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After resizing or tuning storage, relevant workload bottlenecks improve without breaching instance compatibility, availability or maintenance requirements. This would validate Managed Instance and SQL VM compute storage scaling, but it does not establish the required outcome here. Verify instead: Administrators can view authorized hybrid SQL inventory and policy findings while database files remain in their existing managed locations.

The deployed database meets compatibility and service-management requirements without unnecessary virtual-machine maintenance or unsupported instance features. This would validate Choosing Azure SQL Database versus Managed Instance versus SQL VM, but it does not establish the required outcome here. Verify instead: Administrators can view authorized hybrid SQL inventory and policy findings while database files remain in their existing managed locations.

The migrated service opens with consistent data, working identities and restored application workflows within the agreed maintenance period. This would validate Offline migration and post-migration verification, but it does not establish the required outcome here. Verify instead: Administrators can view authorized hybrid SQL inventory and policy findings while database files remain in their existing managed locations.

A recoverable backup is stored under controlled access and a real restore exercise proves the chain, keys and application consistency requirements. 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.

Inspect replication state, endpoint listeners, failover policy, allowed data loss, application reconnect errors, secondary region capacity and DNS cache behavior. This choice pertains to Azure SQL Database active geo replication and failover groups, 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 predicate selectivity, partition elimination, split/merge plans, aligned indexes, compression CPU overhead and real data size reduction. These checks primarily test Table partitioning compression and scale-out tradeoffs instead of the critical system behavior in this case. Examine: Inspect CPU, data IO, log write, storage, concurrent sessions, DTU/vCore utilization, pool-level pressure and per-database limits.

Compare database offering capabilities, deployment parameters, identity, networking, Fabric integration support, source control and tenant governance before provisioning. These checks primarily test Azure SQL deployment automation and Fabric SQL integration boundary instead of the critical system behavior in this case. Examine: Inspect CPU, data IO, log write, storage, concurrent sessions, DTU/vCore utilization, pool-level pressure and per-database limits.

Collect source version, compatibility level, blockers, logins, SQL Agent jobs, linked servers, TDE key dependencies, storage size and application integration map. These checks primarily test Azure SQL migration assessment and feature compatibility instead of the critical system behavior in this case. Examine: Inspect CPU, data IO, log write, storage, concurrent sessions, DTU/vCore utilization, pool-level pressure and per-database limits.

Inspect diagnostic recommendations, Query Store plan variability, runtime skew, parameter compilation, memory grant feedback and database compatibility settings. These checks primarily test Intelligent Insights and parameter-sensitive query analysis instead of the critical system behavior in this case. Examine: Inspect scans/seeks, key lookup counts, implicit conversions, estimated-versus-actual rows, missing-index recommendations and write amplification.

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 scans/seeks, key lookup counts, implicit conversions, estimated-versus-actual rows, missing-index recommendations and write amplification.

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: Inspect scans/seeks, key lookup counts, implicit conversions, estimated-versus-actual rows, missing-index recommendations and write amplification.

The SQL Server instance restarts on an eligible node using accessible shared data and log storage while the application resolves the cluster virtual network name. This would validate SQL Server failover cluster instances shared storage constraints, but it does not establish the required outcome here. Verify instead: A restore to the required historical point completes into a supported database target and data plus dependent identities are validated.

The application reconnects through the intended endpoint after a tested supported failover, with documented possible data loss and read/write behavior. This would validate Azure SQL failover groups versus active geo replication decisions, but it does not establish the required outcome here. Verify instead: A restore to the required historical point completes into a supported database target and data plus dependent identities are validated.

A recoverable backup is stored under controlled access and a real restore exercise proves the chain, keys and application consistency requirements. This would validate Backup to Azure Blob URL and tested cloud restore, but it does not establish the required outcome here. Verify instead: A restore to the required historical point completes into a supported database target and data plus dependent identities are validated.

Inspect metric namespace, resource dimensions, aggregation periods, diagnostic destinations, alert scope, delivery permissions, action groups and sample timestamps. This choice pertains to Azure Monitor alerts diagnostics and resource metrics, not the needed response/evidence pair. Use: Review actual execution plans, predicate sargability, cardinality estimates and suitable index designs before adding indexes or scaling hardware. Check: Inspect scans/seeks, key lookup counts, implicit conversions, estimated-versus-actual rows, missing-index recommendations and write amplification.

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 choice pertains to Query Store plan regressions and forced plans, not the needed response/evidence pair. Use: Review actual execution plans, predicate sargability, cardinality estimates and suitable index designs before adding indexes or scaling hardware. Check: Inspect scans/seeks, key lookup counts, implicit conversions, estimated-versus-actual rows, missing-index recommendations and write amplification.

Competing workloads respect their configured limits and critical requests retain service within documented platform and resource constraints. This choice pertains to Resource Governor and scoped compute configuration, not the needed response/evidence pair. Use: Review actual execution plans, predicate sargability, cardinality estimates and suitable index designs before adding indexes or scaling hardware. Check: Inspect scans/seeks, key lookup counts, implicit conversions, estimated-versus-actual rows, missing-index recommendations and write amplification.

Database files and supported backups remain encrypted with accessible protectors, and rotation or failover does not block required recovery operations. This choice pertains to Transparent data encryption keys and protector lifecycle, not the needed response/evidence pair. Use: Configure database auditing for activity accountability, select Change Tracking or Change Data Capture for supported data-change synchronization, and use ledger only when tamper-evidence requirements justify it. Check: Examine audit destinations, retention and access, captured event classes, Change Tracking version retention, CDC capture jobs, ledger digest verification and application expectations.

Classify sensitive columns, apply supported Dynamic Data Masking only for presentation control, and use encryption or RLS when stronger confidentiality is required. This choice pertains to Dynamic data masking classification and permission differences, not the needed response/evidence pair. Use: Configure database auditing for activity accountability, select Change Tracking or Change Data Capture for supported data-change synchronization, and use ledger only when tamper-evidence requirements justify it. Check: Examine audit destinations, retention and access, captured event classes, Change Tracking version retention, CDC capture jobs, ledger digest verification and application expectations.

Inspect tenant and server Entra administrator settings, token audience, user mapping, group membership, service principal, role grants and sign-in failures. This choice pertains to Microsoft Entra authentication with contained service identity, not the needed response/evidence pair. Use: Configure database auditing for activity accountability, select Change Tracking or Change Data Capture for supported data-change synchronization, and use ledger only when tamper-evidence requirements justify it. Check: Examine audit destinations, retention and access, captured event classes, Change Tracking version retention, CDC capture jobs, ledger digest verification and application expectations.

Use Az PowerShell or Azure CLI in authenticated deployment workflows with the minimum Azure RBAC rights and explicit resource/subscription selection to manage approved SQL resources. This addresses Azure PowerShell and CLI operations with scoped automation identity, not the controlling requirement here. Azure RBAC permissions to create an Azure SQL server do not imply arbitrary T-SQL data access to every user database. Prefer: Use ARM or Bicep to define Azure SQL servers, databases, identity, networking and policy settings in source-controlled templates with environment parameters and gated deployment checks.

Use Azure SQL elastic jobs for supported scheduled T-SQL maintenance across Azure SQL Database targets, managing target groups, credentials and job execution state. This addresses Azure SQL Database elastic jobs for fleet maintenance, not the controlling requirement here. Elastic jobs are a separate managed job-agent service and should not be confused with SQL Server Agent jobs inside Azure SQL Database. Prefer: Use ARM or Bicep to define Azure SQL servers, databases, identity, networking and policy settings in source-controlled templates with environment parameters and gated deployment checks.

Investigate SQL Agent job-step execution context, timing and dependencies before retrying, and make destructive maintenance operations safe for partial reruns. This addresses SQL Agent job troubleshooting and idempotent maintenance, not the controlling requirement here. Retrying a failed job without tracking committed work can create duplicate actions; application and SQL job state must be reconciled. Prefer: Use ARM or Bicep to define Azure SQL servers, databases, identity, networking and policy settings in source-controlled templates with environment parameters and gated deployment checks.

A real job failure triggers one useful notification to the right team and its history records sufficient context for a safe repair or retry. This would validate SQL Agent alerts operators and failure notifications, but it does not establish the required outcome here. Verify instead: Scheduled maintenance produces validated database results and on-call teams receive accurate failure notifications with safe recovery playbooks.

The automation updates only intended database resources and produces repeatable audit evidence of changes and failures without storing plaintext passwords. This would validate Azure PowerShell and CLI operations with scoped automation identity, but it does not establish the required outcome here. Verify instead: Scheduled maintenance produces validated database results and on-call teams receive accurate failure notifications with safe recovery playbooks.

The job runs on intended databases with controlled concurrency and job history that identifies any failed or skipped target for remediation. This would validate Azure SQL Database elastic jobs for fleet maintenance, but it does not establish the required outcome here. Verify instead: Scheduled maintenance produces validated database results and on-call teams receive accurate failure notifications with safe recovery playbooks.

Alerts fire for meaningful sustained database risk while log delivery and missing-metric gaps are independently observable. This would validate Azure Monitor alerts diagnostics and resource metrics, but it does not establish the required outcome here. Verify instead: The identified bottleneck has a specific measured cause, and the chosen corrective action changes the relevant metric under representative load.

The captured evidence explains the failing operation at the right time with sufficient context and acceptable overhead, without recording unrestricted sensitive payloads. This would validate Extended Events and workload-specific incident evidence, but it does not establish the required outcome here. Verify instead: The identified bottleneck has a specific measured cause, and the chosen corrective action changes the relevant metric under representative load.

Competing workloads respect their configured limits and critical requests retain service within documented platform and resource constraints. This would validate Resource Governor and scoped compute configuration, but it does not establish the required outcome here. Verify instead: The identified bottleneck has a specific measured cause, and the chosen corrective action changes the relevant metric under representative load.

Use Azure Arc-enabled SQL Server to inventory and govern supported SQL Server instances outside Azure without assuming Arc moves their databases or turns them into PaaS. This addresses Azure Arc-enabled SQL and hybrid fleet governance, not the controlling requirement here. Azure Arc projects management and governance into Azure; Arc onboarding is not equivalent to migration or replacing SQL Server backups and patching. Prefer: Choose a supported online migration path with ongoing data synchronization when a tight outage window requires it, and plan explicit final cutover, validation and rollback checkpoints.

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. This addresses Offline migration and post-migration verification, not the controlling requirement here. A BACPAC export captures schema and data for applicable databases but is not an instance backup that automatically recreates all server features and jobs. Prefer: Choose a supported online migration path with ongoing data synchronization when a tight outage window requires it, and plan explicit final cutover, validation and rollback checkpoints.

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: Choose a supported online migration path with ongoing data synchronization when a tight outage window requires it, and plan explicit final cutover, validation and rollback checkpoints.