Spot capacity economics addresses the separate need to save on flexible interruptible EC2 computing because Spot Instances exploit spare EC2 capacity at discounted rates with interruption risk; it is not as direct as Savings Plans commitment for the actual requirement to obtain eligible compute discounts in exchange for a spending commitment.

Capital expenditure (CapEx) addresses the separate need to recognize upfront infrastructure purchase as a fixed investment because capEx involves purchasing owned assets such as servers and data-center equipment before the benefits are consumed; it is not as direct as Savings Plans commitment for the actual requirement to obtain eligible compute discounts in exchange for a spending commitment.

Variable cloud costs addresses the separate need to align consumption-based expense with actual usage because usage-based pricing lets spending change with resource consumption instead of requiring fixed purchased capacity; it is not as direct as Savings Plans commitment for the actual requirement to obtain eligible compute discounts in exchange for a spending commitment.

Scalability is intended to support larger workloads by adding capacity as requirements grow because scalability is the ability of a system to handle growth by increasing resources or distributing work; in this design the new outcome is to repeat routine resource provisioning with fewer manual variations, which calls for Automation consistency rather than Scalability or the earlier On-demand resource availability.

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 repeat routine resource provisioning with fewer manual variations, which calls for Automation consistency rather than Elasticity or the earlier On-demand resource availability.

On-demand resource availability primarily supports the earlier 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, but the new task is to repeat routine resource provisioning with fewer manual variations; that is why Automation consistency is preferable here.

Assuming hardware cannot fail creates avoidable single points of failure; that caveat is associated more closely with Design for failure for the need to plan for individual components or zones becoming unavailable than with Loose coupling for the requirement to allow application components to fail or scale with less direct dependency on each other.

A configuration suitable at launch may be inefficient after usage changes; that caveat is associated more closely with Continuous performance tuning for the need to revisit resource choices as application demand evolves than with Loose coupling for the requirement to allow application components to fail or scale with less direct dependency on each other.

Automation complements but does not replace valid failure-testing plans; that caveat is associated more closely with Automate recovery for the need to restore normal application behavior without waiting for routine manual intervention than with Loose coupling for the requirement to allow application components to fail or scale with less direct dependency on each other.

That description belongs to Self-service provisioning because authorized teams can provision cloud resources through APIs or a console when they are needed; it is used to create an environment without waiting for physical equipment installation, not to explain how Experimentation at low initial commitment provides the function to test a prototype without large upfront infrastructure investment.

That description belongs to Resource pooling because cloud providers abstract and share large infrastructure fleets while logically isolating customers; it is used to benefit from provider-managed shared infrastructure without operating a dedicated facility, not to explain how Experimentation at low initial commitment provides the function to test a prototype without large upfront infrastructure investment.

That description belongs to Fault tolerance because fault-tolerant systems absorb failures using redundancy, isolation and suitable application behavior; it is used to continue operating despite an individual infrastructure component failing, not to explain how Experimentation at low initial commitment provides the function to test a prototype without large upfront infrastructure investment.

AWS CAF Governance perspective addresses the separate need to manage transformation risks, priorities and portfolio decisions because the Governance perspective addresses decision-making, program oversight and value management; it is not as direct as Retire for the actual requirement to remove an application that no longer delivers sufficient business value.

Repurchase addresses the separate need to replace an existing application with a different software product or SaaS solution because repurchasing selects a new commercial offering rather than migrating the same software deployment unchanged; it is not as direct as Retire for the actual requirement to remove an application that no longer delivers sufficient business value.

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 Retire for the actual requirement to remove an application that no longer delivers sufficient business value.

That description belongs to Loose coupling because queues and asynchronous communication can decouple component lifecycles; it is used to allow application components to fail or scale with less direct dependency on each other, not to explain how Design for failure provides the function to plan for individual components or zones becoming unavailable.

That description belongs to Security pillar because the security pillar addresses identities, detection, infrastructure and data protection, and incident response; it is used to protect information, systems and assets using risk-aware controls, not to explain how Design for failure provides the function to plan for individual components or zones becoming unavailable.

That description belongs to Operational excellence pillar because operational excellence focuses on delivering business value through effective operations and continuous learning; it is used to improve how teams operate, monitor and continually refine workloads, not to explain how Design for failure provides the function to plan for individual components or zones becoming unavailable.

Resource tagging for accountability addresses a different objective, to attribute cloud spending to teams and projects, because consistent resource tags support reporting and ownership when activated for cost allocation; the checklist instead requires the distinct outcomes to reuse eligible existing software licenses under applicable provider terms; remove overprovisioning based on workload measurements.

Savings Plans commitment addresses a different objective, to obtain eligible compute discounts in exchange for a spending commitment, because savings Plans provide discounts for qualifying usage during a commitment term; the checklist instead requires the distinct outcomes to reuse eligible existing software licenses under applicable provider terms; remove overprovisioning based on workload measurements.

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 reuse eligible existing software licenses under applicable provider terms; remove overprovisioning based on workload measurements.

AWS CAF Governance perspective addresses the separate need to manage transformation risks, priorities and portfolio decisions because the Governance perspective addresses decision-making, program oversight and value management; it is not as direct as Rehost (lift and shift) for the actual requirement to move an application to cloud infrastructure with minimal redesign.

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 Rehost (lift and shift) for the actual requirement to move an application to cloud infrastructure with minimal redesign.

AWS CAF Business perspective addresses the separate need to connect cloud adoption to business outcomes and investment decisions because the Business perspective aligns cloud initiatives with strategy, value and commercial priorities; it is not as direct as Rehost (lift and shift) for the actual requirement to move an application to cloud infrastructure with minimal redesign.

Faster time to market addresses a different objective, to release a customer-facing capability with less infrastructure lead time, because on-demand delivery of infrastructure helps shorten build and launch cycles; the checklist instead requires the distinct outcomes to choose a physical deployment geography to address customers or regulatory constraints; support larger workloads by adding capacity as requirements grow.

Rapid global deployment addresses a different objective, 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; the checklist instead requires the distinct outcomes to choose a physical deployment geography to address customers or regulatory constraints; support larger workloads by adding capacity as requirements grow.

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 choose a physical deployment geography to address customers or regulatory constraints; support larger workloads by adding capacity as requirements grow.

Resource-efficient software addresses the separate need to avoid unnecessary processing and storage when delivering the same output because reducing wasted computation contributes to performance and sustainability objectives; it is not as direct as Cost optimization pillar for the actual requirement to avoid unnecessary expenditure while achieving business outcomes.

Operational excellence pillar addresses the separate need to improve how teams operate, monitor and continually refine workloads because operational excellence focuses on delivering business value through effective operations and continuous learning; it is not as direct as Cost optimization pillar for the actual requirement to avoid unnecessary expenditure while achieving business outcomes.

Vertical scaling addresses the separate need to increase the capacity of an existing compute resource because vertical scaling changes the size or power of one instance or server; it is not as direct as Cost optimization pillar for the actual requirement to avoid unnecessary expenditure while achieving business outcomes.

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 Rightsizing for the requirement to remove overprovisioning based on workload measurements.

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 Rightsizing for the requirement to remove overprovisioning based on workload measurements.

It differs from owning hardware that is capitalized up front; that caveat is associated more closely with Operating expenditure (OpEx) for the need to treat recurring service consumption as a running operational cost than with Rightsizing for the requirement to remove overprovisioning based on workload measurements.