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The destination is consistent at an accepted cutover point, applications use the intended endpoint, and rollback criteria are documented before retirement of source. This would validate Online migration with controlled cutover and validation, but it does not establish the required outcome here. Verify instead: The migration plan explicitly maps each source feature to a supported destination behavior and documented remediation before cutover.

New environment deployments match approved SKU, networking and identities while Fabric access follows supported synchronization and permission boundaries. This would validate Azure SQL deployment automation and Fabric SQL integration boundary, but it does not establish the required outcome here. Verify instead: The migration plan explicitly maps each source feature to a supported destination behavior and documented remediation before cutover.

Administrators can view authorized hybrid SQL inventory and policy findings while database files remain in their existing managed locations. This would validate Azure Arc-enabled SQL and hybrid fleet governance, but it does not establish the required outcome here. Verify instead: The migration plan explicitly maps each source feature to a supported destination behavior and documented remediation before cutover.

Inspect Query Store capture mode, runtime statistics, plan IDs, compatibility level, force-plan failure reasons and workload parameter distributions. These checks primarily test Query Store plan regressions and forced plans instead of the critical system behavior in this case. Examine: Inspect metric namespace, resource dimensions, aggregation periods, diagnostic destinations, alert scope, delivery permissions, action groups and sample timestamps.

Inspect event session predicates, event fields, ring buffer or event file targets, dropped events, blocked process reports and collection overhead. These checks primarily test Extended Events and workload-specific incident evidence instead of the critical system behavior in this case. Examine: Inspect metric namespace, resource dimensions, aggregation periods, diagnostic destinations, alert scope, delivery permissions, action groups and sample timestamps.

Inspect blocker/waiter SPIDs, wait_resource, open transactions, deadlock XML, isolation level, lock escalation and transaction duration. These checks primarily test Blocking deadlocks and isolation strategy instead of the critical system behavior in this case. Examine: Inspect metric namespace, resource dimensions, aggregation periods, diagnostic destinations, alert scope, delivery permissions, action groups and sample timestamps.

Design Azure SQL firewall policies and Private Link or approved service endpoints at the required scope, enforcing TLS and minimizing public endpoint exposure. This choice pertains to Azure SQL private endpoints firewall and TLS boundary, not the needed response/evidence pair. Use: Protect targeted sensitive objects through supported SQL encryption functions, key hierarchy and application threat model while distinguishing column encryption from network and storage encryption. Check: Review key hierarchy, certificate availability, encrypted payload format, authorized decryption path, T-SQL function usage, rotation and backup procedures.

Approved users can execute only intended tables, views and procedures, while unauthorized writes and administrative operations fail reproducibly. This choice pertains to Least-privilege SQL roles and ownership chaining, not the needed response/evidence pair. Use: Protect targeted sensitive objects through supported SQL encryption functions, key hierarchy and application threat model while distinguishing column encryption from network and storage encryption. Check: Review key hierarchy, certificate availability, encrypted payload format, authorized decryption path, T-SQL function usage, rotation and backup procedures.

Inspect sensitivity labels, masking expressions, UNMASK permissions, privileged role membership and direct query behavior across application identities. This choice pertains to Dynamic data masking classification and permission differences, not the needed response/evidence pair. Use: Protect targeted sensitive objects through supported SQL encryption functions, key hierarchy and application threat model while distinguishing column encryption from network and storage encryption. Check: Review key hierarchy, certificate availability, encrypted payload format, authorized decryption path, T-SQL function usage, rotation and backup procedures.

Compare CPU versus runnable tasks, WRITELOG, PAGEIOLATCH, resource governance, connection counts, tempdb usage, storage latency and times of workload change. These checks primarily test SQL operational baseline across waits locks and storage instead of the critical system behavior in this case. Examine: Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention.

Inspect blocker/waiter SPIDs, wait_resource, open transactions, deadlock XML, isolation level, lock escalation and transaction duration. These checks primarily test Blocking deadlocks and isolation strategy instead of the critical system behavior in this case. Examine: Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention.

Inspect metric namespace, resource dimensions, aggregation periods, diagnostic destinations, alert scope, delivery permissions, action groups and sample timestamps. These checks primarily test Azure Monitor alerts diagnostics and resource metrics instead of the critical system behavior in this case. Examine: Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention.

Use Query Store to compare query runtime and plan history, identify a genuine plan regression, and force a known suitable plan only with ongoing validation and rollback. This addresses Query Store plan regressions and forced plans, not the controlling requirement here. Forcing a historical plan can mitigate a regression but does not make poor statistics or parameter sensitivity disappear and may fail after schema changes. Prefer: Configure supported metrics, diagnostic settings and alerts for Azure SQL resources to detect real performance or availability regressions with correct thresholds and missing-data treatment.

Create a workload baseline and enable appropriate Azure SQL monitoring, including database watcher where supported, to correlate query behavior with resource saturation over time. This addresses Database watcher and Azure SQL monitoring baseline, not the controlling requirement here. Database watcher and Azure Monitor observe resource activity but do not by themselves repair a bad execution plan or guarantee metrics are complete. Prefer: Configure supported metrics, diagnostic settings and alerts for Azure SQL resources to detect real performance or availability regressions with correct thresholds and missing-data treatment.

Diagnose blocked and deadlocked sessions using live DMVs and deadlock graphs, then fix transaction scope, indexing or isolation behavior with concurrency tests. This addresses Blocking deadlocks and isolation strategy, not the controlling requirement here. Raising an app timeout does not remove a blocking root cause; snapshot isolation can reduce some reader/writer contention but changes version-store behavior. Prefer: Configure supported metrics, diagnostic settings and alerts for Azure SQL resources to detect real performance or availability regressions with correct thresholds and missing-data treatment.

Assess Managed Instance service tiers, built-in availability, failover groups and supported SQL Managed Instance link scenarios for hybrid resilience without inventing unsupported topologies. This choice pertains to Managed Instance hybrid recovery and operational readiness, not the needed response/evidence pair. Use: Test availability and recovery plans with realistic but controlled primary outages, application write workload, backups and rollback exercises before claiming a recovery objective. Check: Examine failover runbook owner, replica health, DNS and application retry time, last confirmed transaction, validation queries and restore evidence.

The secondary replays the intended log sequence and can be recovered with documented RPO/RTO and acceptable data loss when primary fails. This choice pertains to Log shipping health and recovery orchestration, not the needed response/evidence pair. Use: Test availability and recovery plans with realistic but controlled primary outages, application write workload, backups and rollback exercises before claiming a recovery objective. Check: Examine failover runbook owner, replica health, DNS and application retry time, last confirmed transaction, validation queries and restore evidence.

Inspect shared disk or supported file-share topology, Windows cluster validation, storage permissions, listener name, resource ownership and node failover tests. This choice pertains to SQL Server failover cluster instances shared storage constraints, not the needed response/evidence pair. Use: Test availability and recovery plans with realistic but controlled primary outages, application write workload, backups and rollback exercises before claiming a recovery objective. Check: Examine failover runbook owner, replica health, DNS and application retry time, last confirmed transaction, validation queries and restore evidence.

Design Azure SQL firewall policies and Private Link or approved service endpoints at the required scope, enforcing TLS and minimizing public endpoint exposure. This addresses Azure SQL private endpoints firewall and TLS boundary, not the controlling requirement here. A Private Endpoint does not provide correct DNS records automatically in every custom network; name resolution and access policy require separate verification. Prefer: Enable supported Transparent Data Encryption and choose managed or customer-managed protectors based on compliance, rotating keys without losing the ability to decrypt database backups.

Configure supported Microsoft Entra authentication and database users or contained identities for Azure SQL, ensuring the application principal receives only required permissions. This addresses Microsoft Entra authentication with contained service identity, not the controlling requirement here. A successful token request is not sufficient if the database principal, scope or permissions are missing or the token targets the wrong resource. Prefer: Enable supported Transparent Data Encryption and choose managed or customer-managed protectors based on compliance, rotating keys without losing the ability to decrypt database backups.

Select Entra or SQL authentication deliberately for Azure SQL Database, Managed Instance and SQL Server VMs based on platform support, application constraints and security controls. This addresses SQL authentication versus Entra and managed-instance principals, not the controlling requirement here. A login defined in one SQL Server instance is not automatically a contained user in another database or a globally valid Entra identity. Prefer: Enable supported Transparent Data Encryption and choose managed or customer-managed protectors based on compliance, rotating keys without losing the ability to decrypt database backups.

Approved managed-instance failover or hybrid transition works after controlled traffic redirection, with required instance features and logins present. This choice pertains to Managed Instance hybrid recovery and operational readiness, not the needed response/evidence pair. Use: Configure SQL Server log shipping across supported instances with reliable log backup, copy and restore schedules, delay and standby policies, then test manual recovery and ownership of jobs. Check: Inspect monitor-server history, last backup/copied/restored times, log chain continuity, share access, standby mode and restore delay.

Use supported SQL Server failover cluster instances on Azure virtual machines with compatible shared storage and cluster quorum instead of treating FCIs as data-replication AGs. This choice pertains to SQL Server failover cluster instances shared storage constraints, not the needed response/evidence pair. Use: Configure SQL Server log shipping across supported instances with reliable log backup, copy and restore schedules, delay and standby policies, then test manual recovery and ownership of jobs. Check: Inspect monitor-server history, last backup/copied/restored times, log chain continuity, share access, standby mode and restore delay.

Inspect backup URL, SAS or managed identity support by SQL version, container permissions, encryption/certificate material, backup headers and RESTORE VERIFYONLY caveats. This choice pertains to Backup to Azure Blob URL and tested cloud restore, not the needed response/evidence pair. Use: Configure SQL Server log shipping across supported instances with reliable log backup, copy and restore schedules, delay and standby policies, then test manual recovery and ownership of jobs. Check: Inspect monitor-server history, last backup/copied/restored times, log chain continuity, share access, standby mode and restore delay.

Repeatable deployments create the intended SQL resources in each subscription without silently broadening public network access or replacing production data. This choice pertains to ARM and Bicep declarative Azure SQL provisioning, not the needed response/evidence pair. Use: Investigate SQL Agent job-step execution context, timing and dependencies before retrying, and make destructive maintenance operations safe for partial reruns. Check: Inspect step command, proxy token, connection defaults, deadlocks, Agent history output, last success timestamp and job rerun behavior.

Configure SQL Server Agent schedules and job-step security on supported SQL Server or Managed Instance platforms, separating service credentials from the database data permissions they need. This choice pertains to SQL Server Agent schedules and job ownership, not the needed response/evidence pair. Use: Investigate SQL Agent job-step execution context, timing and dependencies before retrying, and make destructive maintenance operations safe for partial reruns. Check: Inspect step command, proxy token, connection defaults, deadlocks, Agent history output, last success timestamp and job rerun behavior.

Inspect deployment operation results, resource provider error codes, policy denials, what-if diffs, resource locks, template validation and database post-deploy health. This choice pertains to Deployment monitoring rollback and drift reconciliation, not the needed response/evidence pair. Use: Investigate SQL Agent job-step execution context, timing and dependencies before retrying, and make destructive maintenance operations safe for partial reruns. Check: Inspect step command, proxy token, connection defaults, deadlocks, Agent history output, last success timestamp and job rerun behavior.

Inspect template parameters, deployment scope, what-if output, module dependencies, identity role assignments and post-deploy effective configuration. These checks primarily test ARM and Bicep declarative Azure SQL provisioning instead of the critical system behavior in this case. Examine: Inspect automation account managed identity, runbook schedule, Azure Monitor action group, job output, retry policy, resource locks and target database state.

Inspect elastic job agent setup, target server groups, database-scoped credentials, schedule, job version, execution history and permissions. These checks primarily test Azure SQL Database elastic jobs for fleet maintenance instead of the critical system behavior in this case. Examine: Inspect automation account managed identity, runbook schedule, Azure Monitor action group, job output, retry policy, resource locks and target database state.

Inspect deployment operation results, resource provider error codes, policy denials, what-if diffs, resource locks, template validation and database post-deploy health. These checks primarily test Deployment monitoring rollback and drift reconciliation instead of the critical system behavior in this case. Examine: Inspect automation account managed identity, runbook schedule, Azure Monitor action group, job output, retry policy, resource locks and target database state.

Choose database vCore or DTU purchasing models, compute tier and elastic-pool membership from measured resource patterns, isolation needs and predictable workload peaks. This addresses Azure SQL Database service tiers and elastic pools, not the controlling requirement here. Elastic pools share resources across eligible Azure SQL databases; adding a pool cannot eliminate an individual database's workload or resource configuration limits. Prefer: Use supported backup/restore, BACPAC or database-copy methods based on source/target compatibility and offline downtime budget, then validate security, consistency and performance after migration.

Use a current migration assessment to inventory database dependencies, unsupported features, downtime constraints and target platform compatibility before moving data. This addresses Azure SQL migration assessment and feature compatibility, not the controlling requirement here. Successful schema import does not prove that instance-level jobs, security identities and linked dependencies survive a migration. Prefer: Use supported backup/restore, BACPAC or database-copy methods based on source/target compatibility and offline downtime budget, then validate security, consistency and performance after migration.

Size Managed Instance and SQL Server VM compute, storage latency and throughput using performance evidence, including correct storage-layout and platform support limits. This addresses Managed Instance and SQL VM compute storage scaling, not the controlling requirement here. Increasing CPU cannot fix a saturated log throughput budget or a storage path with high sustained write latency. Prefer: Use supported backup/restore, BACPAC or database-copy methods based on source/target compatibility and offline downtime budget, then validate security, consistency and performance after migration.