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Check automatic tuning mode, automatic plan correction state, index create/drop recommendations, plan verification, workload compatibility level and rollback events. These checks primarily test Automatic tuning and intelligent query processing guardrails 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 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 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.

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: 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. Check: Inspect TDE state, Azure Key Vault or Managed HSM key permissions, protector version, key availability, rotation policy and restore dependencies.

Check effective permission using EXECUTE AS, user/database role membership, ownership chain, DENY overrides, T-SQL GRANT statements and precise failed operation. This choice pertains to Least-privilege SQL roles and ownership chaining, not the needed response/evidence pair. Use: 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. Check: Inspect TDE state, Azure Key Vault or Managed HSM key permissions, protector version, key availability, rotation policy and restore dependencies.

A previously failing user connects with the correct principal and performs only approved operations after a narrowly scoped corrective change. This choice pertains to Diagnosing login failure and group-based access, not the needed response/evidence pair. Use: 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. Check: Inspect TDE state, Azure Key Vault or Managed HSM key permissions, protector version, key availability, rotation policy and restore dependencies.

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.

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.

Inspect step command, proxy token, connection defaults, deadlocks, Agent history output, last success timestamp and job rerun behavior. These checks primarily test SQL Agent job troubleshooting and idempotent maintenance 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 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 index page counts, fragmentation relevance, row modification counters, statistics age, update thresholds, DBCC CHECKDB results and blocking windows. These checks primarily test Index and statistics maintenance with targeted cadence 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.

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 metric namespace, resource dimensions, aggregation periods, diagnostic destinations, alert scope, delivery permissions, action groups and sample timestamps.

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 Resource Governor on supported SQL Server platforms for workload classification and resource controls, while choosing Azure SQL compute tier and database-scoped settings appropriately for PaaS.

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. This addresses Automatic tuning and intelligent query processing guardrails, not the controlling requirement here. Automatic tuning may need time to evaluate evidence and can reverse actions; feature availability is platform and compatibility-level dependent. Prefer: Use Resource Governor on supported SQL Server platforms for workload classification and resource controls, while choosing Azure SQL compute tier and database-scoped settings appropriately for PaaS.

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 Resource Governor on supported SQL Server platforms for workload classification and resource controls, while choosing Azure SQL compute tier and database-scoped settings appropriately for PaaS.

Back up supported SQL Server databases to Azure Blob storage through approved credential or managed identity patterns, then validate access, checksums and test restores from cloud targets. This choice pertains to Backup to Azure Blob URL and tested cloud restore, not the needed response/evidence pair. Use: Use Azure SQL automated backups and configured point-in-time retention or long-term retention policy for supported managed offerings, choosing the correct restore workflow and retention costs. Check: Check service tier, available restore points, retention setting, logical server and database permissions, LTR vault policy and restore destination.

Inspect database recovery model, complete backup-chain LSNs, log backup cadence, backup checksums, database state and recovery target. This choice pertains to SQL Server native backup chain and recovery model, not the needed response/evidence pair. Use: Use Azure SQL automated backups and configured point-in-time retention or long-term retention policy for supported managed offerings, choosing the correct restore workflow and retention costs. Check: Check service tier, available restore points, retention setting, logical server and database permissions, LTR vault policy and restore destination.

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: Use Azure SQL automated backups and configured point-in-time retention or long-term retention policy for supported managed offerings, choosing the correct restore workflow and retention costs. Check: Check service tier, available restore points, retention setting, logical server and database permissions, LTR vault policy and restore destination.

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 backup URL, SAS or managed identity support by SQL version, container permissions, encryption/certificate material, backup headers and RESTORE VERIFYONLY caveats.

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 backup URL, SAS or managed identity support by SQL version, container permissions, encryption/certificate material, backup headers and RESTORE VERIFYONLY caveats.

Inspect replication state, endpoint listeners, failover policy, allowed data loss, application reconnect errors, secondary region capacity and DNS cache behavior. These checks primarily test Azure SQL Database active geo replication and failover groups instead of the critical system behavior in this case. Examine: Inspect backup URL, SAS or managed identity support by SQL version, container permissions, encryption/certificate material, backup headers and RESTORE VERIFYONLY caveats.

Inspect shared disk or supported file-share topology, Windows cluster validation, storage permissions, listener name, resource ownership and node failover tests. These checks primarily test SQL Server failover cluster instances shared storage constraints instead of the critical system behavior in this case. Examine: Inspect Windows Server failover cluster or supported Linux HA configuration, availability replica state, listener IP/DNS, synchronization health, AG endpoint port and failover readiness.

Inspect monitor-server history, last backup/copied/restored times, log chain continuity, share access, standby mode and restore delay. These checks primarily test Log shipping health and recovery orchestration instead of the critical system behavior in this case. Examine: Inspect Windows Server failover cluster or supported Linux HA configuration, availability replica state, listener IP/DNS, synchronization health, AG endpoint port and failover readiness.

Inspect replica role, readable secondary capacity, asynchronous replication lag, failover-group listener endpoint, DNS TTL and connection retry handling. These checks primarily test Azure SQL failover groups versus active geo replication decisions instead of the critical system behavior in this case. Examine: Inspect Windows Server failover cluster or supported Linux HA configuration, availability replica state, listener IP/DNS, synchronization health, AG endpoint port and failover readiness.

Database files and supported backups remain encrypted with accessible protectors, and rotation or failover does not block required recovery operations. This would validate Transparent data encryption keys and protector lifecycle, but it does not establish the required outcome here. Verify instead: Low-trust users receive suitably masked results while sensitive storage and access controls still enforce separately tested privacy requirements.

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: Low-trust users receive suitably masked results while sensitive storage and access controls still enforce separately tested privacy requirements.

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: Low-trust users receive suitably masked results while sensitive storage and access controls still enforce separately tested privacy requirements.

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

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

The secondary replays the intended log sequence and can be recovered with documented RPO/RTO and acceptable data loss when primary fails. This would validate Log shipping health and recovery orchestration, but it does not establish the required outcome here. Verify instead: A recoverable backup is stored under controlled access and a real restore exercise proves the chain, keys and application consistency requirements.

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: Select Azure SQL Database for managed database-level PaaS needs, Azure SQL Managed Instance when near-instance compatibility is required, or SQL Server on Azure VMs for OS and instance control.

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. This addresses Azure SQL deployment automation and Fabric SQL integration boundary, not the controlling requirement here. Using Fabric with Azure SQL does not remove operational security responsibilities or grant unsupported cross-service transactional semantics. Prefer: Select Azure SQL Database for managed database-level PaaS needs, Azure SQL Managed Instance when near-instance compatibility is required, or SQL Server on Azure VMs for OS and instance control.

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: Select Azure SQL Database for managed database-level PaaS needs, Azure SQL Managed Instance when near-instance compatibility is required, or SQL Server on Azure VMs for OS and instance control.