A reports an inadequate or failed acceptance condition: The simulated failure is allowed to exceed safety stop criteria without control. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that post-experiment records show observed recovery time and remediation for missed targets. The underlying design requirement is failure rehearsals validate recovery assumptions; an untested runbook is not proof of resilience.

C reports an inadequate or failed acceptance condition: A successful pre-release test is treated as proof after several untested new deployments. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that post-experiment records show observed recovery time and remediation for missed targets. The underlying design requirement is failure rehearsals validate recovery assumptions; an untested runbook is not proof of resilience.

D reports an inadequate or failed acceptance condition: A runbook document is current but no fault-injection drill measures recovery. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that post-experiment records show observed recovery time and remediation for missed targets. The underlying design requirement is failure rehearsals validate recovery assumptions; an untested runbook is not proof of resilience.

A would rely only on successful package upload as evidence that the new targets are serving traffic safely. This is not a defensible answer to the stated constraint (Deployments cause a high rate of incidents because all production instances are replaced at once): gradual traffic shifting and rollback reduce release blast radius compared with unobserved all-at-once updates. The required design is adopt monitored canary or blue/green rollout with automatic CloudWatch-alarm rollback; acceptance depends on evidence that a bad deployment fails in the canary cohort and old healthy targets regain production traffic.

B would deploy every new version to the whole fleet before checking production error rates. This is not a defensible answer to the stated constraint (Deployments cause a high rate of incidents because all production instances are replaced at once): gradual traffic shifting and rollback reduce release blast radius compared with unobserved all-at-once updates. The required design is adopt monitored canary or blue/green rollout with automatic CloudWatch-alarm rollback; acceptance depends on evidence that a bad deployment fails in the canary cohort and old healthy targets regain production traffic.

D would use canary routing but disable rollback when its error alarm triggers. This is not a defensible answer to the stated constraint (Deployments cause a high rate of incidents because all production instances are replaced at once): gradual traffic shifting and rollback reduce release blast radius compared with unobserved all-at-once updates. The required design is adopt monitored canary or blue/green rollout with automatic CloudWatch-alarm rollback; acceptance depends on evidence that a bad deployment fails in the canary cohort and old healthy targets regain production traffic.

A reports an inadequate or failed acceptance condition: A package deployment succeeds, but the former healthy target group never regains requests after rollback. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that a bad deployment fails in the canary cohort and old healthy targets regain production traffic. The underlying design requirement is gradual traffic shifting and rollback reduce release blast radius compared with unobserved all-at-once updates.

B reports an inadequate or failed acceptance condition: A full-fleet rollout reports some successful targets but all users saw high error rates. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that a bad deployment fails in the canary cohort and old healthy targets regain production traffic. The underlying design requirement is gradual traffic shifting and rollback reduce release blast radius compared with unobserved all-at-once updates.

C reports an inadequate or failed acceptance condition: A canary has elevated error metrics yet the release keeps receiving new traffic. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that a bad deployment fails in the canary cohort and old healthy targets regain production traffic. The underlying design requirement is gradual traffic shifting and rollback reduce release blast radius compared with unobserved all-at-once updates.

B would monitor API Gateway, Lambda, and DynamoDB metrics separately without a propagated trace identifier. This is not a defensible answer to the stated constraint (Operations cannot correlate Lambda, API Gateway and DynamoDB latency within one customer request): end-to-end traces reveal cross-service delays that isolated service averages conceal. The required design is implement trace propagation with AWS X-Ray or supported OpenTelemetry instrumentation and correlated request identifiers; acceptance depends on evidence that a trace shows API ingress, Lambda work, and database timings for the same request.

C would record only Lambda execution duration and infer which upstream customer request was affected. This is not a defensible answer to the stated constraint (Operations cannot correlate Lambda, API Gateway and DynamoDB latency within one customer request): end-to-end traces reveal cross-service delays that isolated service averages conceal. The required design is implement trace propagation with AWS X-Ray or supported OpenTelemetry instrumentation and correlated request identifiers; acceptance depends on evidence that a trace shows API ingress, Lambda work, and database timings for the same request.

D would add tracing to one service without correlating span context into downstream calls. This is not a defensible answer to the stated constraint (Operations cannot correlate Lambda, API Gateway and DynamoDB latency within one customer request): end-to-end traces reveal cross-service delays that isolated service averages conceal. The required design is implement trace propagation with AWS X-Ray or supported OpenTelemetry instrumentation and correlated request identifiers; acceptance depends on evidence that a trace shows API ingress, Lambda work, and database timings for the same request.

A reports an inadequate or failed acceptance condition: Separate service dashboards show normal averages but cannot trace an individual failed request. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that a trace shows API ingress, Lambda work, and database timings for the same request. The underlying design requirement is end-to-end traces reveal cross-service delays that isolated service averages conceal.

C reports an inadequate or failed acceptance condition: An API Gateway request ID disappears before the downstream Lambda and DynamoDB spans. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that a trace shows API ingress, Lambda work, and database timings for the same request. The underlying design requirement is end-to-end traces reveal cross-service delays that isolated service averages conceal.

D reports an inadequate or failed acceptance condition: Only Lambda duration is visible; the upstream and database latency contribution is unknown. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that a trace shows API ingress, Lambda work, and database timings for the same request. The underlying design requirement is end-to-end traces reveal cross-service delays that isolated service averages conceal.

A would create State Manager documents but never associate them with production targets. This is not a defensible answer to the stated constraint (A platform team wants the same configuration compliance policy in development and production accounts): state Manager can enforce desired operating state across managed nodes, unlike one-off shell edits. The required design is publish approved SSM documents and State Manager associations with account-scoped parameters; acceptance depends on evidence that association executions show drift correction and evidence per environment.

B would use one mutable set of environment variables with no account-scoped parameters or execution records. This is not a defensible answer to the stated constraint (A platform team wants the same configuration compliance policy in development and production accounts): state Manager can enforce desired operating state across managed nodes, unlike one-off shell edits. The required design is publish approved SSM documents and State Manager associations with account-scoped parameters; acceptance depends on evidence that association executions show drift correction and evidence per environment.

D would apply configuration manually in development and assume production remains consistent by naming convention. This is not a defensible answer to the stated constraint (A platform team wants the same configuration compliance policy in development and production accounts): state Manager can enforce desired operating state across managed nodes, unlike one-off shell edits. The required design is publish approved SSM documents and State Manager associations with account-scoped parameters; acceptance depends on evidence that association executions show drift correction and evidence per environment.

A reports an inadequate or failed acceptance condition: The State Manager document exists yet there are no successful association executions. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that association executions show drift correction and evidence per environment. The underlying design requirement is state Manager can enforce desired operating state across managed nodes, unlike one-off shell edits.

B reports an inadequate or failed acceptance condition: The same configuration values are used in different accounts even when account-specific parameters are required. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that association executions show drift correction and evidence per environment. The underlying design requirement is state Manager can enforce desired operating state across managed nodes, unlike one-off shell edits.

C reports an inadequate or failed acceptance condition: Development associations show compliance, but production node settings have diverged. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that association executions show drift correction and evidence per environment. The underlying design requirement is state Manager can enforce desired operating state across managed nodes, unlike one-off shell edits.

B would trigger branches independently but offer no execution history or human review for failures. This is not a defensible answer to the stated constraint (A distributed ETL pipeline needs workflow branching, retries, and human-reviewed failure handling): a state machine provides structured orchestration; chained Lambda invocations hide failure states and retries. The required design is model workflow steps in Step Functions with explicit retries, catches, and observable execution state; acceptance depends on evidence that failed branches follow documented compensations and every run has a traceable execution history.

C would run workflow steps as detached cron jobs with no durable run-level state. This is not a defensible answer to the stated constraint (A distributed ETL pipeline needs workflow branching, retries, and human-reviewed failure handling): a state machine provides structured orchestration; chained Lambda invocations hide failure states and retries. The required design is model workflow steps in Step Functions with explicit retries, catches, and observable execution state; acceptance depends on evidence that failed branches follow documented compensations and every run has a traceable execution history.

D would retry every failed ETL step without catch handling or a bounded exception path. This is not a defensible answer to the stated constraint (A distributed ETL pipeline needs workflow branching, retries, and human-reviewed failure handling): a state machine provides structured orchestration; chained Lambda invocations hide failure states and retries. The required design is model workflow steps in Step Functions with explicit retries, catches, and observable execution state; acceptance depends on evidence that failed branches follow documented compensations and every run has a traceable execution history.

A reports an inadequate or failed acceptance condition: Individual steps report success, but no execution history correlates them to one ETL workflow. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that failed branches follow documented compensations and every run has a traceable execution history. The underlying design requirement is a state machine provides structured orchestration; chained Lambda invocations hide failure states and retries.

C reports an inadequate or failed acceptance condition: A cron scheduler launches jobs but the branch and retry decisions cannot be reconstructed. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that failed branches follow documented compensations and every run has a traceable execution history. The underlying design requirement is a state machine provides structured orchestration; chained Lambda invocations hide failure states and retries.

D reports an inadequate or failed acceptance condition: A failed transformation retries indefinitely without entering the documented exception handler. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that failed branches follow documented compensations and every run has a traceable execution history. The underlying design requirement is a state machine provides structured orchestration; chained Lambda invocations hide failure states and retries.

A would page on every brief CPU spike regardless of customer error rate and SLO impact. This is not a defensible answer to the stated constraint (Engineers have inconsistent incident priorities because alerts are keyed to EC2 CPU but not application impact): business-service symptoms make better operational alerts than treating every resource utilization increase as failure. The required design is define service-level objectives and alarms on customer errors, latency, and saturation with runbook links; acceptance depends on evidence that an incident drill pages on objective violations and routes responders to relevant recovery actions.

B would use a weekly manual service report in place of actionable real-time SLO alerts. This is not a defensible answer to the stated constraint (Engineers have inconsistent incident priorities because alerts are keyed to EC2 CPU but not application impact): business-service symptoms make better operational alerts than treating every resource utilization increase as failure. The required design is define service-level objectives and alarms on customer errors, latency, and saturation with runbook links; acceptance depends on evidence that an incident drill pages on objective violations and routes responders to relevant recovery actions.

D would create latency dashboards but omit error budgets, severity policy, and runbook routing. This is not a defensible answer to the stated constraint (Engineers have inconsistent incident priorities because alerts are keyed to EC2 CPU but not application impact): business-service symptoms make better operational alerts than treating every resource utilization increase as failure. The required design is define service-level objectives and alarms on customer errors, latency, and saturation with runbook links; acceptance depends on evidence that an incident drill pages on objective violations and routes responders to relevant recovery actions.

A reports an inadequate or failed acceptance condition: CPU alarms page the team during healthy service while user-facing failures have no alert. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that an incident drill pages on objective violations and routes responders to relevant recovery actions. The underlying design requirement is business-service symptoms make better operational alerts than treating every resource utilization increase as failure.

B reports an inadequate or failed acceptance condition: An SLO document exists, but error-budget violations do not trigger paging. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that an incident drill pages on objective violations and routes responders to relevant recovery actions. The underlying design requirement is business-service symptoms make better operational alerts than treating every resource utilization increase as failure.

C reports an inadequate or failed acceptance condition: A latency chart identifies a problem but the responders receive no runbook or actionable incident link. This result does not establish the specified outcome for the current architecture. The decisive test must demonstrate that an incident drill pages on objective violations and routes responders to relevant recovery actions. The underlying design requirement is business-service symptoms make better operational alerts than treating every resource utilization increase as failure.