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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: 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.

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. This choice pertains to Transparent data encryption keys and protector lifecycle, 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.

Investigators obtain the intended activity or row-change evidence, while tampering or synchronization gaps are detected by the correct feature-specific controls. This choice pertains to Azure SQL auditing ledger and change tracking distinctions, 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.

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: Operators detect regressions against representative baseline periods and can link database symptoms to trustworthy collected performance evidence.

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

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: Operators detect regressions against representative baseline periods and can link database symptoms to trustworthy collected performance evidence.

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: 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.

Classify sensitive columns, apply supported Dynamic Data Masking only for presentation control, and use encryption or RLS when stronger confidentiality is required. This addresses Dynamic data masking classification and permission differences, not the controlling requirement here. Dynamic Data Masking is not encryption or a complete defense against inference; administrators and UNMASK principals can still access original values. Prefer: 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.

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: 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.

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: 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.

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: 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.

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. This addresses Azure SQL auditing ledger and change tracking distinctions, not the controlling requirement here. SQL auditing, change tracking, CDC and ledger answer different questions; enabling one does not guarantee identical transaction history or immutable external evidence. Prefer: 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.

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: Queries and retention maintenance operate on intended partitions with predictable execution plans, storage growth and acceptable CPU overhead.

The chosen tier or pool absorbs expected peaks with measured response times while avoiding waste from persistently idle dedicated allocations. This would validate Azure SQL Database service tiers and elastic pools, but it does not establish the required outcome here. Verify instead: Queries and retention maintenance operate on intended partitions with predictable execution plans, storage growth and acceptable CPU overhead.

The migration plan explicitly maps each source feature to a supported destination behavior and documented remediation before cutover. This would validate Azure SQL migration assessment and feature compatibility, but it does not establish the required outcome here. Verify instead: Queries and retention maintenance operate on intended partitions with predictable execution plans, storage growth and acceptable CPU overhead.

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: 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.

Select a supported HA and disaster recovery architecture from business-defined RPO, RTO, region failure assumptions, planned failover steps and service-specific capabilities. This choice pertains to RPO RTO strategy and availability versus recovery, 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.

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: 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.

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: Diagnose blocked and deadlocked sessions using live DMVs and deadlock graphs, then fix transaction scope, indexing or isolation behavior with concurrency tests.

Review actual execution plans, predicate sargability, cardinality estimates and suitable index designs before adding indexes or scaling hardware. This addresses Execution plans cardinality and indexing improvements, not the controlling requirement here. A missing-index suggestion is a starting hypothesis, not a license to create every suggested index; SARGable predicates and accurate estimates matter. Prefer: Diagnose blocked and deadlocked sessions using live DMVs and deadlock graphs, then fix transaction scope, indexing or isolation behavior with concurrency tests.

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. This addresses Azure Monitor alerts diagnostics and resource metrics, not the controlling requirement here. A low CPU value does not mean an app is healthy; incorrect aggregation or missing telemetry can hide blocked sessions and failures. Prefer: Diagnose blocked and deadlocked sessions using live DMVs and deadlock graphs, then fix transaction scope, indexing or isolation behavior with concurrency tests.

Inspect CPU, data IO, log write, storage, concurrent sessions, DTU/vCore utilization, pool-level pressure and per-database limits. This choice pertains to Azure SQL Database service tiers and elastic pools, not the needed response/evidence pair. Use: Size Managed Instance and SQL Server VM compute, storage latency and throughput using performance evidence, including correct storage-layout and platform support limits. Check: Measure vCore pressure, memory grants, data and log latency, tempdb contention, IOPS ceilings, disk caching, VM SKU caps and scaling windows.

Implement supported partition functions and aligned partition schemes for lifecycle-aware large tables, and choose row, page or columnstore compression only after measuring query and maintenance effects. This choice pertains to Table partitioning compression and scale-out tradeoffs, not the needed response/evidence pair. Use: Size Managed Instance and SQL Server VM compute, storage latency and throughput using performance evidence, including correct storage-layout and platform support limits. Check: Measure vCore pressure, memory grants, data and log latency, tempdb contention, IOPS ceilings, disk caching, VM SKU caps and scaling windows.

New environment deployments match approved SKU, networking and identities while Fabric access follows supported synchronization and permission boundaries. This choice pertains to Azure SQL deployment automation and Fabric SQL integration boundary, not the needed response/evidence pair. Use: Size Managed Instance and SQL Server VM compute, storage latency and throughput using performance evidence, including correct storage-layout and platform support limits. Check: Measure vCore pressure, memory grants, data and log latency, tempdb contention, IOPS ceilings, disk caching, VM SKU caps and scaling windows.

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 replica role, readable secondary capacity, asynchronous replication lag, failover-group listener endpoint, DNS TTL and connection retry handling.

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 replica role, readable secondary capacity, asynchronous replication lag, failover-group listener endpoint, DNS TTL and connection retry handling.

Check service tier, available restore points, retention setting, logical server and database permissions, LTR vault policy and restore destination. These checks primarily test Azure SQL automatic PITR and long-term retention instead of the critical system behavior in this case. Examine: Inspect replica role, readable secondary capacity, asynchronous replication lag, failover-group listener endpoint, DNS TTL and connection retry handling.

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. This addresses Azure Monitor alerts diagnostics and resource metrics, not the controlling requirement here. A low CPU value does not mean an app is healthy; incorrect aggregation or missing telemetry can hide blocked sessions and failures. Prefer: Review actual execution plans, predicate sargability, cardinality estimates and suitable index designs before adding indexes or scaling hardware.

Distinguish compute, data IO, log IO, memory and blocking contention using correlated counters, wait types and workload-specific thresholds before changing resources. This addresses SQL operational baseline across waits locks and storage, not the controlling requirement here. One wait type alone is not a universal diagnosis; waits, plan behavior, request duration and resource data must be read together. Prefer: Review actual execution plans, predicate sargability, cardinality estimates and suitable index designs before adding indexes or scaling hardware.

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: Review actual execution plans, predicate sargability, cardinality estimates and suitable index designs before adding indexes or scaling hardware.

The migration plan explicitly maps each source feature to a supported destination behavior and documented remediation before cutover. This would validate Azure SQL migration assessment and feature compatibility, but it does not establish the required outcome here. Verify instead: Queries and retention maintenance operate on intended partitions with predictable execution plans, storage growth and acceptable CPU overhead.

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: Queries and retention maintenance operate on intended partitions with predictable execution plans, storage growth and acceptable CPU overhead.

The chosen tier or pool absorbs expected peaks with measured response times while avoiding waste from persistently idle dedicated allocations. This would validate Azure SQL Database service tiers and elastic pools, but it does not establish the required outcome here. Verify instead: Queries and retention maintenance operate on intended partitions with predictable execution plans, storage growth and acceptable CPU overhead.