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Inspect backup format, target offering limits, export size, authentication mapping, integrity checks, DBCC findings, workload baselines and cutover test results. These checks primarily test Offline migration and post-migration verification instead of the critical system behavior in this case. Examine: Collect source version, compatibility level, blockers, logins, SQL Agent jobs, linked servers, TDE key dependencies, storage size and application integration map.

Measure vCore pressure, memory grants, data and log latency, tempdb contention, IOPS ceilings, disk caching, VM SKU caps and scaling windows. These checks primarily test Managed Instance and SQL VM compute storage scaling instead of the critical system behavior in this case. Examine: Collect source version, compatibility level, blockers, logins, SQL Agent jobs, linked servers, TDE key dependencies, storage size and application integration map.

Inventory SQL Agent, cross-database dependencies, instance features, latency, licensing, OS access and application connection requirements before choosing a target. These checks primarily test Choosing Azure SQL Database versus Managed Instance versus SQL VM instead of the critical system behavior in this case. Examine: Collect source version, compatibility level, blockers, logins, SQL Agent jobs, linked servers, TDE key dependencies, storage size and application integration map.

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: The application reconnects through the intended endpoint after a tested supported failover, with documented possible data loss and read/write behavior.

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: The application reconnects through the intended endpoint after a tested supported failover, with documented possible data loss and read/write behavior.

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: The application reconnects through the intended endpoint after a tested supported failover, with documented possible data loss and read/write behavior.

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. This addresses Azure SQL automatic PITR and long-term retention, not the controlling requirement here. Point-in-time restore usually creates a separate database and does not undo production writes in place; retention is constrained by service-specific limits. Prefer: 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.

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: 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.

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 addresses SQL Server failover cluster instances shared storage constraints, not the controlling requirement here. An FCI moves SQL Server instance ownership over shared storage but does not automatically provide a separate cross-region copy of database files. Prefer: 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.

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: 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.

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: 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.

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: 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.

Inspect server-level and database-level firewall rules, private endpoint approval and DNS, VNet/subnet routing, public network access status and certificate validation. These checks primarily test Azure SQL private endpoints firewall and TLS boundary instead of the critical system behavior in this case. Examine: Review key hierarchy, certificate availability, encrypted payload format, authorized decryption path, T-SQL function usage, rotation and backup procedures.

Inspect login/user mapping, server principals, password policy, Entra admin configuration, directory identity, database containment and connection string authentication mode. These checks primarily test SQL authentication versus Entra and managed-instance principals instead of the critical system behavior in this case. Examine: Review key hierarchy, certificate availability, encrypted payload format, authorized decryption path, T-SQL function usage, rotation and backup procedures.

Inspect SESSION_CONTEXT usage, predicate function logic, policy state, object permissions, execution plans and cross-tenant test accounts. These checks primarily test Row-level security and ownership predicates instead of the critical system behavior in this case. Examine: Review key hierarchy, certificate availability, encrypted payload format, authorized decryption path, T-SQL function usage, rotation and backup procedures.

A representative mix of small and large parameter executions achieves stable resource use, with intelligent feature effects monitored over time. This would validate Intelligent Insights and parameter-sensitive query analysis, 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 identified bottleneck has a specific measured cause, and the chosen corrective action changes the relevant metric under representative load. This would validate SQL operational baseline across waits locks and storage, 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.

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

Inspect Windows Server failover cluster or supported Linux HA configuration, availability replica state, listener IP/DNS, synchronization health, AG endpoint port and failover readiness. These checks primarily test Always On availability groups on SQL Server VMs and SQL MI links instead of the critical system behavior in this case. Examine: Check service tier, available restore points, retention setting, logical server and database permissions, LTR vault policy and restore destination.

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: 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: Check service tier, available restore points, retention setting, logical server and database permissions, LTR vault policy and restore destination.

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 shared disk or supported file-share topology, Windows cluster validation, storage permissions, listener name, resource ownership and node failover tests.

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 shared disk or supported file-share topology, Windows cluster validation, storage permissions, listener name, resource ownership and node failover tests.

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 shared disk or supported file-share topology, Windows cluster validation, storage permissions, listener name, resource ownership and node failover tests.

Inspect automation account managed identity, runbook schedule, Azure Monitor action group, job output, retry policy, resource locks and target database state. These checks primarily test Azure database task automation alerts and retries instead of the critical system behavior in this case. Examine: Inspect elastic job agent setup, target server groups, database-scoped credentials, schedule, job version, execution history and permissions.

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 elastic job agent setup, target server groups, database-scoped credentials, schedule, job version, execution history and permissions.

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 elastic job agent setup, target server groups, database-scoped credentials, schedule, job version, execution history and permissions.

Distinguish authentication from authorization using SQL error context, Entra membership and database principal mapping before changing firewall or granting elevated roles. This choice pertains to Diagnosing login failure and group-based access, not the needed response/evidence pair. Use: 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. Check: Inspect login/user mapping, server principals, password policy, Entra admin configuration, directory identity, database containment and connection string authentication mode.

Inspect SESSION_CONTEXT usage, predicate function logic, policy state, object permissions, execution plans and cross-tenant test accounts. This choice pertains to Row-level security and ownership predicates, not the needed response/evidence pair. Use: 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. Check: Inspect login/user mapping, server principals, password policy, Entra admin configuration, directory identity, database containment and connection string authentication mode.

Only approved SQL principals or application clients decrypt the intended data and key rotation retains tested recovery capability. This choice pertains to Object-level encryption and database cryptographic controls, not the needed response/evidence pair. Use: 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. Check: Inspect login/user mapping, server principals, password policy, Entra admin configuration, directory identity, database containment and connection string authentication mode.

After a planned or forced failover the intended database endpoint serves valid writes and read-only workloads under documented consistency limits. This would validate Azure SQL Database active geo replication and failover groups, but it does not establish the required outcome here. Verify instead: The secondary replays the intended log sequence and can be recovered with documented RPO/RTO and acceptable data loss when primary fails.

Approved managed-instance failover or hybrid transition works after controlled traffic redirection, with required instance features and logins present. This would validate Managed Instance hybrid recovery and operational readiness, but it does not establish the required outcome here. Verify instead: The secondary replays the intended log sequence and can be recovered with documented RPO/RTO and acceptable data loss when primary fails.

The intended database replicas transition primary role as designed and application connections reach the listener without unsupported database or instance assumptions. This would validate Always On availability groups on SQL Server VMs and SQL MI links, but it does not establish the required outcome here. Verify instead: The secondary replays the intended log sequence and can be recovered with documented RPO/RTO and acceptable data loss when primary fails.