无法提供与 X-Ray 相同级别的请求流可见性。

AWS X-Ray is specifically designed to provide end-to-end tracing for applications, enabling developers to visualize service dependencies, trace requests, and identify bottlenecks in distributed systems like microservices. This makes it the ideal choice for debugging latency issues and improving workload visibility in the given scenario.

AWS X-Ray 专门设计用于为应用程序提供端到端跟踪，使开发人员能够可视化服务依赖关系、跟踪请求并识别微服务等分布式系统中的瓶颈。这使其成为调试延迟问题和提高给定场景中工作负载可见性的理想选择。

To diagnose latency in a microservices-based application, AWS X-Ray is the ideal tool as it provides end-to-end request tracing and allows you to visualize the flow of requests across services. This is particularly important for identifying bottlenecks or performance issues in distributed applications, which cannot be achieved using logs or network-level monitoring alone.

要诊断基于微服务的应用程序中的延迟，AWS X-Ray 是理想的工具，因为它提供端到端请求跟踪，并允许您可视化跨服务的请求流。这对于识别分布式应用程序中的瓶颈或性能问题尤其重要，而仅使用日志或网络级监控无法实现这一点。

AWS X-Ray is designed specifically for tracing end-to-end requests in distributed systems like microservices. By enabling X-Ray on ECS services and instrumenting application code with the X-Ray SDK, the development team can collect detailed performance data, trace requests, and diagnose bottlenecks across multiple services. Other services like CloudWatch Logs and ALB logging provide monitoring and logging capabilities but do not offer the same level of visibility as X-Ray for tracing requests end-to-end.

AWS X-Ray 专为跟踪微服务等分布式系统中的端到端请求而设计。通过在 ECS 服务上启用 X-Ray 并使用 X-Ray SDK 检测应用程序代码，开发团队可以跨多个服务收集详细的性能数据、跟踪请求并诊断瓶颈。 CloudWatch Logs 和 ALB 日志记录等其他服务提供监控和日志记录功能，但无法提供与 X-Ray 相同级别的端到端跟踪请求可见性。

To design a high-performing architecture for a video streaming platform, it's essential to handle traffic spikes efficiently while minimizing costs. Auto Scaling ensures the backend can scale dynamically to meet demand. Amazon ElastiCache reduces backend load by caching frequently accessed data. Amazon CloudFront improves user experience by caching and delivering content from edge locations, reducing latency and offloading traffic from the origin servers. Switching to a Network Load Balancer or using AWS Lambda are unsuitable for this use case due to the specific requirements of video streaming applications.

要为视频流平台设计高性能架构，必须有效处理流量峰值，同时最大限度地降低成本。自动缩放确保后端可以动态扩展以满足需求。 Amazon ElastiCache 通过缓存经常访问的数据来减少后端负载。 Amazon CloudFront 通过缓存和传输边缘位置的内容、减少延迟并减轻源服务器的流量来改善用户体验。由于视频流应用的特定要求，切换到 Network Load Balancer 或使用 AWS Lambda 不适合此用例。

To design a high-performing architecture for the gaming application, enabling Auto Scaling ensures that the EC2 instances can handle fluctuating traffic dynamically. Additionally, deploying Amazon CloudFront helps offload static content delivery from the ALB, improving overall performance and latency. Other options either do not fit the requirements or provide less scalable solutions.

要为游戏应用程序设计高性能架构，启用 Auto Scaling 可确保 EC2 实例可以动态处理波动的流量。此外，部署 Amazon CloudFront 有助于卸载 ALB 的静态内容交付，从而提高整体性能和延迟。其他选项要么不符合要求，要么提供可扩展性较差的解决方案。

For a real-time analytics application that processes millions of events per second, Amazon Kinesis Data Streams is an ideal service for high-throughput, low-latency data ingestion. Amazon Kinesis Data Analytics can process this data in real-time, offering built-in analytics capabilities. Alternatively, AWS Lambda can be used alongside Kinesis Data Streams to process and transform streaming data in near real-time. Other services like SQS, DynamoDB, Firehose, and Redshift are not designed to handle this specific real-time, high-throughput use case effectively.

对于每秒处理数百万个事件的实时分析应用程序，Amazon Kinesis Data Streams 是高吞吐量、低延迟数据摄取的理想服务。 Amazon Kinesis 数据分析可以实时处理这些数据，提供内置分析功能。或者，AWS Lambda 可以与 Kinesis Data Streams 一起使用，以近乎实时的方式处理和转换流数据。 SQS、DynamoDB、Firehose 和 Redshift 等其他服务并非旨在有效处理这种特定的实时、高吞吐量用例。

To handle traffic spikes effectively and improve performance, the architecture should include Auto Scaling for dynamic scalability and ElastiCache for offloading frequently accessed data from the EC2 instances. These solutions reduce the computational burden during traffic spikes, ensuring a more responsive and high-performing application.

为了有效处理流量峰值并提高性能，该架构应包括用于动态可扩展性的 Auto Scaling 和用于从 EC2 实例卸载频繁访问的数据的 ElastiCache。这些解决方案减少了流量高峰期间的计算负担，确保应用程序响应更快且性能更高。

Amazon S3 with S3 Standard is the most suitable option for building a data lake due to its scalability, durability, and cost-effectiveness. It supports massive amounts of unstructured data and integrates well with analytics tools, addressing the company's need for high availability and optimized query performance. Other options like EFS, RDS, and DynamoDB are designed for different use cases and do not align with the petabyte-scale data lake requirement.

由于其可扩展性、耐用性和成本效益，采用 S3 标准的 Amazon S3 是构建数据湖的最合适选择。它支持海量非结构化数据，并与分析工具良好集成，满足公司对高可用性和优化查询性能的需求。 EFS、RDS 和 DynamoDB 等其他选项是针对不同的用例而设计的，并不符合 PB 级数据湖的要求。

The best solution for storing and processing large volumes of time-series data with high throughput and scalability requirements is Amazon DynamoDB. It is a fully managed, serverless NoSQL database designed to handle frequent writes and automatically scale to accommodate growing datasets. The on-demand capacity mode further simplifies scaling for unpredictable workloads, making it an ideal fit for this scenario.

存储和处理具有高吞吐量和可扩展性要求的大量时间序列数据的最佳解决方案是 Amazon DynamoDB。它是一个完全托管的无服务器 NoSQL 数据库，旨在处理频繁写入并自动扩展以适应不断增长的数据集。按需容量模式进一步简化了不可预测工作负载的扩展，使其非常适合这种场景。

Amazon S3 with S3 Transfer Acceleration is the most appropriate solution for a video-on-demand platform because it offers the scalability, high throughput, and low latency needed for streaming video content to a global audience. S3 Transfer Acceleration optimizes data transfer speeds for users in different geographic locations, ensuring a smooth streaming experience.

具有 S3 传输加速功能的 Amazon S3 是视频点播平台最合适的解决方案，因为它提供了向全球观众流式传输视频内容所需的可扩展性、高吞吐量和低延迟。 S3 传输加速为不同地理位置的用户优化数据传输速度，确保流畅的流媒体体验。

The most suitable storage solution for frequently accessed video files with high performance and global scalability requirements is Amazon S3 with Transfer Acceleration. It leverages Amazon CloudFront's edge locations to deliver low-latency access to users worldwide, making it ideal for media streaming use cases. Other options like EFS, FSx, and S3 Glacier are not designed for this specific scenario.

对于经常访问且具有高性能和全局可扩展性要求的视频文件来说，最合适的存储解决方案是具有传输加速功能的 Amazon S3。它利用 Amazon CloudFront 的边缘位置为全球用户提供低延迟访问，使其成为媒体流用例的理想选择。 EFS、FSx 和 S3 Glacier 等其他选项并非针对此特定场景而设计。

The best solution is to store session data in Amazon ElastiCache for Redis. This service provides low-latency, in-memory data storage, making it ideal for session management. It ensures that session data is not tied to a specific EC2 instance, addressing the issue of session loss if an instance fails or is replaced. While other options, such as sticky sessions or Amazon RDS, may partially address the requirement, they do not provide the same level of scalability, performance, and fault tolerance as ElastiCache.

最好的解决方案是将会话数据存储在 Redis 的 Amazon ElastiCache 中。该服务提供低延迟的内存数据存储，使其成为会话管理的理想选择。它确保会话数据不绑定到特定的 EC2 实例，从而解决实例失败或被替换时会话丢失的问题。虽然其他选项（例如粘性会话或 Amazon RDS）可以部分满足要求，但它们无法提供与 ElastiCache 相同级别的可扩展性、性能和容错能力。

The most cost-effective solution to improve read-heavy database performance is to use Amazon RDS Read Replicas. Read Replicas allow you to offload read queries from the primary database, reducing the load on the primary instance and improving overall performance. Other options, like Multi-AZ or increasing instance size, do not specifically target read performance or may involve higher costs.

提高读取密集型数据库性能的最具成本效益的解决方案是使用 Amazon RDS 只读副本。只读副本允许您从主数据库卸载读取查询，从而减少主实例上的负载并提高整体性能。其他选项（例如多可用区或增加实例大小）并不专门针对读取性能或可能涉及更高的成本。

To secure an S3 bucket and allow access only from an ALB, you should use a bucket policy that restricts access based on the ALB's AWS account ID. This approach leverages AWS's native security mechanisms to ensure that only requests originating from the authorized ALB are allowed. Other methods, such as using a VPC endpoint or IP-based policies, are either unnecessary or unsuitable in this context.

要保护 S3 存储桶并仅允许从 ALB 进行访问，您应使用基于 ALB 的 AWS 账户 ID 限制访问的存储桶策略。此方法利用 AWS 的本机安全机制来确保仅允许来自授权 ALB 的请求。其他方法（例如使用 VPC 终端节点或基于 IP 的策略）在这种情况下要么是不必要的，要么是不适合的。

The best solution is to store the images in Amazon S3 and use Amazon CloudFront to cache the images. Amazon CloudFront is a content delivery network (CDN) that helps minimize latency and improves performance by delivering content from edge locations closest to the user, while also reducing costs by offloading traffic from the origin (S3).

最好的解决方案是将图像存储在 Amazon S3 中，并使用 Amazon CloudFront 来缓存图像。 Amazon CloudFront 是一种内容交付网络 (CDN)，可通过从最靠近用户的边缘位置交付内容来帮助最大限度地减少延迟并提高性能，同时还通过从源 (S3) 卸载流量来降低成本。

The AWS Storage Gateway in File Gateway mode is the best solution for hybrid storage requirements where frequently accessed data needs to be cached locally for low-latency access, and infrequent data is stored cost-effectively in Amazon S3. It seamlessly integrates on-premises environments with AWS storage services, meeting the business requirements outlined.

文件网关模式下的 AWS Storage Gateway 是满足混合存储需求的最佳解决方案，其中频繁访问的数据需要在本地缓存以实现低延迟访问，而不频繁的数据则经济高效地存储在 Amazon S3 中。它将本地环境与 AWS 存储服务无缝集成，满足概述的业务要求。

AWS Storage Gateway File Gateway is the best solution for this scenario as it provides a hybrid storage option that integrates seamlessly with on-premises environments. It enables low-latency access to frequently used files while storing less frequently accessed data in Amazon S3, meeting the regulatory and business requirements for hybrid storage and long-term archival.

AWS Storage Gateway 文件网关是此场景的最佳解决方案，因为它提供了与本地环境无缝集成的混合存储选项。它可以对常用文件进行低延迟访问，同时将不常访问的数据存储在 Amazon S3 中，满足混合存储和长期归档的法规和业务要求。

The AWS Storage Gateway in File Gateway configuration is specifically designed for hybrid storage architectures where low-latency access to active data is required on-premises, while securely archiving older data to Amazon S3. It enables seamless integration between on-premises applications and AWS storage, meeting the business requirements for this scenario.

文件网关配置中的 AWS Storage Gateway 专为需要在本地低延迟访问活动数据的混合存储架构而设计，同时将旧数据安全地存档到 Amazon S3。它可以实现本地应用程序与 AWS 存储之间的无缝集成，满足该场景的业务需求。

The company requires a hybrid storage solution to store frequently accessed media files on-premises while archiving infrequently accessed files to AWS. AWS Storage Gateway File Gateway is specifically designed for this use case, allowing seamless integration of on-premises storage with AWS cloud storage services like Amazon S3 and S3 Glacier. Other solutions mentioned either do not align with the hybrid storage requirement or are not suitable for managing large media files.

该公司需要一种混合存储解决方案来在本地存储经常访问的媒体文件，同时将不经常访问的文件存档到 AWS。 AWS Storage Gateway 文件网关专为此用例而设计，允许将本地存储与 Amazon S3 和 S3 Glacier 等 AWS 云存储服务无缝集成。提到的其他解决方案要么不符合混合存储要求，要么不适合管理大型媒体文件。

Amazon S3 is the most appropriate choice for this scenario because it is designed to handle large-scale object storage with high scalability and low-latency access. It integrates seamlessly with Amazon CloudFront, enabling global delivery of media files with a content delivery network. The other options, such as Amazon EBS, Amazon EFS, and Amazon FSx for Windows File Server, lack the scalability, CDN integration, or suitability for unpredictable traffic patterns required for this use case.

Amazon S3 是这种场景最合适的选择，因为它旨在处理具有高可扩展性和低延迟访问的大规模对象存储。它与 Amazon CloudFront 无缝集成，支持通过内容交付网络在全球范围内交付媒体文件。其他选项（例如适用于 Windows 文件服务器的 Amazon EBS、Amazon EFS 和 Amazon FSx）缺乏可扩展性、CDN 集成或对该用例所需的不可预测流量模式的适用性。

Amazon S3 is specifically designed to store objects such as images and provides features like high durability, public accessibility, and lifecycle management. These features align perfectly with the requirements of the given use case. Other services like Amazon EFS and Amazon EBS are not suitable as they are designed for different purposes, and AWS Snowball is a data transfer device, not a storage service.

Amazon S3 专门用于存储图像等对象，并提供高耐用性、公共可访问性和生命周期管理等功能。这些功能与给定用例的要求完美契合。其他服务（例如 Amazon EFS 和 Amazon EBS）不适合，因为它们是为不同的目的而设计的，并且 AWS Snowball 是数据传输设备，而不是存储服务。

The correct combination of storage services ensures the application meets its requirements. Amazon S3 is best suited for static content due to its scalability and cost-effectiveness. Amazon EFS is the optimal choice for shared storage required by media processing. For user profile data requiring low-latency access, Amazon EBS is the appropriate solution as it provides high-performance block storage attached to EC2 instances.

存储服务的正确组合可确保应用程序满足其要求。由于其可扩展性和成本效益，Amazon S3 最适合静态内容。 Amazon EFS 是媒体处理所需共享存储的最佳选择。对于需要低延迟访问的用户配置文件数据，Amazon EBS 是合适的解决方案，因为它提供附加到 EC2 实例的高性能块存储。

Amazon S3 is the best service for storing media files that need to be accessed frequently and durably with global reach. Enabling S3 Transfer Acceleration further reduces latency for users distributed worldwide by utilizing Amazon’s globally distributed CloudFront edge locations. Other options like EBS, EFS, and S3 Glacier Deep Archive are not suitable due to their specific use cases and limitations.

Amazon S3 是存储需要在全球范围内频繁、持久访问的媒体文件的最佳服务。通过利用 Amazon 全球分布的 CloudFront 边缘站点，启用 S3 传输加速可进一步减少分布在世界各地的用户的延迟。其他选项（如 EBS、EFS 和 S3 Glacier Deep Archive）由于其特定的用例和限制而不适合。

Each storage type has specific use cases. Amazon S3 is suitable for storing logs as it provides durable and scalable object storage. Amazon EFS offers a shared file system that can be accessed by multiple EC2 instances. Amazon EBS provides block-level storage optimized for performance-intensive workloads, such as databases. This combination effectively addresses all the use cases described in the question.

每种存储类型都有特定的用例。 Amazon S3 适合存储日志，因为它提供持久且可扩展的对象存储。 Amazon EFS 提供可由多个 EC2 实例访问的共享文件系统。 Amazon EBS 提供针对性能密集型工作负载（例如数据库）进行优化的块级存储。这种组合有效地解决了问题中描述的所有用例。

Amazon S3 is the best choice for this scenario because it is an object storage service optimized for storing unstructured data such as multimedia files and log data. It provides virtually unlimited scalability, high durability, and integrates with other AWS services like Amazon Athena, AWS Lambda, and Amazon Rekognition, making it well-suited for cloud-native applications requiring analytics and machine learning capabilities.

Amazon S3 是该场景的最佳选择，因为它是针对存储多媒体文件和日志数据等非结构化数据而优化的对象存储服务。它提供几乎无限的可扩展性、高耐用性，并与 Amazon Athena、AWS Lambda 和 Amazon Rekognition 等其他 AWS 服务集成，使其非常适合需要分析和机器学习功能的云原生应用程序。

For storing large-scale, unstructured data such as images, videos, and log files, Amazon S3 is the best choice. It is an object storage service offering high durability, scalability, and global access. Additionally, its integration with services like Amazon Athena makes it an excellent option for analytics use cases. Other storage types like EBS, EFS, and FSx are better suited for specific use cases such as block storage, file storage, or Windows-based file systems.

对于存储图像、视频和日志文件等大规模非结构化数据，Amazon S3 是最佳选择。它是一种对象存储服务，提供高持久性、可扩展性和全局访问能力。此外，它与 Amazon Athena 等服务的集成使其成为分析用例的绝佳选择。其他存储类型（例如 EBS、EFS 和 FSx）更适合特定用例，例如块存储、文件存储或基于 Windows 的文件系统。

The company's use case involves storing large video files with global accessibility and metadata tagging. Amazon S3 is the best choice because it is an object storage service designed for scalability, metadata management, and high availability across different regions. Other options, like Amazon EBS and EFS, are designed for different types of storage workloads, and AWS Storage Gateway is not applicable to this scenario.

该公司的用例涉及存储具有全局可访问性和元数据标记的大型视频文件。 Amazon S3 是最好的选择，因为它是一种对象存储服务，旨在实现跨区域的可扩展性、元数据管理和高可用性。其他选项（例如 Amazon EBS 和 EFS）是针对不同类型的存储工作负载而设计的，AWS Storage Gateway 不适用于此场景。

The best solution for high-traffic web applications with unpredictable spikes is to use an Auto Scaling group. This ensures the application can automatically scale in response to demand, providing both high performance and cost efficiency. Combining On-Demand and Spot Instances in the Auto Scaling group further optimizes costs while maintaining elasticity and reliability.

对于具有不可预测峰值的高流量 Web 应用程序，最佳解决方案是使用 Auto Scaling 组。这确保应用程序可以根据需求自动扩展，从而提供高性能和成本效益。在 Auto Scaling 组中结合按需实例和 Spot 实例可进一步优化成本，同时保持弹性和可靠性。

To design a high-performing and elastic compute solution for variable workloads, you should use Auto Scaling to dynamically adjust resources and Scheduled Scaling to handle predictable patterns. Elastic Load Balancing ensures traffic is evenly distributed across instances in multiple availability zones, improving resilience and performance. Avoid using a single large instance, as it is neither elastic nor fault-tolerant, and Spot Instances are inappropriate for critical workloads that require consistent availability.

要为可变工作负载设计高性能、弹性的计算解决方案，您应该使用 Auto Scaling 来动态调整资源，并使用 Scheduled Scaling 来处理可预测的模式。 Elastic Load Balancing 可确保流量在多个可用区的实例之间均匀分布，从而提高弹性和性能。避免使用单个大型实例，因为它既不具有弹性，也不具有容错能力，并且 Spot 实例不适合需要一致可用性的关键工作负载。

The best solution for handling unpredictable traffic spikes in a cost-effective and high-performing manner is to use an Auto Scaling group with dynamic scaling policies. This allows the number of EC2 instances to scale up or down automatically based on traffic demands, ensuring the application remains responsive while optimizing costs. Other options either require manual intervention, involve unnecessary architectural changes, or lead to over-provisioning and increased costs.

以经济高效且高性能的方式处理不可预测的流量峰值的最佳解决方案是使用具有动态扩展策略的 Auto Scaling 组。这允许 EC2 实例的数量根据流量需求自动增加或减少，确保应用程序保持响应，同时优化成本。其他选项要么需要手动干预，涉及不必要的架构更改，要么导致过度配置和成本增加。

To design a high-performing and elastic compute solution, an Auto Scaling group with target tracking scaling policies is the most appropriate choice. It dynamically adjusts the number of EC2 instances based on real-time metrics, such as CPU utilization, ensuring the application can handle traffic spikes while minimizing costs during low traffic periods. This approach aligns with AWS best practices for scalability and elasticity.

要设计高性能、弹性的计算解决方案，具有目标跟踪扩展策略的 Auto Scaling 组是最合适的选择。它根据实时指标（例如 CPU 利用率）动态调整 EC2 实例的数量，确保应用程序能够处理流量峰值，同时在低流量期间最大限度地降低成本。此方法符合 AWS 在可扩展性和弹性方面的最佳实践。

The best solution to handle high read traffic is to add read replicas to the Amazon RDS instance. Read replicas allow you to offload read queries from the primary database instance, improving performance and scalability. This solution is straightforward to implement and requires minimal changes to the existing application.

处理高读取流量的最佳解决方案是将只读副本添加到 Amazon RDS 实例。只读副本允许您从主数据库实例卸载读取查询，从而提高性能和可扩展性。该解决方案实施起来很简单，并且只需要对现有应用程序进行最少的更改。

To ensure high availability and disaster recovery in the event of a Regional outage, you need to deploy resources in multiple AWS Regions. Setting up a backup EC2 instance in the secondary Region and creating a cross-region read replica for the RDS database provides a disaster recovery solution. Additionally, using AWS Elastic Load Balancing for EC2 in multiple Regions and RDS Global Database ensures automated failover and minimal downtime, making these options the best solution for the given scenario.

为了确保区域中断时的高可用性和灾难恢复，您需要在多个 AWS 区域部署资源。在辅助 Region 中设置备份 EC2 实例并为 RDS 数据库创建跨区域只读副本提供了灾难恢复解决方案。此外，在多个区域中使用适用于 EC2 的 AWS Elastic Load Balancing 和 RDS 全局数据库可确保自动故障转移和最短的停机时间，使这些选项成为给定场景的最佳解决方案。

Amazon RDS is the most appropriate choice because it is a managed relational database service that supports structured data, high availability, scalability, and complex SQL queries, which are all requirements for the company's application. Other options like DynamoDB, Redshift, and S3 do not meet all the criteria for this specific use case.

Amazon RDS 是最合适的选择，因为它是托管关系数据库服务，支持结构化数据、高可用性、可扩展性和复杂的 SQL 查询，这些都是公司应用程序的要求。其他选项（例如 DynamoDB、Redshift 和 S3）不满足此特定用例的所有标准。

Amazon Elastic File System (EFS) is the best choice for this scenario because it is designed for applications that require shared file storage with low-latency access across multiple EC2 instances. EFS is fully managed, scalable, and persists independently of the lifecycle of individual instances, meeting all the requirements of the application.

Amazon Elastic File System (EFS) 是此场景的最佳选择，因为它专为需要跨多个 EC2 实例进行低延迟访问的共享文件存储的应用程序而设计。 EFS 是完全托管的、可扩展的，并且独立于各个实例的生命周期而持续存在，满足应用程序的所有要求。