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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.

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. This addresses Choosing Azure SQL Database versus Managed Instance versus SQL VM, not the controlling requirement here. A managed database offering does not necessarily expose every SQL Server instance feature; platform responsibility differs from SQL Server on a VM. Prefer: 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.

Choose database vCore or DTU purchasing models, compute tier and elastic-pool membership from measured resource patterns, isolation needs and predictable workload peaks. This addresses Azure SQL Database service tiers and elastic pools, not the controlling requirement here. Elastic pools share resources across eligible Azure SQL databases; adding a pool cannot eliminate an individual database's workload or resource configuration limits. Prefer: 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.

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: 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.

Inspect deployment operation results, resource provider error codes, policy denials, what-if diffs, resource locks, template validation and database post-deploy health. This choice pertains to Deployment monitoring rollback and drift reconciliation, not the needed response/evidence pair. Use: Use ARM or Bicep to define Azure SQL servers, databases, identity, networking and policy settings in source-controlled templates with environment parameters and gated deployment checks. Check: Inspect template parameters, deployment scope, what-if output, module dependencies, identity role assignments and post-deploy effective configuration.

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 choice pertains to Azure PowerShell and CLI operations with scoped automation identity, not the needed response/evidence pair. Use: Use ARM or Bicep to define Azure SQL servers, databases, identity, networking and policy settings in source-controlled templates with environment parameters and gated deployment checks. Check: Inspect template parameters, deployment scope, what-if output, module dependencies, identity role assignments and post-deploy effective configuration.

A real job failure triggers one useful notification to the right team and its history records sufficient context for a safe repair or retry. This choice pertains to SQL Agent alerts operators and failure notifications, not the needed response/evidence pair. Use: Use ARM or Bicep to define Azure SQL servers, databases, identity, networking and policy settings in source-controlled templates with environment parameters and gated deployment checks. Check: Inspect template parameters, deployment scope, what-if output, module dependencies, identity role assignments and post-deploy effective configuration.

Approved users can execute only intended tables, views and procedures, while unauthorized writes and administrative operations fail reproducibly. This would validate Least-privilege SQL roles and ownership chaining, but it does not establish the required outcome here. Verify instead: Authorized workloads resolve the intended endpoint and connect over the required private or permitted path while unauthorized public sources are blocked.

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: Authorized workloads resolve the intended endpoint and connect over the required private or permitted path while unauthorized public sources are blocked.

Each authorized tenant sees only its records through SQL and API queries, while unauthorized predicate bypass attempts return no rows. This would validate Row-level security and ownership predicates, but it does not establish the required outcome here. Verify instead: Authorized workloads resolve the intended endpoint and connect over the required private or permitted path while unauthorized public sources are blocked.

Administrators can view authorized hybrid SQL inventory and policy findings while database files remain in their existing managed locations. This choice pertains to Azure Arc-enabled SQL and hybrid fleet governance, not the needed response/evidence pair. Use: 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. Check: Inspect backup format, target offering limits, export size, authentication mapping, integrity checks, DBCC findings, workload baselines and cutover test results.

Use a current migration assessment to inventory database dependencies, unsupported features, downtime constraints and target platform compatibility before moving data. This choice pertains to Azure SQL migration assessment and feature compatibility, not the needed response/evidence pair. Use: 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. Check: Inspect backup format, target offering limits, export size, authentication mapping, integrity checks, DBCC findings, workload baselines and cutover test results.

Inspect migration replication health, source change rate, lag, database compatibility, authentication, connection-string cutover and residual transaction state. This choice pertains to Online migration with controlled cutover and validation, not the needed response/evidence pair. Use: 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. Check: Inspect backup format, target offering limits, export size, authentication mapping, integrity checks, DBCC findings, workload baselines and cutover test results.

Design Azure SQL firewall policies and Private Link or approved service endpoints at the required scope, enforcing TLS and minimizing public endpoint exposure. This addresses Azure SQL private endpoints firewall and TLS boundary, not the controlling requirement here. A Private Endpoint does not provide correct DNS records automatically in every custom network; name resolution and access policy require separate verification. Prefer: 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.

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: 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.

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: 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.

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: The chosen tier or pool absorbs expected peaks with measured response times while avoiding waste from persistently idle dedicated allocations.

After resizing or tuning storage, relevant workload bottlenecks improve without breaching instance compatibility, availability or maintenance requirements. This would validate Managed Instance and SQL VM compute storage scaling, but it does not establish the required outcome here. Verify instead: The chosen tier or pool absorbs expected peaks with measured response times while avoiding waste from persistently idle dedicated allocations.

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 chosen tier or pool absorbs expected peaks with measured response times while avoiding waste from persistently idle dedicated allocations.

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. This addresses Choosing Azure SQL Database versus Managed Instance versus SQL VM, not the controlling requirement here. A managed database offering does not necessarily expose every SQL Server instance feature; platform responsibility differs from SQL Server on a VM. Prefer: Choose database vCore or DTU purchasing models, compute tier and elastic-pool membership from measured resource patterns, isolation needs and predictable workload peaks.

Implement supported partition functions and aligned partition schemes for lifecycle-aware large tables, and choose row, page or columnstore compression only after measuring query and maintenance effects. This addresses Table partitioning compression and scale-out tradeoffs, not the controlling requirement here. Partitioning alone does not make every query faster; indexes and predicate alignment determine pruning and compression may trade CPU for IO. Prefer: Choose database vCore or DTU purchasing models, compute tier and elastic-pool membership from measured resource patterns, isolation needs and predictable workload peaks.

Size Managed Instance and SQL Server VM compute, storage latency and throughput using performance evidence, including correct storage-layout and platform support limits. This addresses Managed Instance and SQL VM compute storage scaling, not the controlling requirement here. Increasing CPU cannot fix a saturated log throughput budget or a storage path with high sustained write latency. Prefer: Choose database vCore or DTU purchasing models, compute tier and elastic-pool membership from measured resource patterns, isolation needs and predictable workload peaks.

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. This addresses Transparent data encryption keys and protector lifecycle, not the controlling requirement here. TDE encrypts storage at rest but does not hide column values from authorized SQL queries or replace end-to-end TLS. Prefer: Protect targeted sensitive objects through supported SQL encryption functions, key hierarchy and application threat model while distinguishing column encryption from network and storage encryption.

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: Protect targeted sensitive objects through supported SQL encryption functions, key hierarchy and application threat model while distinguishing column encryption from network and storage encryption.

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: Protect targeted sensitive objects through supported SQL encryption functions, key hierarchy and application threat model while distinguishing column encryption from network and storage encryption.

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

Authorized workloads resolve the intended endpoint and connect over the required private or permitted path while unauthorized public sources are blocked. This would validate Azure SQL private endpoints firewall and TLS boundary, but it does not establish the required outcome here. Verify instead: Clients establish the intended authentication method without insecure credential sharing, and failed sign-ins can be tied to the correct principal and database.

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: Clients establish the intended authentication method without insecure credential sharing, and failed sign-ins can be tied to the correct principal and database.

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: Inspect encrypted column metadata, column master and encryption keys, driver feature support, enclave attestation where applicable and key store permissions.

Check effective permission using EXECUTE AS, user/database role membership, ownership chain, DENY overrides, T-SQL GRANT statements and precise failed operation. These checks primarily test Least-privilege SQL roles and ownership chaining instead of the critical system behavior in this case. Examine: Inspect encrypted column metadata, column master and encryption keys, driver feature support, enclave attestation where applicable and key store permissions.

Review sign-in error number and state, selected database, Entra token principal, group claims, CREATE USER scope, role membership and firewall reachability. These checks primarily test Diagnosing login failure and group-based access instead of the critical system behavior in this case. Examine: Inspect encrypted column metadata, column master and encryption keys, driver feature support, enclave attestation where applicable and key store permissions.