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Low-trust users receive suitably masked results while sensitive storage and access controls still enforce separately tested privacy requirements. This would validate Dynamic data masking classification and permission differences, but it does not establish the required outcome here. Verify instead: Approved users can execute only intended tables, views and procedures, while unauthorized writes and administrative operations fail reproducibly.

Clients establish the intended authentication method without insecure credential sharing, and failed sign-ins can be tied to the correct principal and database. This would validate SQL authentication versus Entra and managed-instance principals, but it does not establish the required outcome here. Verify instead: Approved users can execute only intended tables, views and procedures, while unauthorized writes and administrative operations fail reproducibly.

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: Approved users can execute only intended tables, views and procedures, while unauthorized writes and administrative operations fail reproducibly.

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 addresses SQL Server Agent schedules and job ownership, not the controlling requirement here. SQL Server Agent is supported on relevant instance-level offerings but is not the native scheduling mechanism inside a standalone Azure SQL Database. Prefer: Configure SQL Server Agent notifications, operators and error handling so failed backups and maintenance tasks generate actionable alerts without leaking sensitive details.

Investigate SQL Agent job-step execution context, timing and dependencies before retrying, and make destructive maintenance operations safe for partial reruns. This addresses SQL Agent job troubleshooting and idempotent maintenance, not the controlling requirement here. Retrying a failed job without tracking committed work can create duplicate actions; application and SQL job state must be reconciled. Prefer: Configure SQL Server Agent notifications, operators and error handling so failed backups and maintenance tasks generate actionable alerts without leaking sensitive details.

Use Az PowerShell or Azure CLI in authenticated deployment workflows with the minimum Azure RBAC rights and explicit resource/subscription selection to manage approved SQL resources. This addresses Azure PowerShell and CLI operations with scoped automation identity, not the controlling requirement here. Azure RBAC permissions to create an Azure SQL server do not imply arbitrary T-SQL data access to every user database. Prefer: Configure SQL Server Agent notifications, operators and error handling so failed backups and maintenance tasks generate actionable alerts without leaking sensitive details.

After resizing or tuning storage, relevant workload bottlenecks improve without breaching instance compatibility, availability or maintenance requirements. This choice pertains to Managed Instance and SQL VM compute storage scaling, not the needed response/evidence pair. Use: 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. Check: Inventory SQL Agent, cross-database dependencies, instance features, latency, licensing, OS access and application connection requirements before choosing a target.

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 choice pertains to Azure SQL deployment automation and Fabric SQL integration boundary, not the needed response/evidence pair. Use: 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. Check: Inventory SQL Agent, cross-database dependencies, instance features, latency, licensing, OS access and application connection requirements before choosing a target.

Inspect installed Arc agent/extensions, SQL resource inventory, policy assignments, supported assessment features, connectivity and data residency needs. This choice pertains to Azure Arc-enabled SQL and hybrid fleet governance, not the needed response/evidence pair. Use: 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. Check: Inventory SQL Agent, cross-database dependencies, instance features, latency, licensing, OS access and application connection requirements before choosing a target.

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 choice pertains to Least-privilege SQL roles and ownership chaining, 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.

Authorized workloads resolve the intended endpoint and connect over the required private or permitted path while unauthorized public sources are blocked. This choice pertains to Azure SQL private endpoints firewall and TLS boundary, 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.

Examine audit destinations, retention and access, captured event classes, Change Tracking version retention, CDC capture jobs, ledger digest verification and application expectations. This choice pertains to Azure SQL auditing ledger and change tracking distinctions, 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.

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: 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.

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: 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.

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 automation account managed identity, runbook schedule, Azure Monitor action group, job output, retry policy, resource locks and target database state.

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

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 automation account managed identity, runbook schedule, Azure Monitor action group, job output, retry policy, resource locks and target database state.

A recoverable backup is stored under controlled access and a real restore exercise proves the chain, keys and application consistency requirements. This would validate Backup to Azure Blob URL and tested cloud restore, but it does not establish the required outcome here. Verify instead: Approved managed-instance failover or hybrid transition works after controlled traffic redirection, with required instance features and logins present.

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: Approved managed-instance failover or hybrid transition works after controlled traffic redirection, with required instance features and logins present.

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: Approved managed-instance failover or hybrid transition works after controlled traffic redirection, with required instance features and logins present.

Inspect TDE state, Azure Key Vault or Managed HSM key permissions, protector version, key availability, rotation policy and restore dependencies. These checks primarily test Transparent data encryption keys and protector lifecycle 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 sensitivity labels, masking expressions, UNMASK permissions, privileged role membership and direct query behavior across application identities. These checks primarily test Dynamic data masking classification and permission differences 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.

Examine audit destinations, retention and access, captured event classes, Change Tracking version retention, CDC capture jobs, ledger digest verification and application expectations. These checks primarily test Azure SQL auditing ledger and change tracking distinctions 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.

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: Approved applications can query protected columns with authorized client drivers while other SQL readers cannot obtain original plaintext directly.

Only approved SQL principals or application clients decrypt the intended data and key rotation retains tested recovery capability. This would validate Object-level encryption and database cryptographic controls, but it does not establish the required outcome here. Verify instead: Approved applications can query protected columns with authorized client drivers while other SQL readers cannot obtain original plaintext directly.

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: Approved applications can query protected columns with authorized client drivers while other SQL readers cannot obtain original plaintext directly.

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 choice pertains to Azure SQL auditing ledger and change tracking distinctions, not the needed response/evidence pair. Use: Implement Row-Level Security with a carefully tested predicate function and security policy for each tenant or business boundary, independent of form-level filtering. Check: Inspect SESSION_CONTEXT usage, predicate function logic, policy state, object permissions, execution plans and cross-tenant test accounts.

Authorized workloads resolve the intended endpoint and connect over the required private or permitted path while unauthorized public sources are blocked. This choice pertains to Azure SQL private endpoints firewall and TLS boundary, not the needed response/evidence pair. Use: Implement Row-Level Security with a carefully tested predicate function and security policy for each tenant or business boundary, independent of form-level filtering. Check: Inspect SESSION_CONTEXT usage, predicate function logic, policy state, object permissions, execution plans and cross-tenant test accounts.

Review sign-in error number and state, selected database, Entra token principal, group claims, CREATE USER scope, role membership and firewall reachability. This choice pertains to Diagnosing login failure and group-based access, not the needed response/evidence pair. Use: Implement Row-Level Security with a carefully tested predicate function and security policy for each tenant or business boundary, independent of form-level filtering. Check: Inspect SESSION_CONTEXT usage, predicate function logic, policy state, object permissions, execution plans and cross-tenant test accounts.

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.