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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: Competing workloads respect their configured limits and critical requests retain service within documented platform and resource constraints.

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: Competing workloads respect their configured limits and critical requests retain service within documented platform and resource constraints.

The identified bottleneck has a specific measured cause, and the chosen corrective action changes the relevant metric under representative load. This would validate SQL operational baseline across waits locks and storage, but it does not establish the required outcome here. Verify instead: Competing workloads respect their configured limits and critical requests retain service within documented platform and resource constraints.

Examine failover runbook owner, replica health, DNS and application retry time, last confirmed transaction, validation queries and restore evidence. These checks primarily test HA DR tabletop and destructive failure testing instead of the critical system behavior in this case. Examine: Inspect monitor-server history, last backup/copied/restored times, log chain continuity, share access, standby mode and restore delay.

Inspect backup URL, SAS or managed identity support by SQL version, container permissions, encryption/certificate material, backup headers and RESTORE VERIFYONLY caveats. These checks primarily test Backup to Azure Blob URL and tested cloud restore instead of the critical system behavior in this case. Examine: Inspect monitor-server history, last backup/copied/restored times, log chain continuity, share access, standby mode and restore delay.

Inspect Windows Server failover cluster or supported Linux HA configuration, availability replica state, listener IP/DNS, synchronization health, AG endpoint port and failover readiness. These checks primarily test Always On availability groups on SQL Server VMs and SQL MI links instead of the critical system behavior in this case. Examine: Inspect monitor-server history, last backup/copied/restored times, log chain continuity, share access, standby mode and restore delay.

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: Test availability and recovery plans with realistic but controlled primary outages, application write workload, backups and rollback exercises before claiming a recovery objective. Check: Examine failover runbook owner, replica health, DNS and application retry time, last confirmed transaction, validation queries and restore evidence.

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: Test availability and recovery plans with realistic but controlled primary outages, application write workload, backups and rollback exercises before claiming a recovery objective. Check: Examine failover runbook owner, replica health, DNS and application retry time, last confirmed transaction, validation queries and restore evidence.

A restore to the required historical point completes into a supported database target and data plus dependent identities are validated. This choice pertains to Azure SQL automatic PITR and long-term retention, not the needed response/evidence pair. Use: Test availability and recovery plans with realistic but controlled primary outages, application write workload, backups and rollback exercises before claiming a recovery objective. Check: Examine failover runbook owner, replica health, DNS and application retry time, last confirmed transaction, validation queries and restore evidence.

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 Query Store capture mode, runtime statistics, plan IDs, compatibility level, force-plan failure reasons and workload parameter distributions.

Review database watcher configuration and targets, query and instance samples, CPU, data/log IO, wait statistics, alert scope and time-series retention. These checks primarily test Database watcher and Azure SQL monitoring baseline instead of the critical system behavior in this case. Examine: Inspect Query Store capture mode, runtime statistics, plan IDs, compatibility level, force-plan failure reasons and workload parameter distributions.

Inspect metric namespace, resource dimensions, aggregation periods, diagnostic destinations, alert scope, delivery permissions, action groups and sample timestamps. These checks primarily test Azure Monitor alerts diagnostics and resource metrics instead of the critical system behavior in this case. Examine: Inspect Query Store capture mode, runtime statistics, plan IDs, compatibility level, force-plan failure reasons and workload parameter distributions.

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 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: 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 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: 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: Inventory SQL Agent, cross-database dependencies, instance features, latency, licensing, OS access and application connection requirements before choosing a target.

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: Inventory SQL Agent, cross-database dependencies, instance features, latency, licensing, OS access and application connection requirements before choosing a target.

Inspect login/user mapping, server principals, password policy, Entra admin configuration, directory identity, database containment and connection string authentication mode. These checks primarily test SQL authentication versus Entra and managed-instance principals instead of the critical system behavior in this case. Examine: Check effective permission using EXECUTE AS, user/database role membership, ownership chain, DENY overrides, T-SQL GRANT statements and precise failed operation.

Review key hierarchy, certificate availability, encrypted payload format, authorized decryption path, T-SQL function usage, rotation and backup procedures. These checks primarily test Object-level encryption and database cryptographic controls instead of the critical system behavior in this case. Examine: Check effective permission using EXECUTE AS, user/database role membership, ownership chain, DENY overrides, T-SQL GRANT statements and precise failed operation.

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

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: Check automatic tuning mode, automatic plan correction state, index create/drop recommendations, plan verification, workload compatibility level and rollback events.

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: Check automatic tuning mode, automatic plan correction state, index create/drop recommendations, plan verification, workload compatibility level and rollback events.

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: Check automatic tuning mode, automatic plan correction state, index create/drop recommendations, plan verification, workload compatibility level and rollback events.

Inspect database recovery model, complete backup-chain LSNs, log backup cadence, backup checksums, database state and recovery target. These checks primarily test SQL Server native backup chain and recovery model instead of the critical system behavior in this case. Examine: Inspect shared disk or supported file-share topology, Windows cluster validation, storage permissions, listener name, resource ownership and node failover tests.

Inspect monitor-server history, last backup/copied/restored times, log chain continuity, share access, standby mode and restore delay. These checks primarily test Log shipping health and recovery orchestration instead of the critical system behavior in this case. Examine: Inspect shared disk or supported file-share topology, Windows cluster validation, storage permissions, listener name, resource ownership and node failover tests.

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: Inspect shared disk or supported file-share topology, Windows cluster validation, storage permissions, listener name, resource ownership and node failover tests.

The SQL Server instance restarts on an eligible node using accessible shared data and log storage while the application resolves the cluster virtual network name. This would validate SQL Server failover cluster instances shared storage constraints, but it does not establish the required outcome here. Verify instead: After a planned or forced failover the intended database endpoint serves valid writes and read-only workloads under documented consistency limits.

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: After a planned or forced failover the intended database endpoint serves valid writes and read-only workloads under documented consistency limits.

A restore to the required historical point completes into a supported database target and data plus dependent identities are validated. This would validate Azure SQL automatic PITR and long-term retention, but it does not establish the required outcome here. Verify instead: After a planned or forced failover the intended database endpoint serves valid writes and read-only workloads under documented consistency limits.

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.

Choose a supported online migration path with ongoing data synchronization when a tight outage window requires it, and plan explicit final cutover, validation and rollback checkpoints. This addresses Online migration with controlled cutover and validation, not the controlling requirement here. Online migration reduces downtime but is not automatically zero-downtime; final synchronization, traffic redirection and application tests still matter. Prefer: Choose database vCore or DTU purchasing models, compute tier and elastic-pool membership from measured resource patterns, isolation needs and predictable workload peaks.

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 addresses Azure SQL deployment automation and Fabric SQL integration boundary, not the controlling requirement here. Using Fabric with Azure SQL does not remove operational security responsibilities or grant unsupported cross-service transactional semantics. Prefer: Choose database vCore or DTU purchasing models, compute tier and elastic-pool membership from measured resource patterns, isolation needs and predictable workload peaks.