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This describes a scenario for AWS Global Accelerator: use AWS Global Accelerator for global network traffic entry and endpoint routing. Global Accelerator provides static anycast IP addresses and routes traffic over the AWS global network to healthy endpoints. It is not the most direct example of Data sovereignty Region choice.

This describes a scenario for Multiple Availability Zones: place redundant application components across different AZs within a Region. Multi-AZ deployments can avoid a single-AZ failure taking down the whole application. It is not the most direct example of Data sovereignty Region choice.

This describes a scenario for AWS edge location: use edge locations as points near users for supported edge services. AWS edge locations support services such as CloudFront and reduce delivery distance for content or requests. It is not the most direct example of Data sovereignty Region choice.

This describes a scenario for Spot Instances: use spare EC2 capacity at a discount with interruption risk. EC2 Spot Instances offer discounted unused capacity but can be reclaimed with interruption notices. It is not the most direct example of Savings Plans.

This describes a scenario for Dedicated Hosts: use Dedicated Hosts when eligible licensing requires host visibility and control. Dedicated Hosts supply dedicated EC2 physical server capacity with characteristics useful for supported bring-your-own-license needs. It is not the most direct example of Savings Plans.

This describes a scenario for AWS data transfer charges: account for service- and route-dependent data transfer pricing. Data entering AWS is often priced differently from outbound or cross-Region traffic; actual charges depend on service and path. It is not the most direct example of Savings Plans.

This describes a scenario for Amazon SageMaker AI: use Amazon SageMaker AI for managed machine learning development workflows. SageMaker AI supports building, training and deploying ML models rather than simply translating text. It is not the most direct example of AWS Glue.

This describes a scenario for Amazon Athena: use Amazon Athena for interactive SQL analysis over data in S3. Athena is a serverless interactive query service for supported data sources such as S3. It is not the most direct example of AWS Glue.

This describes a scenario for Amazon Lex: use Amazon Lex for building conversational interfaces. Lex provides conversational AI for chatbots and voice-enabled applications. It is not the most direct example of AWS Glue.

The roles are swapped. AWS Support Center is associated with use the AWS Support Center for eligible technical or account support cases; AWS Health Dashboard instead has the role: Review AWS Health Dashboard for service and account events. AWS Health provides information about relevant service disruptions and scheduled changes; it is distinct from an application metric alarm.

The roles are swapped. AWS Support plans is associated with review current AWS Support plans for eligible response and contact options; AWS Health Dashboard instead has the role: Review AWS Health Dashboard for service and account events. AWS Health provides information about relevant service disruptions and scheduled changes; it is distinct from an application metric alarm.

The roles are swapped. AWS Partner Network is associated with use AWS Partner Network resources to identify AWS partners and offerings; AWS Health Dashboard instead has the role: Review AWS Health Dashboard for service and account events. AWS Health provides information about relevant service disruptions and scheduled changes; it is distinct from an application metric alarm.

Amazon Inspector vulnerability findings is associated with a different use case: an administrator wants continuous assessments of supported workloads for software vulnerabilities. Inspector identifies package and supported workload vulnerabilities; it is not a replacement for data classification. The question instead focuses on a security team wants managed detection of suspicious activity from AWS account and workload signals; Amazon GuardDuty is the more direct match.

Encryption in transit is associated with a different use case: a company wants to protect data while it moves between clients and an online service. Encryption in transit protects communications over networks; it differs from encryption of data stored on disks. The question instead focuses on a security team wants managed detection of suspicious activity from AWS account and workload signals; Amazon GuardDuty is the more direct match.

AWS CloudHSM hardware keys is associated with a different use case: a company needs dedicated hardware security modules for particular cryptographic key requirements. CloudHSM provides customer-controlled HSM capacity for supported workloads requiring hardware-backed cryptographic operations. The question instead focuses on a security team wants managed detection of suspicious activity from AWS account and workload signals; Amazon GuardDuty is the more direct match.

This statement is true of AWS Step Functions, which addresses a business process needs a coordinated sequence of several AWS service tasks with branching states. It does not explain the particular role of Amazon EventBridge; EventBridge matches events against rules and directs them to supported targets.

This statement is true of Amazon Connect, which addresses a company wants a cloud-based customer contact center with voice and contact workflows. It does not explain the particular role of Amazon EventBridge; EventBridge matches events against rules and directs them to supported targets.

This statement is true of Amazon SES, which addresses a company must send transactional confirmation emails from its application. It does not explain the particular role of Amazon EventBridge; EventBridge matches events against rules and directs them to supported targets.

Retaining a workload instead focuses on a different requirement, such as a business must keep a legacy production system on premises until a contractual restriction expires. Retaining is an intentional decision to defer migration when business or technical constraints make an immediate move inappropriate. It is not the primary match for the requirement described here: decommission an unneeded application rather than migrate it.

AWS Database Migration Service instead focuses on a different requirement, such as a company wants to transfer database content to AWS while limiting downtime. AWS DMS can transfer data and support change data capture for applicable database migration scenarios. It is not the primary match for the requirement described here: decommission an unneeded application rather than migrate it.

Relocating a workload instead focuses on a different requirement, such as a company can move a supported virtualized environment to AWS while maintaining its familiar virtualization stack. Relocating retains much of the underlying virtualization model while shifting where it runs. It is not the primary match for the requirement described here: decommission an unneeded application rather than migrate it.

This statement is true of Cost Optimization pillar, which addresses a department wants to eliminate idle spending and understand the cost of delivering business value. It does not explain the particular role of Automated operational response; Automating repeatable operations reduces manual error and supports dependable responses while human review remains appropriate for sensitive changes.

This statement is true of Design for expected change, which addresses a company expects its cloud usage and business requirements to evolve frequently. It does not explain the particular role of Automated operational response; Automating repeatable operations reduces manual error and supports dependable responses while human review remains appropriate for sensitive changes.

This statement is true of Measure outcomes, which addresses a cloud team cannot tell whether a change improved customer-facing performance. It does not explain the particular role of Automated operational response; Automating repeatable operations reduces manual error and supports dependable responses while human review remains appropriate for sensitive changes.

This statement is true of Cross-account role access, which addresses an auditor from a separate AWS account needs time-limited access to approved audit resources. It does not explain the particular role of Multi-factor authentication; MFA requires another authentication factor beyond a password and reduces risks from compromised passwords.

This statement is true of Principle of least privilege, which addresses a developer only needs read access to one object storage bucket for a project. It does not explain the particular role of Multi-factor authentication; MFA requires another authentication factor beyond a password and reduces risks from compromised passwords.

This statement is true of Identity federation, which addresses a company wants staff to authenticate to AWS using its existing corporate identity provider. It does not explain the particular role of Multi-factor authentication; MFA requires another authentication factor beyond a password and reduces risks from compromised passwords.

This describes a scenario for Memory-optimized EC2: choose an EC2 memory-optimized instance family. Memory-optimized instances emphasize memory capacity relative to processing, fitting memory-intensive workloads. It is not the most direct example of Elastic Load Balancing.

This describes a scenario for AWS Lambda: use AWS Lambda for event-driven serverless function execution. Lambda executes event-triggered code without the customer managing underlying servers, subject to service limits. It is not the most direct example of Elastic Load Balancing.

This describes a scenario for Amazon Lightsail: use Amazon Lightsail for simplified cloud hosting. Lightsail offers simple virtual server and related resource plans for common small applications and websites. It is not the most direct example of Elastic Load Balancing.

Measure outcomes is associated with a different use case: a cloud team cannot tell whether a change improved customer-facing performance. The Well-Architected approach encourages observing real workload outcomes rather than relying only on resource existence. The question instead focuses on a department wants to eliminate idle spending and understand the cost of delivering business value; Cost Optimization pillar is the more direct match.

Automated operational response is associated with a different use case: operators repeatedly perform the same low-risk response to predictable workload events. Automating repeatable operations reduces manual error and supports dependable responses while human review remains appropriate for sensitive changes. The question instead focuses on a department wants to eliminate idle spending and understand the cost of delivering business value; Cost Optimization pillar is the more direct match.

Performance Efficiency pillar is associated with a different use case: a team compares computing approaches to meet response-time goals without unnecessary resources. The Performance Efficiency pillar focuses on choosing and adapting resources to match workload performance needs. The question instead focuses on a department wants to eliminate idle spending and understand the cost of delivering business value; Cost Optimization pillar is the more direct match.