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Build and monitor supported SQL Server Always On availability groups on Azure VMs and understand SQL MI link behavior, verifying cluster quorum, replica health, endpoint access and synchronization mode. This addresses Always On availability groups on SQL Server VMs and SQL MI links, not the controlling requirement here. An AG protects replicated user databases and requires cluster/listener configuration; it does not automatically synchronize every SQL Agent job or server-level login. 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.

Select a supported HA and disaster recovery architecture from business-defined RPO, RTO, region failure assumptions, planned failover steps and service-specific capabilities. This addresses RPO RTO strategy and availability versus recovery, not the controlling requirement here. High availability reduces some outages but cannot substitute for recoverable backups after corruption or human deletion; RPO and RTO are separate targets. 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.

Configure supported active geo-replication or Azure SQL failover groups with clear primary-secondary roles, read-only routing, connection listeners and manual/automatic recovery procedures. This addresses Azure SQL Database active geo replication and failover groups, not the controlling requirement here. Geo-replication is normally asynchronous and does not guarantee all uncommitted or recently committed data survives a forced regional failover. 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.

Implement Row-Level Security with a carefully tested predicate function and security policy for each tenant or business boundary, independent of form-level filtering. This addresses Row-level security and ownership predicates, not the controlling requirement here. Client-side WHERE filters are not a database security boundary, and incorrectly scoped predicates can leak cross-tenant data. Prefer: Configure supported Microsoft Entra authentication and database users or contained identities for Azure SQL, ensuring the application principal receives only required permissions.

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 addresses Least-privilege SQL roles and ownership chaining, not the controlling requirement here. GRANT on one schema or stored procedure does not automatically confer arbitrary permissions on all underlying cross-database resources. Prefer: Configure supported Microsoft Entra authentication and database users or contained identities for Azure SQL, ensuring the application principal receives only required permissions.

Distinguish authentication from authorization using SQL error context, Entra membership and database principal mapping before changing firewall or granting elevated roles. This addresses Diagnosing login failure and group-based access, not the controlling requirement here. Network allow rules cannot repair a database permission denial, and a valid directory group may still lack an associated database user. Prefer: Configure supported Microsoft Entra authentication and database users or contained identities for Azure SQL, ensuring the application principal receives only required permissions.

Inspect backup URL, SAS or managed identity support by SQL version, container permissions, encryption/certificate material, backup headers and RESTORE VERIFYONLY caveats. These checks primarily test Backup to Azure Blob URL and tested cloud restore instead of the critical system behavior in this case. Examine: Inspect database recovery model, complete backup-chain LSNs, log backup cadence, backup checksums, database state and recovery target.

Examine failover runbook owner, replica health, DNS and application retry time, last confirmed transaction, validation queries and restore evidence. These checks primarily test HA DR tabletop and destructive failure testing instead of the critical system behavior in this case. Examine: Inspect database recovery model, complete backup-chain LSNs, log backup cadence, backup checksums, database state and recovery target.

Check Managed Instance region pairing, VNet/DNS dependencies, SQL MI link prerequisites where used, migration and failover sequence, replication health and authentication continuity. These checks primarily test Managed Instance hybrid recovery and operational readiness instead of the critical system behavior in this case. Examine: Inspect database recovery model, complete backup-chain LSNs, log backup cadence, backup checksums, database state and recovery target.

Examine failover runbook owner, replica health, DNS and application retry time, last confirmed transaction, validation queries and restore evidence. This choice pertains to HA DR tabletop and destructive failure testing, not the needed response/evidence pair. Use: Assess Managed Instance service tiers, built-in availability, failover groups and supported SQL Managed Instance link scenarios for hybrid resilience without inventing unsupported topologies. Check: Check Managed Instance region pairing, VNet/DNS dependencies, SQL MI link prerequisites where used, migration and failover sequence, replication health and authentication continuity.

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 choice pertains to Azure SQL failover groups versus active geo replication decisions, not the needed response/evidence pair. Use: Assess Managed Instance service tiers, built-in availability, failover groups and supported SQL Managed Instance link scenarios for hybrid resilience without inventing unsupported topologies. Check: Check Managed Instance region pairing, VNet/DNS dependencies, SQL MI link prerequisites where used, migration and failover sequence, replication health and authentication continuity.

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 choice pertains to SQL Server failover cluster instances shared storage constraints, not the needed response/evidence pair. Use: Assess Managed Instance service tiers, built-in availability, failover groups and supported SQL Managed Instance link scenarios for hybrid resilience without inventing unsupported topologies. Check: Check Managed Instance region pairing, VNet/DNS dependencies, SQL MI link prerequisites where used, migration and failover sequence, replication health and authentication continuity.

Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention. This choice pertains to Database watcher and Azure SQL monitoring baseline, not the needed response/evidence pair. Use: Correlate Azure SQL Intelligent Insights or Query Store evidence with parameter sensitivity and memory grant patterns, selecting documented plan or query changes instead of blindly upgrading SKU. Check: Inspect diagnostic recommendations, Query Store plan variability, runtime skew, parameter compilation, memory grant feedback and database compatibility settings.

Alerts fire for meaningful sustained database risk while log delivery and missing-metric gaps are independently observable. This choice pertains to Azure Monitor alerts diagnostics and resource metrics, not the needed response/evidence pair. Use: Correlate Azure SQL Intelligent Insights or Query Store evidence with parameter sensitivity and memory grant patterns, selecting documented plan or query changes instead of blindly upgrading SKU. Check: Inspect diagnostic recommendations, Query Store plan variability, runtime skew, parameter compilation, memory grant feedback and database compatibility settings.

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: Correlate Azure SQL Intelligent Insights or Query Store evidence with parameter sensitivity and memory grant patterns, selecting documented plan or query changes instead of blindly upgrading SKU. Check: Inspect diagnostic recommendations, Query Store plan variability, runtime skew, parameter compilation, memory grant feedback and database compatibility settings.

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: Compare CPU versus runnable tasks, WRITELOG, PAGEIOLATCH, resource governance, connection counts, tempdb usage, storage latency and times of workload change.

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: Compare CPU versus runnable tasks, WRITELOG, PAGEIOLATCH, resource governance, connection counts, tempdb usage, storage latency and times of workload change.

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: Compare CPU versus runnable tasks, WRITELOG, PAGEIOLATCH, resource governance, connection counts, tempdb usage, storage latency and times of workload change.

Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention. These checks primarily test Database watcher and Azure SQL monitoring baseline instead of the critical system behavior in this case. Examine: Inspect event session predicates, event fields, ring buffer or event file targets, dropped events, blocked process reports and collection overhead.

Inspect supported platform, classifier function, workload groups, CPU and memory caps, connection routing, database-scoped settings and compute metrics. These checks primarily test Resource Governor and scoped compute configuration instead of the critical system behavior in this case. Examine: Inspect event session predicates, event fields, ring buffer or event file targets, dropped events, blocked process reports and collection overhead.

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: Inspect event session predicates, event fields, ring buffer or event file targets, dropped events, blocked process reports and collection overhead.

Inspect SQL Agent service state, job owner, proxy or credential, step subsystem, schedules, permissions, execution history and target database. These checks primarily test SQL Server Agent schedules and job ownership instead of the critical system behavior in this case. Examine: Inspect deployment operation results, resource provider error codes, policy denials, what-if diffs, resource locks, template validation and database post-deploy health.

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 deployment operation results, resource provider error codes, policy denials, what-if diffs, resource locks, template validation and database post-deploy health.

Review subscription context, service principal or managed identity, Azure RBAC role, API response, database resource state and script error handling. These checks primarily test Azure PowerShell and CLI operations with scoped automation identity instead of the critical system behavior in this case. Examine: Inspect deployment operation results, resource provider error codes, policy denials, what-if diffs, resource locks, template validation and database post-deploy health.

Investigators obtain the intended activity or row-change evidence, while tampering or synchronization gaps are detected by the correct feature-specific controls. This would validate Azure SQL auditing ledger and change tracking distinctions, but it does not establish the required outcome here. Verify instead: A previously failing user connects with the correct principal and performs only approved operations after a narrowly scoped corrective change.

Clients establish the intended authentication method without insecure credential sharing, and failed sign-ins can be tied to the correct principal and database. This would validate SQL authentication versus Entra and managed-instance principals, but it does not establish the required outcome here. Verify instead: A previously failing user connects with the correct principal and performs only approved operations after a narrowly scoped corrective change.

The intended app authenticates through the managed identity or Entra principal without shared SQL passwords and can perform only its permitted queries. This would validate Microsoft Entra authentication with contained service identity, but it does not establish the required outcome here. Verify instead: A previously failing user connects with the correct principal and performs only approved operations after a narrowly scoped corrective change.

The application reconnects through the intended endpoint after a tested supported failover, with documented possible data loss and read/write behavior. This choice pertains to Azure SQL failover groups versus active geo replication decisions, not the needed response/evidence pair. Use: Configure supported active geo-replication or Azure SQL failover groups with clear primary-secondary roles, read-only routing, connection listeners and manual/automatic recovery procedures. Check: Inspect replication state, endpoint listeners, failover policy, allowed data loss, application reconnect errors, secondary region capacity and DNS cache behavior.

Check service tier, available restore points, retention setting, logical server and database permissions, LTR vault policy and restore destination. This choice pertains to Azure SQL automatic PITR and long-term retention, not the needed response/evidence pair. Use: Configure supported active geo-replication or Azure SQL failover groups with clear primary-secondary roles, read-only routing, connection listeners and manual/automatic recovery procedures. Check: Inspect replication state, endpoint listeners, failover policy, allowed data loss, application reconnect errors, secondary region capacity and DNS cache behavior.

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 supported active geo-replication or Azure SQL failover groups with clear primary-secondary roles, read-only routing, connection listeners and manual/automatic recovery procedures. Check: Inspect replication state, endpoint listeners, failover policy, allowed data loss, application reconnect errors, secondary region capacity and DNS cache behavior.

The chosen tier or pool absorbs expected peaks with measured response times while avoiding waste from persistently idle dedicated allocations. This choice pertains to Azure SQL Database service tiers and elastic pools, not the needed response/evidence pair. Use: Deploy governed Azure SQL resources with repeatable infrastructure templates and evaluate Azure SQL Database in Fabric for supported analytics-connected workflows rather than assuming all workloads are equivalent. Check: Compare database offering capabilities, deployment parameters, identity, networking, Fabric integration support, source control and tenant governance before provisioning.

Inspect backup format, target offering limits, export size, authentication mapping, integrity checks, DBCC findings, workload baselines and cutover test results. This choice pertains to Offline migration and post-migration verification, not the needed response/evidence pair. Use: Deploy governed Azure SQL resources with repeatable infrastructure templates and evaluate Azure SQL Database in Fabric for supported analytics-connected workflows rather than assuming all workloads are equivalent. Check: Compare database offering capabilities, deployment parameters, identity, networking, Fabric integration support, source control and tenant governance before provisioning.

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 choice pertains to Azure Arc-enabled SQL and hybrid fleet governance, not the needed response/evidence pair. Use: Deploy governed Azure SQL resources with repeatable infrastructure templates and evaluate Azure SQL Database in Fabric for supported analytics-connected workflows rather than assuming all workloads are equivalent. Check: Compare database offering capabilities, deployment parameters, identity, networking, Fabric integration support, source control and tenant governance before provisioning.