Geographic flexibility addresses a different objective, 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; the checklist instead requires the distinct outcomes to benefit from provider-managed shared infrastructure without operating a dedicated facility; obtain computing resources when a new workload is ready to launch.

Elasticity addresses a different objective, 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; the checklist instead requires the distinct outcomes to benefit from provider-managed shared infrastructure without operating a dedicated facility; obtain computing resources when a new workload is ready to launch.

Automation consistency addresses a different objective, to repeat routine resource provisioning with fewer manual variations, because automation applies repeatable processes rather than relying on individual manual changes; the checklist instead requires the distinct outcomes to benefit from provider-managed shared infrastructure without operating a dedicated facility; obtain computing resources when a new workload is ready to launch.

Avoided data-center costs is intended to reduce expenses for facility space, power, cooling and physical maintenance because migrating suitable workloads can shift responsibility for physical facility operation to AWS; in this design the new outcome is to reduce storage expense by matching access frequency to storage class, which calls for Storage tier selection rather than Avoided data-center costs or the earlier Total cost of ownership (TCO).

Variable cloud costs is intended to align consumption-based expense with actual usage because usage-based pricing lets spending change with resource consumption instead of requiring fixed purchased capacity; in this design the new outcome is to reduce storage expense by matching access frequency to storage class, which calls for Storage tier selection rather than Variable cloud costs or the earlier Total cost of ownership (TCO).

Total cost of ownership (TCO) primarily supports the earlier need to compare the full cost of different infrastructure approaches because a TCO analysis considers hardware, software, operations, labor, facilities and cloud usage, but the new task is to reduce storage expense by matching access frequency to storage class; that is why Storage tier selection is preferable here.

AWS Migration Hub is intended to track migration progress across applications and migration tools because migration Hub helps provide visibility across a portfolio's migration activity; in this design the new outcome is to find practical AWS migration patterns and implementation guidance, which calls for AWS Prescriptive Guidance rather than AWS Migration Hub or the earlier AWS Schema Conversion Tool (AWS SCT).

AWS CAF Security perspective is intended to embed protection, risk practices and security capabilities into migration because the Security perspective helps establish security governance and resilient protective controls; in this design the new outcome is to find practical AWS migration patterns and implementation guidance, which calls for AWS Prescriptive Guidance rather than AWS CAF Security perspective or the earlier AWS Schema Conversion Tool (AWS SCT).

AWS Schema Conversion Tool (AWS SCT) primarily supports the earlier need to convert database schema and code for a heterogeneous database migration because AWS SCT helps transform schema objects and certain database code between supported engines, but the new task is to find practical AWS migration patterns and implementation guidance; that is why AWS Prescriptive Guidance is preferable here.

That description belongs to Automation of shutdown schedules because scheduled automation can stop or remove eligible idle resources when they are not required; it is used to avoid running nonproduction compute unnecessarily, not to explain how Demand forecasting provides the function to estimate future usage to avoid unplanned commitment or capacity decisions.

That description belongs to Cost visibility because cost reporting and allocation tools can reveal spend drivers that are less apparent in a shared data center; it is used to understand resource expenses before changing deployment decisions, not to explain how Demand forecasting provides the function to estimate future usage to avoid unplanned commitment or capacity decisions.

That description belongs to Variable cloud costs because usage-based pricing lets spending change with resource consumption instead of requiring fixed purchased capacity; it is used to align consumption-based expense with actual usage, not to explain how Demand forecasting provides the function to estimate future usage to avoid unplanned commitment or capacity decisions.

That description belongs to Reliability pillar because reliability covers recovery, capacity planning and resilience to infrastructure or service disruption; it is used to help a workload recover from failures and continue functioning correctly, not to explain how Right-sized architecture provides the function to match provisioned resources to measured workload requirements.

That description belongs to Horizontal scaling because horizontal scaling increases the number of workers or instances serving a workload; it is used to spread work across additional independent resources, not to explain how Right-sized architecture provides the function to match provisioned resources to measured workload requirements.

That description belongs to Experiment-driven performance choices because measurement of actual application behavior supports appropriate performance trade-offs; it is used to benchmark workload alternatives before standardizing a configuration, not to explain how Right-sized architecture provides the function to match provisioned resources to measured workload requirements.

Retain addresses a different objective, to leave a selected workload in its current environment for the time being, because retention is appropriate when migration is not yet justified or allowed; the checklist instead requires the distinct outcomes to identify which applications and infrastructure components rely on one another; replace an existing application with a different software product or SaaS solution.

AWS CAF Governance perspective addresses a different objective, to manage transformation risks, priorities and portfolio decisions, because the Governance perspective addresses decision-making, program oversight and value management; the checklist instead requires the distinct outcomes to identify which applications and infrastructure components rely on one another; replace an existing application with a different software product or SaaS solution.

AWS Application Migration Service addresses a different objective, 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; the checklist instead requires the distinct outcomes to identify which applications and infrastructure components rely on one another; replace an existing application with a different software product or SaaS solution.

That description belongs to Scalability because scalability is the ability of a system to handle growth by increasing resources or distributing work; it is used to support larger workloads by adding capacity as requirements grow, not to explain how Durability provides the function to reduce the likelihood of losing stored information over time.

That description belongs to Elasticity because elasticity matches provisioned resources to workload demand, allowing capacity to contract after a spike; it is used to increase and decrease capacity in response to changing demand, not to explain how Durability provides the function to reduce the likelihood of losing stored information over time.

That description belongs to Faster time to market because on-demand delivery of infrastructure helps shorten build and launch cycles; it is used to release a customer-facing capability with less infrastructure lead time, not to explain how Durability provides the function to reduce the likelihood of losing stored information over time.

Operating expenditure (OpEx) is intended to treat recurring service consumption as a running operational cost because opEx reflects spending as services and computing resources are consumed; in this design the new outcome is to avoid running nonproduction compute unnecessarily, which calls for Automation of shutdown schedules rather than Operating expenditure (OpEx) or the earlier Savings Plans commitment.

Savings Plans commitment primarily supports the earlier need to obtain eligible compute discounts in exchange for a spending commitment because savings Plans provide discounts for qualifying usage during a commitment term, but the new task is to avoid running nonproduction compute unnecessarily; that is why Automation of shutdown schedules is preferable here.

Demand forecasting is intended to estimate future usage to avoid unplanned commitment or capacity decisions because forecasts help teams plan spend and procurement based on usage trends; in this design the new outcome is to avoid running nonproduction compute unnecessarily, which calls for Automation of shutdown schedules rather than Demand forecasting or the earlier Savings Plans commitment.

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 spend less staff effort maintaining generic infrastructure components; that is why Reduced undifferentiated heavy lifting is preferable here.

Experimentation at low initial commitment is intended to test a prototype without large upfront infrastructure investment because usage-based provisioning enables limited experiments that can be shut down if unsuccessful; in this design the new outcome is to spend less staff effort maintaining generic infrastructure components, which calls for Reduced undifferentiated heavy lifting rather than Experimentation at low initial commitment or the earlier Faster time to market.

Fault tolerance is intended to continue operating despite an individual infrastructure component failing because fault-tolerant systems absorb failures using redundancy, isolation and suitable application behavior; in this design the new outcome is to spend less staff effort maintaining generic infrastructure components, which calls for Reduced undifferentiated heavy lifting rather than Fault tolerance or the earlier Faster time to market.

This does not eliminate the need to secure stored information; that caveat is associated more closely with Resource-efficient software for the need to avoid unnecessary processing and storage when delivering the same output than with Multi-AZ redundancy for the requirement to avoid tying service availability to one Availability Zone.

Optimizing a single pillar can create unintended consequences in another; that caveat is associated more closely with Trade-off evaluation for the need to consider competing architectural priorities instead of optimizing one metric blindly than with Multi-AZ redundancy for the requirement to avoid tying service availability to one Availability Zone.

Cutting needed redundancy may undermine reliability rather than optimize a workload appropriately; that caveat is associated more closely with Cost optimization pillar for the need to avoid unnecessary expenditure while achieving business outcomes than with Multi-AZ redundancy for the requirement to avoid tying service availability to one Availability Zone.

AWS Application Discovery Service primarily supports the earlier need to collect information about on-premises servers and dependencies for migration planning because discovery services help inventory workloads and understand application dependencies, but the new task is to plan service availability and rollback while changing environments; that is why Business continuity during migration is preferable here.

AWS Cloud Adoption Framework (AWS CAF) is intended to structure the organizational changes needed for cloud adoption because AWS CAF organizes transformation capabilities into Business, People, Governance, Platform, Security and Operations perspectives; in this design the new outcome is to plan service availability and rollback while changing environments, which calls for Business continuity during migration rather than AWS Cloud Adoption Framework (AWS CAF) or the earlier AWS Application Discovery Service.

AWS CAF Operations perspective is intended to prepare support, monitoring and service operations for migrated workloads because the Operations perspective develops capabilities for operating workloads effectively; in this design the new outcome is to plan service availability and rollback while changing environments, which calls for Business continuity during migration rather than AWS CAF Operations perspective or the earlier AWS Application Discovery Service.