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Approved managed-instance failover or hybrid transition works after controlled traffic redirection, with required instance features and logins present. This choice pertains to Managed Instance hybrid recovery and operational readiness, not the needed response/evidence pair. Use: Plan full, differential and transaction-log backups using appropriate SQL Server recovery model and restore order for the intended point-in-time objective. Check: Inspect database recovery model, complete backup-chain LSNs, log backup cadence, backup checksums, database state and recovery target.

Inspect replication state, endpoint listeners, failover policy, allowed data loss, application reconnect errors, secondary region capacity and DNS cache behavior. This choice pertains to Azure SQL Database active geo replication and failover groups, not the needed response/evidence pair. Use: Plan full, differential and transaction-log backups using appropriate SQL Server recovery model and restore order for the intended point-in-time objective. Check: Inspect database recovery model, complete backup-chain LSNs, log backup cadence, backup checksums, database state and recovery target.

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: Plan full, differential and transaction-log backups using appropriate SQL Server recovery model and restore order for the intended point-in-time objective. Check: Inspect database recovery model, complete backup-chain LSNs, log backup cadence, backup checksums, database state and recovery target.

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 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.

Use Always Encrypted to protect selected columns with client-side cryptography and evaluate secure enclaves for supported confidential computations and richer query operations. This addresses Always Encrypted client-side protection and enclaves, not the controlling requirement here. Always Encrypted is distinct from TDE; queries and operations may be constrained without supported enclave capabilities and drivers. Prefer: 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.

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: 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.

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: The identified bottleneck has a specific measured cause, and the chosen corrective action changes the relevant metric under representative load.

Long blocking chains shorten and transaction correctness remains valid after safe tuning, with deadlock retry policy and consistency requirements addressed. This would validate Blocking deadlocks and isolation strategy, but it does not establish the required outcome here. Verify instead: The identified bottleneck has a specific measured cause, and the chosen corrective action changes the relevant metric under representative load.

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: The identified bottleneck has a specific measured cause, and the chosen corrective action changes the relevant metric under representative load.

Test availability and recovery plans with realistic but controlled primary outages, application write workload, backups and rollback exercises before claiming a recovery objective. This choice pertains to HA DR tabletop and destructive failure testing, not the needed response/evidence pair. Use: Select a supported HA and disaster recovery architecture from business-defined RPO, RTO, region failure assumptions, planned failover steps and service-specific capabilities. Check: Inspect recovery objectives, replication modes, failure domains, backup frequencies, availability SLA, network and DNS cutover plus application dependency map.

Inspect backup URL, SAS or managed identity support by SQL version, container permissions, encryption/certificate material, backup headers and RESTORE VERIFYONLY caveats. This choice pertains to Backup to Azure Blob URL and tested cloud restore, not the needed response/evidence pair. Use: Select a supported HA and disaster recovery architecture from business-defined RPO, RTO, region failure assumptions, planned failover steps and service-specific capabilities. Check: Inspect recovery objectives, replication modes, failure domains, backup frequencies, availability SLA, network and DNS cutover plus application dependency map.

A complete chain can be restored to the required point using valid full, differential and sequential log backups with proven integrity. This choice pertains to SQL Server native backup chain and recovery model, not the needed response/evidence pair. Use: Select a supported HA and disaster recovery architecture from business-defined RPO, RTO, region failure assumptions, planned failover steps and service-specific capabilities. Check: Inspect recovery objectives, replication modes, failure domains, backup frequencies, availability SLA, network and DNS cutover plus application dependency map.

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

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

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

The destination is consistent at an accepted cutover point, applications use the intended endpoint, and rollback criteria are documented before retirement of source. This would validate Online migration with controlled cutover and validation, but it does not establish the required outcome here. Verify instead: The migrated service opens with consistent data, working identities and restored application workflows within the agreed maintenance period.

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: The migrated service opens with consistent data, working identities and restored application workflows within the agreed maintenance period.

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: The migrated service opens with consistent data, working identities and restored application workflows within the agreed maintenance period.

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: Inspect predicate selectivity, partition elimination, split/merge plans, aligned indexes, compression CPU overhead and real data size reduction.

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: Inspect predicate selectivity, partition elimination, split/merge plans, aligned indexes, compression CPU overhead and real data size reduction.

Inspect CPU, data IO, log write, storage, concurrent sessions, DTU/vCore utilization, pool-level pressure and per-database limits. These checks primarily test Azure SQL Database service tiers and elastic pools instead of the critical system behavior in this case. Examine: Inspect predicate selectivity, partition elimination, split/merge plans, aligned indexes, compression CPU overhead and real data size reduction.

Inspect recovery objectives, replication modes, failure domains, backup frequencies, availability SLA, network and DNS cutover plus application dependency map. These checks primarily test RPO RTO strategy and availability versus recovery instead of the critical system behavior in this case. Examine: 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. These checks primarily test Azure SQL automatic PITR and long-term retention instead of the critical system behavior in this case. Examine: Check Managed Instance region pairing, VNet/DNS dependencies, SQL MI link prerequisites where used, migration and failover sequence, replication health and authentication continuity.

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: Check Managed Instance region pairing, VNet/DNS dependencies, SQL MI link prerequisites where used, migration and failover sequence, replication health and authentication continuity.

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 replication state, endpoint listeners, failover policy, allowed data loss, application reconnect errors, secondary region capacity and DNS cache behavior.

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 replication state, endpoint listeners, failover policy, allowed data loss, application reconnect errors, secondary region capacity and DNS cache behavior.

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 replication state, endpoint listeners, failover policy, allowed data loss, application reconnect errors, secondary region capacity and DNS cache behavior.

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: A problematic query recovers representative execution time without forcing a plan that fails under other parameter or schema conditions.

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.

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: A problematic query recovers representative execution time without forcing a plan that fails under other parameter or schema conditions.

Inspect scans/seeks, key lookup counts, implicit conversions, estimated-versus-actual rows, missing-index recommendations and write amplification. These checks primarily test Execution plans cardinality and indexing improvements instead of the critical system behavior in this case. Examine: Inspect diagnostic recommendations, Query Store plan variability, runtime skew, parameter compilation, memory grant feedback and database compatibility settings.

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 diagnostic recommendations, Query Store plan variability, runtime skew, parameter compilation, memory grant feedback and database compatibility settings.

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 diagnostic recommendations, Query Store plan variability, runtime skew, parameter compilation, memory grant feedback and database compatibility settings.