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Inspect installed Arc agent/extensions, SQL resource inventory, policy assignments, supported assessment features, connectivity and data residency needs. These checks primarily test Azure Arc-enabled SQL and hybrid fleet governance instead of the critical system behavior in this case. Examine: Inspect backup format, target offering limits, export size, authentication mapping, integrity checks, DBCC findings, workload baselines and cutover test results.

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 backup format, target offering limits, export size, authentication mapping, integrity checks, DBCC findings, workload baselines and cutover test results.

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 backup format, target offering limits, export size, authentication mapping, integrity checks, DBCC findings, workload baselines and cutover test results.

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 supported Microsoft Entra authentication and database users or contained identities for Azure SQL, ensuring the application principal receives only required permissions. Check: Inspect tenant and server Entra administrator settings, token audience, user mapping, group membership, service principal, role grants and sign-in failures.

Inspect login/user mapping, server principals, password policy, Entra admin configuration, directory identity, database containment and connection string authentication mode. This choice pertains to SQL authentication versus Entra and managed-instance principals, not the needed response/evidence pair. Use: Configure supported Microsoft Entra authentication and database users or contained identities for Azure SQL, ensuring the application principal receives only required permissions. Check: Inspect tenant and server Entra administrator settings, token audience, user mapping, group membership, service principal, role grants and sign-in failures.

Grant database and object rights to explicit roles, distinguish server-level from database permissions, and avoid applying sysadmin or db_owner as a workaround for every access error. This choice pertains to Least-privilege SQL roles and ownership chaining, not the needed response/evidence pair. Use: Configure supported Microsoft Entra authentication and database users or contained identities for Azure SQL, ensuring the application principal receives only required permissions. Check: Inspect tenant and server Entra administrator settings, token audience, user mapping, group membership, service principal, role grants and sign-in failures.

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 deployed database meets compatibility and service-management requirements without unnecessary virtual-machine maintenance or unsupported instance features.

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: The deployed database meets compatibility and service-management requirements without unnecessary virtual-machine maintenance or unsupported instance features.

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 deployed database meets compatibility and service-management requirements without unnecessary virtual-machine maintenance or unsupported instance features.

A failed deployment is diagnosed without deleting productive data, and the corrected infrastructure remains consistent with reviewed desired state. This would validate Deployment monitoring rollback and drift reconciliation, but it does not establish the required outcome here. Verify instead: The job runs on intended databases with controlled concurrency and job history that identifies any failed or skipped target for remediation.

The maintenance job executes on the approved cadence with least-privilege identity and traceable execution logs without depending on a personal admin login. This would validate SQL Server Agent schedules and job ownership, but it does not establish the required outcome here. Verify instead: The job runs on intended databases with controlled concurrency and job history that identifies any failed or skipped target for remediation.

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

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: Use supported Azure SQL automatic tuning or IQP features with monitoring and safety controls; verify supported recommendations and their observed effect before treating them as universal fixes.

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: Use supported Azure SQL automatic tuning or IQP features with monitoring and safety controls; verify supported recommendations and their observed effect before treating them as universal fixes.

Schedule integrity checks, index and statistics maintenance based on measured fragmentation, modification rates and SLA rather than indiscriminately rebuilding every object each night. This addresses Index and statistics maintenance with targeted cadence, not the controlling requirement here. Small index fragmentation percentages do not automatically justify full rebuild; large rebuilds consume log space and can block workloads. Prefer: Use supported Azure SQL automatic tuning or IQP features with monitoring and safety controls; verify supported recommendations and their observed effect before treating them as universal fixes.

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. This choice pertains to ARM and Bicep declarative Azure SQL provisioning, not the needed response/evidence pair. Use: 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. Check: Review subscription context, service principal or managed identity, Azure RBAC role, API response, database resource state and script error handling.

The repaired scheduled job completes reliably and re-executing a partially completed workflow does not double-post or delete unintended data. This choice pertains to SQL Agent job troubleshooting and idempotent maintenance, not the needed response/evidence pair. Use: 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. Check: Review subscription context, service principal or managed identity, Azure RBAC role, API response, database resource state and script error handling.

Inspect elastic job agent setup, target server groups, database-scoped credentials, schedule, job version, execution history and permissions. This choice pertains to Azure SQL Database elastic jobs for fleet maintenance, not the needed response/evidence pair. Use: 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. Check: Review subscription context, service principal or managed identity, Azure RBAC role, API response, database resource state and script error handling.

A restore to the required historical point completes into a supported database target and data plus dependent identities are validated. This would validate Azure SQL automatic PITR and long-term retention, but it does not establish the required outcome here. Verify instead: A complete chain can be restored to the required point using valid full, differential and sequential log backups with proven integrity.

A documented exercise demonstrates recovery within measured time and data-loss objectives and reveals unmet application dependencies before production emergencies. This would validate HA DR tabletop and destructive failure testing, but it does not establish the required outcome here. Verify instead: A complete chain can be restored to the required point using valid full, differential and sequential log backups with proven integrity.

Measured failover and restoration exercises meet agreed data loss and recovery time limits without confusing uptime redundancy with recoverability. This would validate RPO RTO strategy and availability versus recovery, but it does not establish the required outcome here. Verify instead: A complete chain can be restored to the required point using valid full, differential and sequential log backups with proven integrity.

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. This addresses Log shipping health and recovery orchestration, not the controlling requirement here. Log shipping is backup-copy-restore orchestration, not synchronous automatic database failover or a substitute for manual application cutover. Prefer: 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.

Plan full, differential and transaction-log backups using appropriate SQL Server recovery model and restore order for the intended point-in-time objective. This addresses SQL Server native backup chain and recovery model, not the controlling requirement here. A full backup without subsequent transaction-log backups cannot recover every later transaction; SIMPLE recovery changes log backup support. Prefer: 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.

Choose Azure SQL failover groups or active geo-replication according to group-level endpoint continuity, supported replication topology, read scale and application reconnect requirements. This addresses Azure SQL failover groups versus active geo replication decisions, not the controlling requirement here. Asynchronous cross-region replication may lose recent commits on forced failover; automatic failover behavior differs by service and configuration. Prefer: 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.

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: Measured failover and restoration exercises meet agreed data loss and recovery time limits without confusing uptime redundancy with recoverability.

A complete chain can be restored to the required point using valid full, differential and sequential log backups with proven integrity. This would validate SQL Server native backup chain and recovery model, but it does not establish the required outcome here. Verify instead: Measured failover and restoration exercises meet agreed data loss and recovery time limits without confusing uptime redundancy with recoverability.

A documented exercise demonstrates recovery within measured time and data-loss objectives and reveals unmet application dependencies before production emergencies. This would validate HA DR tabletop and destructive failure testing, but it does not establish the required outcome here. Verify instead: Measured failover and restoration exercises meet agreed data loss and recovery time limits without confusing uptime redundancy with recoverability.

Performance improvements persist under measured production workloads and failed recommendations are reversed or disabled according to policy. This would validate Automatic tuning and intelligent query processing guardrails, but it does not establish the required outcome here. Verify instead: A problematic query recovers representative execution time without forcing a plan that fails under other parameter or schema conditions.

Operators detect regressions against representative baseline periods and can link database symptoms to trustworthy collected performance evidence. This would validate Database watcher and Azure SQL monitoring baseline, but it does not establish the required outcome here. Verify instead: A problematic query recovers representative execution time without forcing a plan that fails under other parameter or schema conditions.

Queries use appropriate access paths under representative parameters while maintenance and write overhead remain acceptable. This would validate Execution plans cardinality and indexing improvements, but it does not establish the required outcome here. Verify instead: A problematic query recovers representative execution time without forcing a plan that fails under other parameter or schema conditions.

Configure SQL Server Agent notifications, operators and error handling so failed backups and maintenance tasks generate actionable alerts without leaking sensitive details. This choice pertains to SQL Agent alerts operators and failure notifications, not the needed response/evidence pair. Use: 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. Check: Inspect SQL Agent service state, job owner, proxy or credential, step subsystem, schedules, permissions, execution history and target database.

Inspect template parameters, deployment scope, what-if output, module dependencies, identity role assignments and post-deploy effective configuration. This choice pertains to ARM and Bicep declarative Azure SQL provisioning, not the needed response/evidence pair. Use: 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. Check: Inspect SQL Agent service state, job owner, proxy or credential, step subsystem, schedules, permissions, execution history and target database.

Scheduled maintenance produces validated database results and on-call teams receive accurate failure notifications with safe recovery playbooks. This choice pertains to Azure database task automation alerts and retries, not the needed response/evidence pair. Use: 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. Check: Inspect SQL Agent service state, job owner, proxy or credential, step subsystem, schedules, permissions, execution history and target database.