Refactor or re-architect is intended to modify an application to exploit cloud-native capabilities more substantially because refactoring changes design or code to gain capabilities such as managed services or elastic components; in this design the new outcome is to move an application to cloud infrastructure with minimal redesign, which calls for Rehost (lift and shift) rather than Refactor or re-architect or the earlier AWS Application Migration Service.

AWS Application Migration Service primarily supports the earlier need to replicate source servers for a largely lift-and-shift migration because application Migration Service supports server migration with continuous replication and automated conversion to run on AWS, but the new task is to move an application to cloud infrastructure with minimal redesign; that is why Rehost (lift and shift) is preferable here.

AWS Database Migration Service (AWS DMS) is intended to move or replicate database data to a supported target because AWS DMS supports migration and ongoing replication for suitable database engines; in this design the new outcome is to move an application to cloud infrastructure with minimal redesign, which calls for Rehost (lift and shift) rather than AWS Database Migration Service (AWS DMS) or the earlier AWS Application Migration Service.

Rapid global deployment is intended to make a proven application available in a newly targeted market quickly because cloud infrastructure in multiple geographic regions reduces the need to construct local facilities; in this design the new outcome is to keep an application accessible despite the failure of an individual component, which calls for High availability rather than Rapid global deployment or the earlier Fault tolerance.

Elasticity is intended to increase and decrease capacity in response to changing demand because elasticity matches provisioned resources to workload demand, allowing capacity to contract after a spike; in this design the new outcome is to keep an application accessible despite the failure of an individual component, which calls for High availability rather than Elasticity or the earlier Fault tolerance.

Fault tolerance primarily supports the earlier need to continue operating despite an individual infrastructure component failing because fault-tolerant systems absorb failures using redundancy, isolation and suitable application behavior, but the new task is to keep an application accessible despite the failure of an individual component; that is why High availability is preferable here.

That description belongs to Economies of scale because large cloud providers can spread infrastructure costs across broad demand and procurement volumes; it is used to benefit from infrastructure purchasing and operations at provider scale, not to explain how Bring Your Own License (BYOL) provides the function to reuse eligible existing software licenses under applicable provider terms.

That description belongs to Savings Plans commitment because savings Plans provide discounts for qualifying usage during a commitment term; it is used to obtain eligible compute discounts in exchange for a spending commitment, not to explain how Bring Your Own License (BYOL) provides the function to reuse eligible existing software licenses under applicable provider terms.

That description belongs to License-included pricing because license-included offerings bundle relevant licensing with the service price; it is used to pay for software license rights as part of an eligible cloud service charge, not to explain how Bring Your Own License (BYOL) provides the function to reuse eligible existing software licenses under applicable provider terms.

That description belongs to AWS Schema Conversion Tool (AWS SCT) because AWS SCT helps transform schema objects and certain database code between supported engines; it is used to convert database schema and code for a heterogeneous database migration, not to explain how AWS CAF Security perspective provides the function to embed protection, risk practices and security capabilities into migration.

That description belongs to AWS Migration Hub because migration Hub helps provide visibility across a portfolio's migration activity; it is used to track migration progress across applications and migration tools, not to explain how AWS CAF Security perspective provides the function to embed protection, risk practices and security capabilities into migration.

That description belongs to AWS Prescriptive Guidance because prescriptive Guidance provides proven strategies and technical patterns for cloud adoption; it is used to find practical AWS migration patterns and implementation guidance, not to explain how AWS CAF Security perspective provides the function to embed protection, risk practices and security capabilities into migration.

Geographic flexibility is intended to choose a physical deployment geography to address customers or regulatory constraints because AWS provides multiple Regions that can be selected for workloads and data; in this design the new outcome is to serve customers in distant geographies with regional deployments, which calls for Global reach rather than Geographic flexibility or the earlier Managed-service operational relief.

Elasticity is intended to increase and decrease capacity in response to changing demand because elasticity matches provisioned resources to workload demand, allowing capacity to contract after a spike; in this design the new outcome is to serve customers in distant geographies with regional deployments, which calls for Global reach rather than Elasticity or the earlier Managed-service operational relief.

Managed-service operational relief primarily supports the earlier need to avoid administering an underlying platform for a common workload because managed services move specific tasks such as database engine patching to AWS, but the new task is to serve customers in distant geographies with regional deployments; that is why Global reach is preferable here.

It is not limited to choosing the least expensive instance; that caveat is associated more closely with Operational excellence pillar for the need to improve how teams operate, monitor and continually refine workloads than with Sustainability pillar for the requirement to minimize environmental impact associated with running workloads.

It differs from performance efficiency, which emphasizes appropriate resource use; that caveat is associated more closely with Reliability pillar for the need to help a workload recover from failures and continue functioning correctly than with Sustainability pillar for the requirement to minimize environmental impact associated with running workloads.

Redundancy without access protection is not the same security objective; that caveat is associated more closely with Security pillar for the need to protect information, systems and assets using risk-aware controls than with Sustainability pillar for the requirement to minimize environmental impact associated with running workloads.

A subscription billed with usage is more like operating expenditure; that caveat is associated more closely with Capital expenditure (CapEx) for the need to recognize upfront infrastructure purchase as a fixed investment than with Avoided data-center costs for the requirement to reduce expenses for facility space, power, cooling and physical maintenance.

Archiving data needed immediately can introduce restore delay and fees; that caveat is associated more closely with Storage tier selection for the need to reduce storage expense by matching access frequency to storage class than with Avoided data-center costs for the requirement to reduce expenses for facility space, power, cooling and physical maintenance.

Visibility is a prerequisite for informed action, not a guarantee that cost will fall; that caveat is associated more closely with Cost visibility for the need to understand resource expenses before changing deployment decisions than with Avoided data-center costs for the requirement to reduce expenses for facility space, power, cooling and physical maintenance.

Some charges such as attached storage can continue after a VM stops; that caveat is associated more closely with Automation of shutdown schedules for the need to avoid running nonproduction compute unnecessarily than with Demand forecasting for the requirement to estimate future usage to avoid unplanned commitment or capacity decisions.

Visibility is a prerequisite for informed action, not a guarantee that cost will fall; that caveat is associated more closely with Cost visibility for the need to understand resource expenses before changing deployment decisions than with Demand forecasting for the requirement to estimate future usage to avoid unplanned commitment or capacity decisions.

A predictable workload can still benefit from suitable commitment discounts; that caveat is associated more closely with Variable cloud costs for the need to align consumption-based expense with actual usage than with Demand forecasting for the requirement to estimate future usage to avoid unplanned commitment or capacity decisions.

AWS Database Migration Service (AWS DMS) addresses the separate need to move or replicate database data to a supported target because AWS DMS supports migration and ongoing replication for suitable database engines; it is not as direct as Business continuity during migration for the actual requirement to plan service availability and rollback while changing environments.

AWS Migration Hub addresses the separate need to track migration progress across applications and migration tools because migration Hub helps provide visibility across a portfolio's migration activity; it is not as direct as Business continuity during migration for the actual requirement to plan service availability and rollback while changing environments.

Migration Evaluator addresses the separate need to develop a data-informed financial business case for migration because migration Evaluator supports assessing on-premises resource usage and potential AWS economics; it is not as direct as Business continuity during migration for the actual requirement to plan service availability and rollback while changing environments.

Global reach is intended to serve customers in distant geographies with regional deployments because AWS Regions allow workloads to run closer to users in multiple geographic markets; in this design the new outcome is to choose a physical deployment geography to address customers or regulatory constraints, which calls for Geographic flexibility rather than Global reach or the earlier Faster time to market.

Self-service provisioning is intended to create an environment without waiting for physical equipment installation because authorized teams can provision cloud resources through APIs or a console when they are needed; in this design the new outcome is to choose a physical deployment geography to address customers or regulatory constraints, which calls for Geographic flexibility rather than Self-service provisioning or the earlier Faster time to market.

Faster time to market primarily supports the earlier need to release a customer-facing capability with less infrastructure lead time because on-demand delivery of infrastructure helps shorten build and launch cycles, but the new task is to choose a physical deployment geography to address customers or regulatory constraints; that is why Geographic flexibility is preferable here.

Loose coupling addresses the separate need to allow application components to fail or scale with less direct dependency on each other because queues and asynchronous communication can decouple component lifecycles; it is not as direct as Experiment-driven performance choices for the actual requirement to benchmark workload alternatives before standardizing a configuration.

Continuous performance tuning addresses the separate need to revisit resource choices as application demand evolves because performance-efficient architectures update technology choices and capacity based on evidence; it is not as direct as Experiment-driven performance choices for the actual requirement to benchmark workload alternatives before standardizing a configuration.

Design for failure addresses the separate need to plan for individual components or zones becoming unavailable because resilient cloud designs anticipate disruption and use isolation and recovery behavior; it is not as direct as Experiment-driven performance choices for the actual requirement to benchmark workload alternatives before standardizing a configuration.