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This check validates a different workload: Register one on-prem machine and confirm inventory/policy reports while it remains physically on-premises. Its associated design is: Use Azure Arc-enabled Servers to inventory hybrid machines and apply supported policies/extensions. The required acceptance test here is: Provision a trial workload and verify access, DNS, logging and compliance controls before migration.

The alternative test targets: Use discovered application dependency maps to group cutover waves with tested inter-service connectivity and rollback. The scenario's actual proposed remedy is: Build a ready Azure landing zone using management groups, subscriptions, governance policies, identity and network foundations. Verify that one by: Provision a trial workload and verify access, DNS, logging and compliance controls before migration.

This check validates a different workload: Compare recommendation sizing and total cost model with sampled observed VM metrics and licensing. Its associated design is: Use Azure Migrate assessment and business case cost estimates grounded in discovered utilization and licensing assumptions. The required acceptance test here is: Provision a trial workload and verify access, DNS, logging and compliance controls before migration.

This cause would explain a different symptom: The first migrated app is unusable because its required database remains unreachable on-premises. The mechanism for that event is: Migration order ignored dependency connectivity and shared service placement. Here the stated symptom is: Migrated apps deploy into ad hoc subscriptions lacking logging, identity and routing controls. Its cause is: The destination landing zone was not prepared for migration waves.

The proposed diagnosis fits another scenario: The cost model ignores actual measured utilization and licensing optimization. It would typically be reflected by: A migration proposal assumes every on-prem CPU must map to an equally large Azure VM. The current evidence instead supports: The destination landing zone was not prepared for migration waves.

This cause would explain a different symptom: A migration dashboard excludes critical servers until their final Azure VM cutover. The mechanism for that event is: The hybrid governance model incorrectly limits inventory to cloud-native servers. Here the stated symptom is: Migrated apps deploy into ad hoc subscriptions lacking logging, identity and routing controls. Its cause is: The destination landing zone was not prepared for migration waves.

This is a reasonable safeguard for a different fault: A migration proposal assumes every on-prem CPU must map to an equally large Azure VM. That different mechanism is: The cost model ignores actual measured utilization and licensing optimization. The original incident here instead arises from: The destination landing zone was not prepared for migration waves. The directly relevant safeguard is: Validate landing-zone readiness gates for each new subscription.

The proposed control focuses on: Migration order ignored dependency connectivity and shared service placement. For the design in the question, recurrence comes from: The destination landing zone was not prepared for migration waves. A precise prevention step is: Validate landing-zone readiness gates for each new subscription.

That safeguard manages another risk: The hybrid governance model incorrectly limits inventory to cloud-native servers. Its scenario is: A migration dashboard excludes critical servers until their final Azure VM cutover. The present recurring risk is: The destination landing zone was not prepared for migration waves. The proper ongoing control is: Validate landing-zone readiness gates for each new subscription.

The option belongs to a different failure mechanism: Database service selection preceded discovery of instance-level feature requirements. That situation exhibits: Applications are moved to Azure SQL Database then break due to unassessed SQL Agent dependencies. For the stated case, the remedy is: Use Azure Migrate assessment and business case cost estimates grounded in discovered utilization and licensing assumptions.

That design instead addresses another observed condition: A one-time disk copy causes extended outage and incomplete changes after initial transfer. Its technical cause is: A continuous migration replication and controlled cutover process was not planned. The current workload exhibits: A migration proposal assumes every on-prem CPU must map to an equally large Azure VM. Its targeted remedy is: Use Azure Migrate assessment and business case cost estimates grounded in discovered utilization and licensing assumptions.

This choice mitigates an alternative scenario, where: Migration planning uses manually guessed VM sizes and misses application dependencies. The underlying issue there is: No structured server discovery and utilization assessment was completed. Here the root issue is: The cost model ignores actual measured utilization and licensing optimization. Choose the corresponding action: Use Azure Migrate assessment and business case cost estimates grounded in discovered utilization and licensing assumptions.

That observation pertains to a separate failure: Migration planning uses manually guessed VM sizes and misses application dependencies. Its cause is: No structured server discovery and utilization assessment was completed. It does not confirm the result of this design. The direct proof would be: Compare recommendation sizing and total cost model with sampled observed VM metrics and licensing.

This check validates a different workload: Run a nonproduction test migration and validate application services before committing final cutover. Its associated design is: Use the supported Azure Migrate server-migration workflow with replication, test migration and final cutover. The required acceptance test here is: Compare recommendation sizing and total cost model with sampled observed VM metrics and licensing.

That observation pertains to a separate failure: Applications are moved to Azure SQL Database then break due to unassessed SQL Agent dependencies. Its cause is: Database service selection preceded discovery of instance-level feature requirements. It does not confirm the result of this design. The direct proof would be: Compare recommendation sizing and total cost model with sampled observed VM metrics and licensing.

The proposed diagnosis fits another scenario: No structured server discovery and utilization assessment was completed. It would typically be reflected by: Migration planning uses manually guessed VM sizes and misses application dependencies. The current evidence instead supports: The cost model ignores actual measured utilization and licensing optimization.

The alternative weakness is: Database service selection preceded discovery of instance-level feature requirements. Its associated failure is: Applications are moved to Azure SQL Database then break due to unassessed SQL Agent dependencies. Neither explains the present observation: A migration proposal assumes every on-prem CPU must map to an equally large Azure VM. The direct cause here is: The cost model ignores actual measured utilization and licensing optimization.

This cause would explain a different symptom: A one-time disk copy causes extended outage and incomplete changes after initial transfer. The mechanism for that event is: A continuous migration replication and controlled cutover process was not planned. Here the stated symptom is: A migration proposal assumes every on-prem CPU must map to an equally large Azure VM. Its cause is: The cost model ignores actual measured utilization and licensing optimization.

This is a reasonable safeguard for a different fault: Migration planning uses manually guessed VM sizes and misses application dependencies. That different mechanism is: No structured server discovery and utilization assessment was completed. The original incident here instead arises from: The cost model ignores actual measured utilization and licensing optimization. The directly relevant safeguard is: Refresh the cost model when rightsizing and workload commitments change.

The proposed control focuses on: A continuous migration replication and controlled cutover process was not planned. For the design in the question, recurrence comes from: The cost model ignores actual measured utilization and licensing optimization. A precise prevention step is: Refresh the cost model when rightsizing and workload commitments change.

That safeguard manages another risk: Database service selection preceded discovery of instance-level feature requirements. Its scenario is: Applications are moved to Azure SQL Database then break due to unassessed SQL Agent dependencies. The present recurring risk is: The cost model ignores actual measured utilization and licensing optimization. The proper ongoing control is: Refresh the cost model when rightsizing and workload commitments change.

The option belongs to a different failure mechanism: The destination landing zone was not prepared for migration waves. That situation exhibits: Migrated apps deploy into ad hoc subscriptions lacking logging, identity and routing controls. For the stated case, the remedy is: Use discovered application dependency maps to group cutover waves with tested inter-service connectivity and rollback.

That design instead addresses another observed condition: The migrated site fails because an unsupported local COM component remains essential. Its technical cause is: PaaS suitability and application dependencies were not assessed before migration. The current workload exhibits: The first migrated app is unusable because its required database remains unreachable on-premises. Its targeted remedy is: Use discovered application dependency maps to group cutover waves with tested inter-service connectivity and rollback.

The option belongs to a different failure mechanism: Rollback ownership and write-direction controls were not defined. That situation exhibits: Both old and new databases accept conflicting updates after a failed migration cutover. For the stated case, the remedy is: Use discovered application dependency maps to group cutover waves with tested inter-service connectivity and rollback.

The alternative test targets: Establish pre-cutover synchronization, validation checkpoints, source write-freeze/rollback plan and recovery roles. The scenario's actual proposed remedy is: Use discovered application dependency maps to group cutover waves with tested inter-service connectivity and rollback. Verify that one by: Cut over a low-risk cohort and verify dependent login, database and message flows before the next wave.

This check validates a different workload: Deploy a pilot on App Service and test application endpoints and dependent services. Its associated design is: Use a supported App Service migration/readiness assessment and verify framework, authentication and dependency constraints. The required acceptance test here is: Cut over a low-risk cohort and verify dependent login, database and message flows before the next wave.

The alternative test targets: Build a ready Azure landing zone using management groups, subscriptions, governance policies, identity and network foundations. The scenario's actual proposed remedy is: Use discovered application dependency maps to group cutover waves with tested inter-service connectivity and rollback. Verify that one by: Cut over a low-risk cohort and verify dependent login, database and message flows before the next wave.

The alternative weakness is: The destination landing zone was not prepared for migration waves. Its associated failure is: Migrated apps deploy into ad hoc subscriptions lacking logging, identity and routing controls. Neither explains the present observation: The first migrated app is unusable because its required database remains unreachable on-premises. The direct cause here is: Migration order ignored dependency connectivity and shared service placement.

This cause would explain a different symptom: Both old and new databases accept conflicting updates after a failed migration cutover. The mechanism for that event is: Rollback ownership and write-direction controls were not defined. Here the stated symptom is: The first migrated app is unusable because its required database remains unreachable on-premises. Its cause is: Migration order ignored dependency connectivity and shared service placement.

The proposed diagnosis fits another scenario: PaaS suitability and application dependencies were not assessed before migration. It would typically be reflected by: The migrated site fails because an unsupported local COM component remains essential. The current evidence instead supports: Migration order ignored dependency connectivity and shared service placement.

The proposed control focuses on: PaaS suitability and application dependencies were not assessed before migration. For the design in the question, recurrence comes from: Migration order ignored dependency connectivity and shared service placement. A precise prevention step is: Maintain wave sequencing and connectivity tests as dependencies are uncovered.

That safeguard manages another risk: The destination landing zone was not prepared for migration waves. Its scenario is: Migrated apps deploy into ad hoc subscriptions lacking logging, identity and routing controls. The present recurring risk is: Migration order ignored dependency connectivity and shared service placement. The proper ongoing control is: Maintain wave sequencing and connectivity tests as dependencies are uncovered.

The proposed control focuses on: Rollback ownership and write-direction controls were not defined. For the design in the question, recurrence comes from: Migration order ignored dependency connectivity and shared service placement. A precise prevention step is: Maintain wave sequencing and connectivity tests as dependencies are uncovered.