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Alerts fire for meaningful sustained database risk while log delivery and missing-metric gaps are independently observable. This choice pertains to Azure Monitor alerts diagnostics and resource metrics, not the needed response/evidence pair. Use: Correlate Azure SQL Intelligent Insights or Query Store evidence with parameter sensitivity and memory grant patterns, selecting documented plan or query changes instead of blindly upgrading SKU. Check: Inspect diagnostic recommendations, Query Store plan variability, runtime skew, parameter compilation, memory grant feedback and database compatibility settings.

Use Query Store to compare query runtime and plan history, identify a genuine plan regression, and force a known suitable plan only with ongoing validation and rollback. This choice pertains to Query Store plan regressions and forced plans, not the needed response/evidence pair. Use: Correlate Azure SQL Intelligent Insights or Query Store evidence with parameter sensitivity and memory grant patterns, selecting documented plan or query changes instead of blindly upgrading SKU. Check: Inspect diagnostic recommendations, Query Store plan variability, runtime skew, parameter compilation, memory grant feedback and database compatibility settings.

Inspect supported platform, classifier function, workload groups, CPU and memory caps, connection routing, database-scoped settings and compute metrics. This choice pertains to Resource Governor and scoped compute configuration, not the needed response/evidence pair. Use: Correlate Azure SQL Intelligent Insights or Query Store evidence with parameter sensitivity and memory grant patterns, selecting documented plan or query changes instead of blindly upgrading SKU. Check: Inspect diagnostic recommendations, Query Store plan variability, runtime skew, parameter compilation, memory grant feedback and database compatibility settings.

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 captured evidence explains the failing operation at the right time with sufficient context and acceptable overhead, without recording unrestricted sensitive payloads.

Access paths and estimates remain healthy with acceptable maintenance duration, transaction log growth and production concurrency. This would validate Index and statistics maintenance with targeted cadence, but it does not establish the required outcome here. Verify instead: The captured evidence explains the failing operation at the right time with sufficient context and acceptable overhead, without recording unrestricted sensitive payloads.

A problematic query recovers representative execution time without forcing a plan that fails under other parameter or schema conditions. This would validate Query Store plan regressions and forced plans, but it does not establish the required outcome here. Verify instead: The captured evidence explains the failing operation at the right time with sufficient context and acceptable overhead, without recording unrestricted sensitive payloads.

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: Examine audit destinations, retention and access, captured event classes, Change Tracking version retention, CDC capture jobs, ledger digest verification and application expectations.

Inspect encrypted column metadata, column master and encryption keys, driver feature support, enclave attestation where applicable and key store permissions. These checks primarily test Always Encrypted client-side protection and enclaves instead of the critical system behavior in this case. Examine: Examine audit destinations, retention and access, captured event classes, Change Tracking version retention, CDC capture jobs, ledger digest verification and application expectations.

Inspect tenant and server Entra administrator settings, token audience, user mapping, group membership, service principal, role grants and sign-in failures. These checks primarily test Microsoft Entra authentication with contained service identity instead of the critical system behavior in this case. Examine: Examine audit destinations, retention and access, captured event classes, Change Tracking version retention, CDC capture jobs, ledger digest verification and application expectations.

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 template parameters, deployment scope, what-if output, module dependencies, identity role assignments and post-deploy effective configuration.

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 template parameters, deployment scope, what-if output, module dependencies, identity role assignments and post-deploy effective configuration.

Review subscription context, service principal or managed identity, Azure RBAC role, API response, database resource state and script error handling. These checks primarily test Azure PowerShell and CLI operations with scoped automation identity instead of the critical system behavior in this case. Examine: Inspect template parameters, deployment scope, what-if output, module dependencies, identity role assignments and post-deploy effective configuration.

Inspect login/user mapping, server principals, password policy, Entra admin configuration, directory identity, database containment and connection string authentication mode. This choice pertains to SQL authentication versus Entra and managed-instance principals, not the needed response/evidence pair. Use: 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. Check: Check effective permission using EXECUTE AS, user/database role membership, ownership chain, DENY overrides, T-SQL GRANT statements and precise failed operation.

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: 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. Check: Check effective permission using EXECUTE AS, user/database role membership, ownership chain, DENY overrides, T-SQL GRANT statements and precise failed operation.

Low-trust users receive suitably masked results while sensitive storage and access controls still enforce separately tested privacy requirements. This choice pertains to Dynamic data masking classification and permission differences, not the needed response/evidence pair. Use: 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. Check: Check effective permission using EXECUTE AS, user/database role membership, ownership chain, DENY overrides, T-SQL GRANT statements and precise failed operation.

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. This addresses ARM and Bicep declarative Azure SQL provisioning, not the controlling requirement here. A valid ARM deployment may still produce unsafe security settings if templates use broad defaults or incorrect resource group/subscription targets. Prefer: Monitor Azure resource deployments and resolve failed dependencies or policy denials using logs and change review, with safe rollback plans for data-bearing SQL resources.

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: Monitor Azure resource deployments and resolve failed dependencies or policy denials using logs and change review, with safe rollback plans for data-bearing SQL resources.

Configure SQL Server Agent notifications, operators and error handling so failed backups and maintenance tasks generate actionable alerts without leaking sensitive details. This addresses SQL Agent alerts operators and failure notifications, not the controlling requirement here. A green schedule and enabled operator are not evidence that email delivery or failure handling works unless the notification path is tested. Prefer: Monitor Azure resource deployments and resolve failed dependencies or policy denials using logs and change review, with safe rollback plans for data-bearing SQL resources.

Inspect replica role, readable secondary capacity, asynchronous replication lag, failover-group listener endpoint, DNS TTL and connection retry handling. This choice pertains to Azure SQL failover groups versus active geo replication decisions, not the needed response/evidence pair. Use: 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. Check: Inspect shared disk or supported file-share topology, Windows cluster validation, storage permissions, listener name, resource ownership and node failover tests.

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. This choice pertains to Always On availability groups on SQL Server VMs and SQL MI links, not the needed response/evidence pair. Use: 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. Check: Inspect shared disk or supported file-share topology, Windows cluster validation, storage permissions, listener name, resource ownership and node failover tests.

A documented exercise demonstrates recovery within measured time and data-loss objectives and reveals unmet application dependencies before production emergencies. This choice pertains to HA DR tabletop and destructive failure testing, not the needed response/evidence pair. Use: 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. Check: Inspect shared disk or supported file-share topology, Windows cluster validation, storage permissions, listener name, resource ownership and node failover tests.

Inspect backup format, target offering limits, export size, authentication mapping, integrity checks, DBCC findings, workload baselines and cutover test results. This choice pertains to Offline migration and post-migration verification, 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.

Use Azure Arc-enabled SQL Server to inventory and govern supported SQL Server instances outside Azure without assuming Arc moves their databases or turns them into PaaS. 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.

The destination is consistent at an accepted cutover point, applications use the intended endpoint, and rollback criteria are documented before retirement of source. This choice pertains to Online migration with controlled cutover and validation, 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. These checks primarily test Azure Arc-enabled SQL and hybrid fleet governance instead of the critical system behavior in this case. Examine: Compare database offering capabilities, deployment parameters, identity, networking, Fabric integration support, source control and tenant governance before provisioning.

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: Compare database offering capabilities, deployment parameters, identity, networking, Fabric integration support, source control and tenant governance before provisioning.

Inspect predicate selectivity, partition elimination, split/merge plans, aligned indexes, compression CPU overhead and real data size reduction. These checks primarily test Table partitioning compression and scale-out tradeoffs instead of the critical system behavior in this case. Examine: Compare database offering capabilities, deployment parameters, identity, networking, Fabric integration support, source control and tenant governance before provisioning.

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.

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

Approved applications can query protected columns with authorized client drivers while other SQL readers cannot obtain original plaintext directly. This would validate Always Encrypted client-side protection and enclaves, 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 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: Automate supported Azure SQL operational tasks with an appropriately scoped schedule or runbook and route failures into measurable alert channels while handling retries idempotently. Check: Inspect automation account managed identity, runbook schedule, Azure Monitor action group, job output, retry policy, resource locks and target database state.

The automation updates only intended database resources and produces repeatable audit evidence of changes and failures without storing plaintext passwords. This choice pertains to Azure PowerShell and CLI operations with scoped automation identity, not the needed response/evidence pair. Use: Automate supported Azure SQL operational tasks with an appropriately scoped schedule or runbook and route failures into measurable alert channels while handling retries idempotently. Check: Inspect automation account managed identity, runbook schedule, Azure Monitor action group, job output, retry policy, resource locks and target database state.

Use Azure SQL elastic jobs for supported scheduled T-SQL maintenance across Azure SQL Database targets, managing target groups, credentials and job execution state. This choice pertains to Azure SQL Database elastic jobs for fleet maintenance, not the needed response/evidence pair. Use: Automate supported Azure SQL operational tasks with an appropriately scoped schedule or runbook and route failures into measurable alert channels while handling retries idempotently. Check: Inspect automation account managed identity, runbook schedule, Azure Monitor action group, job output, retry policy, resource locks and target database state.