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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.

Compare database offering capabilities, deployment parameters, identity, networking, Fabric integration support, source control and tenant governance before provisioning. These checks primarily test Azure SQL deployment automation and Fabric SQL integration boundary 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.

Inspect migration replication health, source change rate, lag, database compatibility, authentication, connection-string cutover and residual transaction state. These checks primarily test Online migration with controlled cutover and validation 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.

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: Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention.

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: Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention.

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: Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention.

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: Implement Row-Level Security with a carefully tested predicate function and security policy for each tenant or business boundary, independent of form-level filtering.

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: Implement Row-Level Security with a carefully tested predicate function and security policy for each tenant or business boundary, independent of form-level filtering.

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: Implement Row-Level Security with a carefully tested predicate function and security policy for each tenant or business boundary, independent of form-level filtering.

Inspect step command, proxy token, connection defaults, deadlocks, Agent history output, last success timestamp and job rerun behavior. This choice pertains to SQL Agent job troubleshooting and idempotent maintenance, not the needed response/evidence pair. Use: Configure SQL Server Agent notifications, operators and error handling so failed backups and maintenance tasks generate actionable alerts without leaking sensitive details. Check: Inspect job history return status, Database Mail profile, operator assignment, alert severity, retry steps, failure branching and delivery errors.

Scheduled maintenance produces validated database results and on-call teams receive accurate failure notifications with safe recovery playbooks. This choice pertains to Azure database task automation alerts and retries, not the needed response/evidence pair. Use: Configure SQL Server Agent notifications, operators and error handling so failed backups and maintenance tasks generate actionable alerts without leaking sensitive details. Check: Inspect job history return status, Database Mail profile, operator assignment, alert severity, retry steps, failure branching and delivery errors.

Configure SQL Server Agent schedules and job-step security on supported SQL Server or Managed Instance platforms, separating service credentials from the database data permissions they need. This choice pertains to SQL Server Agent schedules and job ownership, not the needed response/evidence pair. Use: Configure SQL Server Agent notifications, operators and error handling so failed backups and maintenance tasks generate actionable alerts without leaking sensitive details. Check: Inspect job history return status, Database Mail profile, operator assignment, alert severity, retry steps, failure branching and delivery errors.

Queries and retention maintenance operate on intended partitions with predictable execution plans, storage growth and acceptable CPU overhead. This would validate Table partitioning compression and scale-out tradeoffs, but it does not establish the required outcome here. Verify instead: New environment deployments match approved SKU, networking and identities while Fabric access follows supported synchronization and permission boundaries.

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: New environment deployments match approved SKU, networking and identities while Fabric access follows supported synchronization and permission boundaries.

The deployed database meets compatibility and service-management requirements without unnecessary virtual-machine maintenance or unsupported instance features. This would validate Choosing Azure SQL Database versus Managed Instance versus SQL VM, but it does not establish the required outcome here. Verify instead: New environment deployments match approved SKU, networking and identities while Fabric access follows supported synchronization and permission boundaries.

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 job history return status, Database Mail profile, operator assignment, alert severity, retry steps, failure branching and delivery errors.

Inspect deployment operation results, resource provider error codes, policy denials, what-if diffs, resource locks, template validation and database post-deploy health. These checks primarily test Deployment monitoring rollback and drift reconciliation instead of the critical system behavior in this case. Examine: Inspect job history return status, Database Mail profile, operator assignment, alert severity, retry steps, failure branching and delivery errors.

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 job history return status, Database Mail profile, operator assignment, alert severity, retry steps, failure branching and delivery errors.

Inspect blocker/waiter SPIDs, wait_resource, open transactions, deadlock XML, isolation level, lock escalation and transaction duration. These checks primarily test Blocking deadlocks and isolation strategy instead of the critical system behavior in this case. Examine: Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention.

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: Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention.

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: Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention.

Plan full, differential and transaction-log backups using appropriate SQL Server recovery model and restore order for the intended point-in-time objective. This choice pertains to SQL Server native backup chain and recovery model, not the needed response/evidence pair. Use: 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. Check: Inspect backup URL, SAS or managed identity support by SQL version, container permissions, encryption/certificate material, backup headers and RESTORE VERIFYONLY caveats.

Check Managed Instance region pairing, VNet/DNS dependencies, SQL MI link prerequisites where used, migration and failover sequence, replication health and authentication continuity. This choice pertains to Managed Instance hybrid recovery and operational readiness, not the needed response/evidence pair. Use: 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. Check: Inspect backup URL, SAS or managed identity support by SQL version, container permissions, encryption/certificate material, backup headers and RESTORE VERIFYONLY caveats.

The intended database replicas transition primary role as designed and application connections reach the listener without unsupported database or instance assumptions. This choice pertains to Always On availability groups on SQL Server VMs and SQL MI links, not the needed response/evidence pair. Use: 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. Check: Inspect backup URL, SAS or managed identity support by SQL version, container permissions, encryption/certificate material, backup headers and RESTORE VERIFYONLY caveats.

Inspect job history return status, Database Mail profile, operator assignment, alert severity, retry steps, failure branching and delivery errors. These checks primarily test SQL Agent alerts operators and failure notifications instead of the critical system behavior in this case. Examine: Inspect step command, proxy token, connection defaults, deadlocks, Agent history output, last success timestamp and job rerun behavior.

Inspect deployment operation results, resource provider error codes, policy denials, what-if diffs, resource locks, template validation and database post-deploy health. These checks primarily test Deployment monitoring rollback and drift reconciliation instead of the critical system behavior in this case. Examine: Inspect step command, proxy token, connection defaults, deadlocks, Agent history output, last success timestamp and job rerun behavior.

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 step command, proxy token, connection defaults, deadlocks, Agent history output, last success timestamp and job rerun behavior.

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: Inspect installed Arc agent/extensions, SQL resource inventory, policy assignments, supported assessment features, connectivity and data residency needs.

Inspect migration replication health, source change rate, lag, database compatibility, authentication, connection-string cutover and residual transaction state. These checks primarily test Online migration with controlled cutover and validation instead of the critical system behavior in this case. Examine: Inspect installed Arc agent/extensions, SQL resource inventory, policy assignments, supported assessment features, connectivity and data residency needs.

Compare database offering capabilities, deployment parameters, identity, networking, Fabric integration support, source control and tenant governance before provisioning. These checks primarily test Azure SQL deployment automation and Fabric SQL integration boundary instead of the critical system behavior in this case. Examine: Inspect installed Arc agent/extensions, SQL resource inventory, policy assignments, supported assessment features, connectivity and data residency needs.

Check Managed Instance region pairing, VNet/DNS dependencies, SQL MI link prerequisites where used, migration and failover sequence, replication health and authentication continuity. This choice pertains to Managed Instance hybrid recovery and operational readiness, 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.

After a planned or forced failover the intended database endpoint serves valid writes and read-only workloads under documented consistency limits. This choice pertains to Azure SQL Database active geo replication and failover groups, 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.

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: 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.