AWS CAF Platform perspective addresses a different objective, to establish technical foundations for hosting and building cloud workloads, because the Platform perspective addresses cloud engineering, architecture and platform capabilities; the checklist instead requires the distinct outcomes to replicate source servers for a largely lift-and-shift migration; prepare the workforce and organizational culture for cloud transformation.

AWS Cloud Adoption Framework (AWS CAF) addresses a different objective, to structure the organizational changes needed for cloud adoption, because AWS CAF organizes transformation capabilities into Business, People, Governance, Platform, Security and Operations perspectives; the checklist instead requires the distinct outcomes to replicate source servers for a largely lift-and-shift migration; prepare the workforce and organizational culture for cloud transformation.

AWS CAF Operations perspective addresses a different objective, to prepare support, monitoring and service operations for migrated workloads, because the Operations perspective develops capabilities for operating workloads effectively; the checklist instead requires the distinct outcomes to replicate source servers for a largely lift-and-shift migration; prepare the workforce and organizational culture for cloud transformation.

That description belongs to Operating expenditure (OpEx) because opEx reflects spending as services and computing resources are consumed; it is used to treat recurring service consumption as a running operational cost, not to explain how Spot capacity economics provides the function to save on flexible interruptible EC2 computing.

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 Spot capacity economics provides the function to save on flexible interruptible EC2 computing.

That description belongs to Capital expenditure (CapEx) because capEx involves purchasing owned assets such as servers and data-center equipment before the benefits are consumed; it is used to recognize upfront infrastructure purchase as a fixed investment, not to explain how Spot capacity economics provides the function to save on flexible interruptible EC2 computing.

Experimentation at low initial commitment addresses a different objective, to test a prototype without large upfront infrastructure investment, because usage-based provisioning enables limited experiments that can be shut down if unsuccessful; the checklist instead requires the distinct outcomes to make a proven application available in a newly targeted market quickly; scale test capacity up for an evaluation then stop consuming it.

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 make a proven application available in a newly targeted market quickly; scale test capacity up for an evaluation then stop consuming it.

High availability addresses a different objective, to keep an application accessible despite the failure of an individual component, because high availability relies on redundancy and failure isolation so a single failure need not interrupt service; the checklist instead requires the distinct outcomes to make a proven application available in a newly targeted market quickly; scale test capacity up for an evaluation then stop consuming it.

On-demand resource availability addresses the separate need to obtain computing resources when a new workload is ready to launch because cloud resources can be provisioned without owning and installing new data-center hardware first; it is not as direct as Agility for the actual requirement to experiment and deploy new ideas without a long hardware procurement cycle.

Self-service provisioning addresses the separate need 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; it is not as direct as Agility for the actual requirement to experiment and deploy new ideas without a long hardware procurement cycle.

Elastic test environments addresses the separate need to scale test capacity up for an evaluation then stop consuming it because temporary cloud test resources can be provisioned and removed with demand; it is not as direct as Agility for the actual requirement to experiment and deploy new ideas without a long hardware procurement cycle.

High availability addresses the separate need to keep an application accessible despite the failure of an individual component because high availability relies on redundancy and failure isolation so a single failure need not interrupt service; it is not as direct as Agility for the actual requirement to experiment and deploy new ideas without a long hardware procurement cycle.

Retire is intended to remove an application that no longer delivers sufficient business value because retirement eliminates unneeded systems from the future estate; in this design the new outcome is to connect cloud adoption to business outcomes and investment decisions, which calls for AWS CAF Business perspective rather than Retire or the earlier AWS Cloud Adoption Framework (AWS CAF).

AWS CAF Governance perspective is intended to manage transformation risks, priorities and portfolio decisions because the Governance perspective addresses decision-making, program oversight and value management; in this design the new outcome is to connect cloud adoption to business outcomes and investment decisions, which calls for AWS CAF Business perspective rather than AWS CAF Governance perspective or the earlier AWS Cloud Adoption Framework (AWS CAF).

AWS Cloud Adoption Framework (AWS CAF) primarily supports the earlier need to structure the organizational changes needed for cloud adoption because AWS CAF organizes transformation capabilities into Business, People, Governance, Platform, Security and Operations perspectives, but the new task is to connect cloud adoption to business outcomes and investment decisions; that is why AWS CAF Business perspective is preferable here.

Experiment-driven performance choices primarily supports the earlier need to benchmark workload alternatives before standardizing a configuration because measurement of actual application behavior supports appropriate performance trade-offs, but the new task is to match provisioned resources to measured workload requirements; that is why Right-sized architecture is preferable here.

Horizontal scaling is intended to spread work across additional independent resources because horizontal scaling increases the number of workers or instances serving a workload; in this design the new outcome is to match provisioned resources to measured workload requirements, which calls for Right-sized architecture rather than Horizontal scaling or the earlier Experiment-driven performance choices.

Reliability pillar is intended to help a workload recover from failures and continue functioning correctly because reliability covers recovery, capacity planning and resilience to infrastructure or service disruption; in this design the new outcome is to match provisioned resources to measured workload requirements, which calls for Right-sized architecture rather than Reliability pillar or the earlier Experiment-driven performance choices.

That description belongs to Avoided data-center costs because migrating suitable workloads can shift responsibility for physical facility operation to AWS; it is used to reduce expenses for facility space, power, cooling and physical maintenance, not to explain how Storage tier selection provides the function to reduce storage expense by matching access frequency to storage class.

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 Storage tier selection provides the function to reduce storage expense by matching access frequency to storage class.

That description belongs to Capital expenditure (CapEx) because capEx involves purchasing owned assets such as servers and data-center equipment before the benefits are consumed; it is used to recognize upfront infrastructure purchase as a fixed investment, not to explain how Storage tier selection provides the function to reduce storage expense by matching access frequency to storage class.

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 manage transformation risks, priorities and portfolio decisions, which calls for AWS CAF Governance perspective rather than AWS Cloud Adoption Framework (AWS CAF) or the earlier AWS CAF People perspective.

AWS CAF Business perspective is intended to connect cloud adoption to business outcomes and investment decisions because the Business perspective aligns cloud initiatives with strategy, value and commercial priorities; in this design the new outcome is to manage transformation risks, priorities and portfolio decisions, which calls for AWS CAF Governance perspective rather than AWS CAF Business perspective or the earlier AWS CAF People perspective.

AWS CAF People perspective primarily supports the earlier need to prepare the workforce and organizational culture for cloud transformation because the People perspective addresses skills, roles, workforce transformation and change management, but the new task is to manage transformation risks, priorities and portfolio decisions; that is why AWS CAF Governance perspective is preferable here.

Automation consistency addresses the separate need to repeat routine resource provisioning with fewer manual variations because automation applies repeatable processes rather than relying on individual manual changes; it is not as direct as Managed-service operational relief for the actual requirement to avoid administering an underlying platform for a common workload.

Experimentation at low initial commitment addresses the separate need to test a prototype without large upfront infrastructure investment because usage-based provisioning enables limited experiments that can be shut down if unsuccessful; it is not as direct as Managed-service operational relief for the actual requirement to avoid administering an underlying platform for a common workload.

Resource pooling addresses the separate need to benefit from provider-managed shared infrastructure without operating a dedicated facility because cloud providers abstract and share large infrastructure fleets while logically isolating customers; it is not as direct as Managed-service operational relief for the actual requirement to avoid administering an underlying platform for a common workload.

Variable cloud costs addresses a different objective, to align consumption-based expense with actual usage, because usage-based pricing lets spending change with resource consumption instead of requiring fixed purchased capacity; the checklist instead requires the distinct outcomes to pay for software license rights as part of an eligible cloud service charge; estimate future usage to avoid unplanned commitment or capacity decisions.

Economies of scale addresses a different objective, to benefit from infrastructure purchasing and operations at provider scale, because large cloud providers can spread infrastructure costs across broad demand and procurement volumes; the checklist instead requires the distinct outcomes to pay for software license rights as part of an eligible cloud service charge; estimate future usage to avoid unplanned commitment or capacity decisions.

Avoided data-center costs addresses a different objective, to reduce expenses for facility space, power, cooling and physical maintenance, because migrating suitable workloads can shift responsibility for physical facility operation to AWS; the checklist instead requires the distinct outcomes to pay for software license rights as part of an eligible cloud service charge; estimate future usage to avoid unplanned commitment or capacity decisions.

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 Security pillar for the requirement to protect information, systems and assets using risk-aware controls.

The best-performing option is not automatically the most sustainable or cheapest; that caveat is associated more closely with Performance efficiency pillar for the need to select and adapt resources to meet performance needs efficiently than with Security pillar for the requirement to protect information, systems and assets using risk-aware controls.

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 Security pillar for the requirement to protect information, systems and assets using risk-aware controls.