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Question 81:
What is the primary purpose of implementing Azure SQL Database automatic tuning?
A) To manually optimize queries without recommendations
B) To automatically identify and fix performance issues using AI-driven recommendations
C) To increase database storage capacity automatically
D) To disable all indexes permanently
Answer: B
Explanation:
Azure SQL Database automatic tuning uses artificial intelligence and machine learning to continuously monitor database performance, identify optimization opportunities, and automatically implement performance improvements like creating missing indexes, dropping unused indexes, and forcing optimal query plans. This feature reduces administrative overhead by automatically addressing common performance issues without requiring manual intervention from database administrators.
Option A is incorrect because automatic tuning specifically provides automated optimization rather than manual processes. The feature analyzes query performance patterns and execution statistics to generate recommendations that can be automatically applied, eliminating the need for constant manual query tuning efforts.
Option C is incorrect because automatic tuning focuses on query performance optimization through execution plans and indexing rather than managing storage capacity. Storage expansion is handled through service tier adjustments or elastic pool configurations, which are separate from automatic tuning functionality.
Option D is incorrect because automatic tuning intelligently manages indexes by creating beneficial indexes and removing unused ones rather than disabling all indexes permanently. Indexes are critical for query performance, and automatic tuning optimizes index strategies to improve performance while minimizing maintenance overhead.
Automatic tuning provides three main options including create index recommendations that add missing indexes improving query performance, drop index recommendations removing duplicate or unused indexes reducing maintenance overhead, and force last good plan that identifies queries with execution plan regressions and forces previously optimal plans. Administrators can enable automatic tuning at the database level with options to automatically implement recommendations or review them before manual application. The feature continuously learns from workload patterns and validates that applied changes actually improve performance, automatically reverting changes that degrade performance. Automatic tuning integrates with Query Performance Insight providing visibility into performance trends and tuning actions taken.
Question 82:
Which Azure SQL Database feature provides point-in-time restore capabilities?
A) Automatic backups
B) Manual snapshots only
C) No backup capabilities available
D) Third-party backup tools exclusively
Answer: A
Explanation:
Automatic backups in Azure SQL Database provide comprehensive backup capabilities including full backups, differential backups, and transaction log backups that enable point-in-time restore to any moment within the configured retention period. These automated backups require no configuration or management, are stored in geo-redundant storage by default, and enable recovery from data corruption, accidental deletion, or other data loss scenarios.
Option B is incorrect because Azure SQL Database provides automatic continuous backups rather than requiring manual snapshot creation. While administrators can create copy-only backups for specific purposes, the automatic backup system continuously protects databases without manual intervention or scheduling requirements.
Option C is incorrect because Azure SQL Database includes comprehensive built-in backup capabilities as a core platform feature. Automatic backups are enabled by default for all databases providing protection without additional configuration, ensuring data protection is always available regardless of service tier.
Option D is incorrect because Azure SQL Database provides native backup capabilities through the platform rather than requiring third-party backup tools. While third-party solutions can provide additional backup features or hybrid scenarios, Azure’s built-in backup system provides complete protection for most requirements.
Full backups occur weekly, differential backups occur every 12 to 24 hours, and transaction log backups occur every 5 to 10 minutes ensuring minimal data loss potential. Retention periods range from 7 days for Basic tier to 35 days for other tiers with options for long-term retention up to 10 years for compliance requirements. Point-in-time restore can recover databases to any second within the retention period, creating new databases from backup without affecting source databases. Geo-restore capabilities enable recovery to different Azure regions from geo-replicated backups providing disaster recovery protection. Administrators should regularly test restore procedures, understand retention policies for their service tiers, and configure long-term retention for compliance requirements.
Question 83:
What is the function of Azure SQL Database elastic pools?
A) To increase CPU speed of individual databases
B) To share resources among multiple databases optimizing costs and performance
C) To disable database connectivity completely
D) To provide physical server access
Answer: B
Explanation:
Azure SQL Database elastic pools enable multiple databases to share a set of compute and storage resources including eDTUs or vCores, optimizing costs when databases have varying usage patterns and unpredictable workloads. Elastic pools allow individual databases to scale automatically within pool limits, ensuring adequate resources during peak usage while maintaining cost efficiency by sharing capacity among databases that peak at different times.
Option A is incorrect because elastic pools share resources among databases rather than increasing CPU speed of individual databases. While databases in pools can utilize available pool resources during demand spikes, the pools optimize resource sharing and cost rather than enhancing raw processing power.
Option C is incorrect because elastic pools enhance database availability and resource management rather than disabling connectivity. Databases in elastic pools remain fully accessible and operational, with the pool providing flexible resource allocation among member databases.
Option D is incorrect because Azure SQL Database including elastic pools is a platform as a service offering that abstracts physical server infrastructure. Administrators manage logical databases and resource allocation rather than accessing or managing underlying physical servers.
Elastic pools are ideal for SaaS applications with multiple tenant databases, development and test environments with numerous databases, or any scenario with multiple databases having complementary usage patterns. Pool sizing considers aggregate resource requirements with databases sharing eDTUs or vCores. Individual databases can burst to higher resource levels when needed while remaining within pool limits. Cost benefits occur because pool pricing is typically lower than equivalent separate databases, and resources are efficiently utilized across databases with different peak times. Administrators should monitor pool utilization ensuring adequate resources, consider database usage patterns when designing pools, and adjust pool size as workloads change. Azure provides recommendations for pool sizing based on historical database usage patterns.
Question 84:
Which Azure SQL security feature encrypts data at rest automatically?
A) Transparent Data Encryption (TDE)
B) Network Security Groups only
C) Application-level encryption exclusively
D) No encryption available
Answer: A
Explanation:
Transparent Data Encryption automatically encrypts Azure SQL Database data files at rest including database files, log files, and backup files using AES-256 encryption without requiring application changes or affecting performance significantly. TDE protects data if physical media is stolen or improperly disposed of, ensuring that database files cannot be read without proper decryption keys.
Option B is incorrect because Network Security Groups control network traffic flow and access rather than encrypting data at rest. NSGs provide network-level security by restricting which IP addresses can connect to databases but do not encrypt stored data files.
Option C is incorrect because while application-level encryption adds additional security layers, TDE provides database-level encryption at rest as a built-in platform feature. Application encryption requires code changes and key management within applications, whereas TDE operates transparently without application modifications.
Option D is incorrect because Azure SQL Database includes robust encryption capabilities as standard features. TDE is enabled by default for all newly created databases providing automatic protection, and Always Encrypted protects sensitive data in use and in transit.
TDE uses a database encryption key protected by a service-managed certificate or customer-managed key stored in Azure Key Vault for additional control. Encryption and decryption occur transparently at the page level as data is written to and read from disk, requiring no changes to applications, queries, or connection strings. TDE is enabled by default for new databases but can be verified and managed through Azure Portal or T-SQL commands. For regulatory compliance requiring customer-managed keys, organizations can use Bring Your Own Key capabilities integrating with Azure Key Vault. TDE complements other security features including Always Encrypted for column-level encryption, Transport Layer Security for data in transit, and Azure SQL Database firewall rules and virtual network service endpoints for network security.
Question 85:
What is the purpose of Azure SQL Database read replicas?
A) To provide read-only copies for offloading read workloads and improving performance
B) To disable write operations permanently
C) To delete data automatically
D) To prevent all database access
Answer: A
Explanation:
Azure SQL Database read replicas provide asynchronously replicated read-only database copies that offload read-intensive workloads from primary databases, improve application performance by distributing queries geographically closer to users, and enable reporting or analytics without impacting production workloads. Read replicas continuously synchronize with primary databases ensuring data consistency while allowing read operations to scale independently.
Option B is incorrect because read replicas provide read-only access to database copies rather than disabling write operations on primary databases. The primary database continues accepting read and write operations normally while replicas handle read-only queries, distributing workload across multiple database instances.
Option C is incorrect because read replicas provide additional copies of data for read access rather than deleting data. Replicas synchronize with primary databases maintaining current data copies, and changes on primary databases propagate to replicas ensuring consistency across instances.
Option D is incorrect because read replicas enhance database access by providing additional read endpoints rather than preventing access. Applications can connect to replicas for read operations while primary databases handle write operations, improving overall application scalability and user experience.
Read replicas are available through Active Geo-Replication supporting up to four readable secondary replicas in any Azure region, or through read scale-out in Premium and Business Critical tiers providing built-in read-only replicas within the same region. Use cases include offloading reporting queries, providing low-latency read access to geographically distributed users, and enabling business continuity through multiple database copies. Applications specify read-only intent in connection strings directing read queries to replicas while write operations go to primary databases. Administrators should monitor replication lag ensuring replicas remain sufficiently current for application requirements, consider network latency when placing geo-replicas, and understand that replicas use additional resources affecting costs.
Question 86:
Which Azure SQL Database pricing model charges based on actual compute usage per second?
A) DTU-based model only
B) Serverless compute tier
C) Fixed monthly pricing exclusively
D) No usage-based pricing available
Answer: B
Explanation:
Serverless compute tier provides automatic scaling and per-second billing based on actual compute usage, making it cost-effective for databases with intermittent, unpredictable workloads or development and test environments. Serverless automatically pauses databases during inactive periods charging only for storage, and resumes automatically when activity resumes, eliminating costs for unused compute capacity.
Option A is incorrect because DTU-based models charge fixed prices for provisioned capacity regardless of actual usage. While DTU models provide predictable pricing, they do not offer per-second usage-based billing that adjusts costs based on actual compute consumption patterns.
Option C is incorrect because serverless specifically provides variable usage-based pricing rather than fixed monthly costs. Fixed pricing models charge consistent amounts regardless of utilization, while serverless adjusts charges based on actual compute seconds used and auto-pause periods.
Option D is incorrect because Azure SQL Database offers multiple pricing models including usage-based serverless compute tier. Usage-based pricing provides cost optimization for variable workloads where fixed capacity provisioning would result in paying for unused resources.
Serverless is available in the General Purpose tier using vCore purchasing model with configurable minimum and maximum vCore limits defining scaling boundaries. Databases automatically scale between these limits based on workload demands with billing reflecting actual vCore usage per second. Auto-pause delay configures how long databases must be inactive before automatically pausing with delays ranging from 1 hour to 7 days or disabled for always-on behavior. During paused periods, only storage is charged significantly reducing costs. When connections arrive at paused databases, automatic resume occurs typically within one minute. Serverless is ideal for development and test databases, infrequently used applications, databases with unpredictable usage patterns, and scenarios where cost optimization for idle periods is important. Administrators should configure appropriate min and max vCore settings and auto-pause delays based on application requirements and cost optimization goals.
Question 87:
What is the function of Azure SQL Database Query Performance Insight?
A) To delete poorly performing queries automatically
B) To provide visualization and analysis of query performance and resource consumption
C) To disable query execution completely
D) To increase database storage limits
Answer: B
Explanation:
Query Performance Insight provides visual analysis of database query performance showing top resource-consuming queries, execution statistics, query duration trends, and performance patterns over time through intuitive dashboards. This tool helps identify problematic queries causing performance issues, understand resource consumption patterns, and prioritize optimization efforts based on actual impact on database performance.
Option A is incorrect because Query Performance Insight identifies and analyzes poorly performing queries rather than deleting them. The tool provides information enabling administrators to optimize or rewrite problematic queries, but does not automatically modify or remove queries from applications.
Option C is incorrect because Query Performance Insight analyzes query execution patterns rather than disabling queries. The tool helps optimize query performance by providing visibility into execution characteristics, enabling informed decisions about indexing, query rewriting, or configuration changes.
Option D is incorrect because Query Performance Insight focuses on query performance analysis rather than managing database storage. Storage capacity is adjusted through service tier changes or elastic pool configurations, which are separate from query performance monitoring and optimization.
Query Performance Insight displays top CPU-consuming, IO-consuming, and longest-running queries with detailed metrics including execution count, average duration, CPU time, logical reads, and physical reads. Time range selection enables viewing recent performance or historical trends identifying when performance degradation occurred. Clicking individual queries provides detailed execution statistics, query text, and execution plans. The tool integrates with automatic tuning recommendations suggesting index creations or query plan optimizations. Administrators should regularly review top resource-consuming queries, correlate performance issues with specific queries, and use insights to drive optimization efforts. Query Performance Insight works with Query Store which must be enabled to collect performance data, and is available for single databases and elastic pools providing performance visibility without additional configuration or overhead.
Question 88:
Which Azure SQL feature provides always-on, built-in high availability?
A) Manual failover clusters only
B) Availability Groups built into the service
C) No high availability capabilities
D) Third-party clustering exclusively
Answer: B
Explanation:
Azure SQL Database includes built-in high availability through availability groups that automatically maintain multiple replicas of databases, providing automatic failover if primary replicas fail without requiring manual intervention or additional configuration. This architecture ensures database availability targets of 99.99 percent or higher depending on service tier, with transparent failover handling hardware failures, software updates, or scaling operations.
Option A is incorrect because Azure SQL Database provides automatic built-in high availability rather than requiring manual failover cluster configuration. The platform automatically manages replica placement, synchronization, and failover processes transparently to applications without administrator intervention.
Option C is incorrect because high availability is a core feature of Azure SQL Database included in all service tiers. The platform architecture inherently provides redundancy and automatic failover ensuring database availability even during infrastructure failures or maintenance operations.
Option D is incorrect because Azure SQL Database includes native high availability capabilities within the service rather than requiring third-party clustering solutions. The platform provides availability groups as part of the managed service eliminating the need for external high availability technologies.
Basic, Standard, and General Purpose tiers use remote storage architecture with compute and storage separation, maintaining three data replicas with automatic failover to standby compute nodes during failures. Premium and Business Critical tiers use local storage architecture similar to Always On Availability Groups with multiple replicas on different nodes providing faster failover and higher availability. Business Critical tier includes a built-in read-only replica for offloading read workloads. Zone-redundant configurations distribute replicas across availability zones protecting against datacenter failures. During failover events, connection strings remain unchanged with brief connection interruptions typically under 30 seconds. Applications should implement retry logic to handle transient connection failures during failover. High availability is automatic requiring no configuration, but administrators should understand service tier availability characteristics when selecting appropriate tiers for applications.
Question 89:
What is the purpose of Azure SQL Database Intelligent Insights?
A) To manually analyze performance logs
B) To automatically detect and diagnose database performance issues using AI
C) To disable performance monitoring completely
D) To provide physical server access
Answer: B
Explanation:
Intelligent Insights uses artificial intelligence to continuously analyze database telemetry automatically detecting performance degradation, identifying root causes, and providing actionable recommendations for resolution without requiring manual log analysis or performance troubleshooting. This built-in intelligence monitors patterns like increased query duration, excessive waits, or resource bottlenecks, generating diagnostic logs with detailed analysis of detected issues.
Option A is incorrect because Intelligent Insights provides automated artificial intelligence-driven analysis rather than requiring manual log review. The feature continuously analyzes performance metrics automatically identifying anomalies and performance problems without administrator intervention or manual diagnostics.
Option C is incorrect because Intelligent Insights enhances performance monitoring by adding intelligent detection and analysis rather than disabling monitoring. The feature complements other monitoring tools by providing automated problem detection and root cause analysis improving visibility into database health.
Option D is incorrect because Azure SQL Database is a platform as a service offering where physical server infrastructure is abstracted and managed by Microsoft. Intelligent Insights operates at the database performance level rather than providing physical infrastructure access.
Intelligent Insights detects performance issues including high DTU or CPU utilization, excessive waits, tempdb contention, locking issues, high query duration, and plan choice regression. When issues are detected, diagnostic logs generated include problem descriptions, root cause analysis, performance impact assessment, and recommendations for resolution. Insights integrate with Azure Monitor enabling alerts when problems are detected, and logs can be sent to Log Analytics, Event Hubs, or storage accounts for further analysis. The feature automatically establishes performance baselines and detects deviations indicating problems. Administrators should configure diagnostic settings to route Intelligent Insights logs to monitoring solutions, review detected issues regularly, and implement recommended corrective actions. Intelligent Insights provides proactive problem detection helping maintain optimal database performance without constant manual monitoring.
Question 90:
Which Azure SQL Database security feature encrypts sensitive data in memory and during query processing?
A) Transparent Data Encryption only
B) Always Encrypted
C) Network Security Groups exclusively
D) Basic firewall rules only
Answer: B
Explanation:
Always Encrypted protects sensitive data by encrypting it at the column level within client applications with data remaining encrypted throughout its journey including in memory, during query processing, and at rest, ensuring that even database administrators cannot view plaintext sensitive data. This encryption technology provides end-to-end protection for highly sensitive information like credit card numbers, social security numbers, or personal health information.
Option A is incorrect because Transparent Data Encryption encrypts data at rest on disk but does not protect data in memory during query processing. TDE prevents unauthorized access to physical database files, while Always Encrypted protects data throughout its entire lifecycle including during active use.
Option C is incorrect because Network Security Groups control network-level access to resources rather than encrypting data. NSGs restrict which sources can connect to databases but do not provide encryption protection for data stored or processed within databases.
Option D is incorrect because firewall rules control connection permissions based on IP addresses rather than encrypting sensitive data. Firewalls provide network access control but do not protect data confidentiality through encryption when data is accessed by authorized users.
Always Encrypted uses two types of keys including column encryption keys that encrypt data and column master keys that protect column encryption keys. Keys can be stored in Azure Key Vault, Windows Certificate Store, or hardware security modules providing separation of duties where database administrators manage databases without accessing sensitive data. Two encryption types are available: deterministic encryption enabling equality searches on encrypted columns but potentially revealing patterns, and randomized encryption providing stronger protection but limiting query capabilities to retrieval only. Applications require Always Encrypted-enabled drivers and connection strings configured to enable encryption. Use cases include protecting regulated data, ensuring data privacy from cloud providers or administrators, and meeting compliance requirements for data separation. Implementation requires careful planning including determining which columns need encryption, selecting appropriate encryption types, managing key lifecycle, and modifying applications to work with encrypted data.
Question 91:
What is the function of Azure SQL Database geo-replication?
A) To delete databases across regions
B) To create readable secondary databases in different regions for disaster recovery and load distribution
C) To disable all cross-region connectivity
D) To increase single database storage only
Answer: B
Explanation:
Active geo-replication creates continuously synchronized readable secondary databases in different Azure regions providing disaster recovery capabilities, geographic load distribution for read workloads, and application resilience against regional outages. Secondary databases can be used for read-only queries reducing load on primary databases while ensuring business continuity if primary regions become unavailable.
Option A is incorrect because geo-replication creates additional copies of databases in other regions rather than deleting them. The purpose is providing redundancy and availability through multiple database instances that can survive regional failures or disasters.
Option C is incorrect because geo-replication specifically enables cross-region database synchronization rather than disabling connectivity. The feature creates connections between regions to replicate data continuously ensuring secondary databases remain current with primary databases.
Option D is incorrect because geo-replication focuses on creating additional database copies in different regions for availability and disaster recovery rather than increasing storage capacity of individual databases. Storage expansion is handled through service tier adjustments independent of replication configuration.
Active geo-replication supports up to four readable secondaries in any Azure region with asynchronous replication ensuring minimal impact on primary database performance. Applications can direct read-only queries to secondary databases improving performance and reducing primary database load. During regional outages, administrators can initiate failover promoting secondary databases to primary role with connection string updates redirecting applications. Planned failover ensures no data loss by synchronizing before failover, while unplanned failover accepts potential data loss measured in seconds for rapid recovery. Failover groups provide abstraction over geo-replication with automatic failover capabilities and listener endpoints that automatically route connections to current primary databases. Use cases include disaster recovery plans, distributing read workloads geographically closer to users, and maintaining application availability during regional maintenance or outages. Administrators should consider replication lag when reading from secondaries, plan and test failover procedures regularly, and understand RPO and RTO characteristics for their configurations.
Question 92:
Which Azure SQL Database feature automatically optimizes database maintenance operations?
A) Manual index maintenance scripts only
B) Automatic tuning for index and query optimization
C) No automated maintenance available
D) Third-party tools exclusively
Answer: B
Explanation:
Automatic tuning continuously monitors database workloads and automatically implements performance optimizations including creating missing indexes improving query performance, dropping unused indexes reducing maintenance overhead, and forcing optimal query plans when plan regressions are detected. This intelligent feature reduces database administration overhead by automatically addressing common performance issues without manual intervention.
Option A is incorrect because automatic tuning provides automated maintenance rather than requiring manual scripting. While administrators can create custom maintenance scripts, automatic tuning eliminates much of this work by intelligently managing indexes and query plans based on actual workload patterns.
Option C is incorrect because Azure SQL Database includes comprehensive automatic maintenance capabilities through automatic tuning, automatic backups, and built-in monitoring. These features continuously maintain database health without requiring extensive manual administration.
Option D is incorrect because Azure SQL Database provides built-in automatic tuning capabilities within the platform rather than requiring third-party maintenance tools. While third-party tools can provide additional functionality, native automatic tuning addresses most common optimization needs.
Automatic tuning includes three main capabilities: create index identifies queries that would benefit from indexes and automatically creates them after verifying performance improvements, drop index removes duplicate or unused indexes that consume resources without providing benefits, and force last good plan detects query plan regressions where optimizer chooses suboptimal plans and forces previously better-performing plans. Administrators enable automatic tuning at database or server level with options to automatically apply recommendations or review them before implementation. The feature validates all changes ensuring they improve performance and automatically reverts changes that degrade performance. Tuning history provides visibility into actions taken with before and after metrics demonstrating impact. Automatic tuning works continuously adapting to changing workload patterns and learning from past actions. Administrators should enable automatic tuning for production databases, review tuning recommendations and actions through Azure portal or DMVs, and combine with Query Performance Insight for comprehensive performance management.
Question 93:
What is the purpose of Azure SQL Database dynamic data masking?
A) To permanently delete sensitive data
B) To obfuscate sensitive data in query results for unauthorized users while keeping original data intact
C) To encrypt all database connections
D) To disable database queries completely
Answer: B
Explanation:
Dynamic data masking limits sensitive data exposure by obfuscating it in query results for non-privileged users while maintaining original data unchanged in the database. This security feature applies masking rules to designated columns automatically masking data in query results based on user privileges, protecting information like credit card numbers, social security numbers, or email addresses from unauthorized viewing.
Option A is incorrect because dynamic data masking obfuscates data in query results rather than permanently deleting or modifying actual stored data. Original data remains intact in the database with masking applied only to query results based on user permissions.
Option C is incorrect because encrypting database connections is handled by Transport Layer Security and connection encryption settings rather than dynamic data masking. Data masking focuses on obfuscating sensitive column values in query results while TLS protects data during transmission.
Option D is incorrect because dynamic data masking allows queries to execute normally but masks sensitive values in results rather than disabling query execution. Authorized users see actual data while unauthorized users see masked values, maintaining database functionality while protecting sensitive information.
Dynamic data masking supports several masking functions including default masking that fully masks values showing X characters, email masking that shows first letter and domain while masking middle portion, random number masking that replaces numbers with random values within specified ranges, and custom string masking that exposes defined portions while masking the rest. Masking rules are defined on specific columns with functions applied to those columns. Privileged users can be exempted from masking seeing actual values regardless of masking rules. Implementation is straightforward requiring definition of masking rules on sensitive columns without application changes. Use cases include protecting sensitive data in non-production environments, limiting sensitive data exposure to application users, and meeting compliance requirements for data privacy. Administrators should identify sensitive columns requiring masking, select appropriate masking functions for data types, test masking with different user privileges, and understand that masking does not prevent data access but only obfuscates displayed values.
Question 94:
Which Azure SQL Database monitoring tool collects and analyzes database telemetry?
A) Azure Monitor and Log Analytics
B) Manual log file review exclusively
C) No monitoring tools available
D) Physical server monitoring only
Answer: A
Explanation:
Azure Monitor and Log Analytics provide comprehensive monitoring solutions collecting database telemetry including performance metrics, resource utilization, query statistics, and diagnostic logs enabling detailed analysis, alerting, and visualization of database health and performance. These tools integrate with Azure SQL Database providing unified monitoring across Azure resources with customizable dashboards, alerting rules, and advanced query capabilities.
Option B is incorrect because Azure SQL Database provides sophisticated automated monitoring tools rather than requiring manual log file review. While administrators can review logs manually, Azure Monitor automates collection, analysis, and alerting based on telemetry data.
Option C is incorrect because Azure SQL Database includes extensive built-in monitoring capabilities through Azure Monitor, Query Performance Insight, Intelligent Insights, and dynamic management views. These tools provide comprehensive visibility into database health and performance.
Option D is incorrect because Azure SQL Database is a platform as a service offering where physical server monitoring is handled by Microsoft. Database monitoring focuses on logical database performance, queries, and resource utilization rather than underlying physical infrastructure.
Azure Monitor collects metrics like DTU or CPU percentage, storage usage, connection statistics, and deadlocks with retention periods and granularity based on configuration. Diagnostic settings route logs including query performance statistics, wait statistics, errors, and intelligent insights to destinations like Log Analytics workspaces, storage accounts, or Event Hubs. Log Analytics provides powerful Kusto Query Language for analyzing telemetry, creating custom queries, and building dashboards. Alert rules trigger notifications when metrics exceed thresholds or specific events occur. Workbooks provide customizable visualizations combining multiple data sources. Integration with Azure SQL Insights provides specialized database monitoring views. Administrators should configure diagnostic settings to capture relevant logs, create alerts for critical conditions like high CPU or failed connections, build dashboards showing key performance indicators, and regularly review monitoring data to identify trends and potential issues. Effective monitoring enables proactive problem detection, capacity planning, and performance optimization.
Question 95:
What is the function of Azure SQL Database firewall rules?
A) To encrypt data at rest exclusively
B) To control which IP addresses can connect to logical servers and databases
C) To increase database performance automatically
D) To provide backup services only
Answer: B
Explanation:
Azure SQL Database firewall rules control network access by specifying which IP addresses or ranges are permitted to connect to logical servers and individual databases, blocking all connection attempts by default until administrators explicitly allow access. This network-level security prevents unauthorized connection attempts protecting databases from internet-based attacks and ensuring only approved sources can establish database connections.
Option A is incorrect because data encryption at rest is provided by Transparent Data Encryption rather than firewall rules. Firewall rules control network access determining who can connect, while TDE protects data stored on disk from unauthorized access to physical media.
Option C is incorrect because firewall rules provide security through access control rather than affecting database performance. While firewall evaluation occurs during connection establishment, it does not impact query performance or database operations once connections are authenticated.
Option D is incorrect because backup services are provided by Azure SQL Database automatic backup functionality rather than firewall rules. Firewall rules control connection access while backup services protect data through continuous automated backups independent of network security configuration.
Firewall rules exist at two levels: server-level rules apply to all databases on a logical server and are stored in master database, while database-level rules apply to individual databases providing more granular control. Rules specify IP address ranges defining allowed sources with rules evaluated in order until a match is found. Azure services can be allowed through special rules enabling connections from other Azure resources. Virtual network rules provide more secure access control by allowing connections only from specific virtual network subnets rather than public IP addresses. Administrators configure rules through Azure Portal, PowerShell, Azure CLI, or Transact-SQL. Best practices include limiting access to specific IP ranges rather than allowing all addresses, using virtual network rules for Azure-hosted applications, regularly reviewing and removing unnecessary rules, and combining firewall rules with authentication and authorization for defense-in-depth security. Connection attempts from blocked addresses fail immediately at the network level before authentication occurs.
Question 96:
Which Azure SQL Database feature provides automated performance recommendations?
A) Database Advisor
B) Manual performance analysis exclusively
C) No recommendation capabilities available
D) Third-party tools only
Answer: A
Explanation:
Database Advisor analyzes database workloads and provides intelligent performance recommendations including index creation suggestions, index drop recommendations, schema issue identification, and parameterization opportunities. This feature uses machine learning to understand workload patterns and generate actionable recommendations that improve query performance and reduce resource consumption when implemented.
Option B is incorrect because Database Advisor provides automated artificial intelligence-driven recommendations rather than requiring manual performance analysis. While administrators can perform manual analysis, Database Advisor continuously monitors databases automatically identifying optimization opportunities without manual intervention.
Option C is incorrect because Azure SQL Database includes comprehensive recommendation capabilities through Database Advisor, automatic tuning, and Intelligent Insights. These features provide proactive guidance for optimizing database performance based on actual workload analysis.
Option D is incorrect because Database Advisor is a built-in Azure SQL Database feature rather than requiring third-party tools. The platform provides native performance recommendation capabilities eliminating the need for external analysis tools for most optimization scenarios.
Database Advisor recommendations include create index suggestions for missing indexes that would improve query performance with estimated impact scores, drop index recommendations for unused or duplicate indexes consuming resources, schema issues like missing primary keys or statistics, and parameterization suggestions for queries that would benefit from forced parameterization. Each recommendation includes detailed justification, estimated performance impact, affected queries, and implementation scripts. Administrators can review recommendations through Azure Portal or query system views, choose to implement recommendations manually or enable automatic tuning to apply them automatically after validation. The advisor tracks implemented recommendations and reverts them if performance degrades. Recommendations are based on actual workload analysis over time ensuring they reflect real usage patterns rather than theoretical optimizations. Administrators should regularly review Database Advisor recommendations, prioritize high-impact suggestions, test recommendations in non-production environments when possible, and monitor results after implementation to ensure expected improvements are realized.
Question 97:
What is the purpose of Azure SQL Database managed instance?
A) To provide IaaS virtual machines exclusively
B) To offer near 100 percent SQL Server compatibility with PaaS benefits
C) To disable all cloud features
D) To require manual infrastructure management
Answer: B
Explanation:
Azure SQL Database Managed Instance provides near 100 percent compatibility with on-premises SQL Server Enterprise Edition while delivering platform as a service benefits including automated patching, backups, high availability, and reduced management overhead. This deployment option enables lift-and-shift migrations of on-premises SQL Server applications to Azure with minimal application changes while maintaining advanced SQL Server features.
Option A is incorrect because Managed Instance is a platform as a service offering rather than infrastructure as a service virtual machines. While Managed Instance provides more SQL Server feature compatibility than single databases, it abstracts infrastructure management unlike IaaS VMs requiring operating system and SQL Server administration.
Option C is incorrect because Managed Instance specifically provides cloud platform benefits including automated backups, built-in high availability, automatic patching, and elastic scalability. The service combines extensive SQL Server compatibility with cloud advantages rather than disabling cloud features.
Option D is incorrect because Managed Instance reduces infrastructure management by providing automated platform services rather than requiring manual administration. Microsoft manages underlying infrastructure, operating system patching, and SQL Server updates while administrators focus on database management.
Managed Instance supports features not available in single databases including SQL Agent, cross-database queries, linked servers, Service Broker, database mail, CLR assemblies, and change data capture. Native virtual network integration provides secure connectivity and private IP addresses. Use cases include migrating on-premises SQL Server databases to cloud with minimal changes, applications requiring SQL Server features not available in single databases, and consolidating multiple databases requiring instance-level features. Deployment involves selecting service tier (General Purpose or Business Critical), compute resources, and storage capacity. Managed Instance provides multiple databases per instance, similar to on-premises SQL Server. Administrators should assess application compatibility using Data Migration Assistant, plan virtual network configuration before deployment, consider service tier characteristics for performance and cost requirements, and understand limitations compared to on-premises SQL Server. Managed Instance bridges the gap between single databases and SQL Server on virtual machines providing optimal balance of compatibility and platform benefits.
Question 98:
Which Azure SQL Database security feature provides row-level security?
A) Row-Level Security (RLS)
B) Column-level encryption only
C) Network security groups exclusively
D) Database firewall rules only
Answer: A
Explanation:
Row-Level Security enables fine-grained access control by restricting which rows users can access based on user characteristics like identity, role, or custom logic implemented through security predicates. RLS enforces access control directly in the database layer ensuring security policies apply consistently regardless of application layer controls, preventing unauthorized access to sensitive row data.
Option B is incorrect because column-level encryption through Always Encrypted protects specific columns rather than controlling row-level access. While both features enhance data security, they address different concerns with column encryption protecting data confidentiality and row-level security controlling which rows users can see.
Option C is incorrect because network security groups control network traffic flow at the infrastructure level rather than providing row-level data access control within databases. NSGs restrict which sources can connect to resources but do not filter which specific data rows users can access.
Option D is incorrect because database firewall rules control which IP addresses can establish database connections rather than filtering row access within databases. Firewall rules provide network-level access control while row-level security provides data-level access control within tables.
Row-Level Security implementation involves creating security predicates as inline table-valued functions that define filtering logic, then creating security policies binding predicates to tables. Filter predicates silently filter rows from SELECT, UPDATE, and DELETE operations while block predicates explicitly prevent INSERT, UPDATE, and DELETE operations that violate security rules. Common scenarios include multi-tenant applications where tenants should only access their own data, organizations where employees access only data relevant to their departments, and applications requiring data isolation based on user roles or attributes. RLS uses session context information like USER_NAME, USER_ID, or custom session variables to determine appropriate filtering. Security policies can be enabled or disabled without dropping them, and multiple predicates can apply to single tables. Administrators should carefully design predicate logic ensuring performance by using indexed columns in filter conditions, thoroughly test security policies with different user contexts, consider performance implications of complex predicates, and document security policies for compliance and maintenance. RLS provides centralized security enforcement in the database layer reducing application complexity and ensuring consistent protection across all database access methods.
Question 99:
What is the function of Azure SQL Database query store?
A) To delete query history automatically
B) To capture and retain query execution plans and performance statistics over time
C) To disable query execution completely
D) To provide network routing services
Answer: B
Explanation:
Query Store automatically captures and retains comprehensive information about queries including execution plans, runtime statistics, wait statistics, and query text over configurable retention periods. This feature provides historical performance analysis enabling administrators to identify query performance regressions, compare execution plan changes over time, and understand query behavior trends without requiring external monitoring tools.
Option A is incorrect because Query Store retains query history for analysis rather than deleting it. The feature maintains configurable retention periods ensuring historical data remains available for trend analysis and performance troubleshooting while automatically aging out old data based on retention policies.
Option C is incorrect because Query Store monitors query execution rather than disabling queries. The feature operates transparently capturing performance information as queries execute normally without preventing query execution or affecting application functionality.
Option D is incorrect because Query Store provides query performance monitoring within databases rather than network routing services. Network routing is handled by Azure networking infrastructure while Query Store focuses on database query analysis and optimization.
Query Store captures query text, execution plans, runtime statistics including execution count, duration, CPU time, logical and physical reads, and wait statistics identifying performance bottlenecks. Data is stored in internal tables within the database with minimal performance impact. Query Store enables features like automatic tuning which relies on Query Store data to detect plan regressions and force optimal plans. Administrators query Query Store data through built-in catalog views and dynamic management views, or use graphical Query Store reports in SQL Server Management Studio showing top resource-consuming queries, queries with plan changes, and overall Query Store statistics. Configuration options include retention period, capture mode controlling which queries are captured, and size limits. Query Store should be enabled for production databases to enable automatic tuning and performance troubleshooting, configured with appropriate retention periods balancing historical analysis needs against storage consumption, and regularly reviewed to identify optimization opportunities. The feature is essential for understanding query performance over time and detecting regressions when code or schema changes occur.
Question 100:
Which Azure SQL Database tool helps migrate on-premises SQL Server databases to Azure?
A) Azure Database Migration Service
B) Manual script execution exclusively
C) No migration tools available
D) Physical media transfer only
Answer: A
Explanation:
Azure Database Migration Service provides comprehensive tooling for migrating on-premises SQL Server databases, other database platforms, and cloud databases to Azure SQL Database with minimal downtime through online migrations. The service supports assessment, schema conversion, data migration, and validation ensuring successful migrations while handling differences between source and target platforms.
Option B is incorrect because Azure provides sophisticated migration tools rather than requiring manual script creation and execution. While administrators can perform manual migrations using scripts, Azure Database Migration Service automates much of the process reducing complexity and migration time.
Option C is incorrect because Microsoft provides multiple migration tools including Azure Database Migration Service, Data Migration Assistant for assessment and offline migrations, SQL Server Management Studio with deployment wizards, and Azure Data Studio with migration extensions. These tools support various migration scenarios and database platforms.
Option D is incorrect because modern cloud migrations use network-based transfers rather than physical media. Azure Database Migration Service performs online migrations over network connections enabling minimal downtime migrations for production databases without requiring physical backup media transfer.
Azure Database Migration Service supports offline migrations where source databases are unavailable during migration suitable for non-production systems, and online migrations using transaction log replication minimizing downtime for production databases. The service handles schema migration, data transfer, and validation with detailed progress monitoring. Data Migration Assistant complements the service by assessing database compatibility, identifying migration blockers or warnings, and recommending remediation steps before migration. Migration workflows typically involve assessing source databases for compatibility issues, addressing identified issues, creating target Azure SQL databases, configuring Azure Database Migration Service projects specifying source and target, executing migration with monitoring, and validating migrated databases. The service supports SQL Server, MySQL, PostgreSQL, MongoDB, and other platforms as sources. Administrators should thoroughly assess databases before migration, plan appropriate service tiers for target databases, test migrations in non-production environments, prepare rollback plans, and schedule production migrations during maintenance windows. Migration tools significantly simplify cloud adoption by automating complex migration tasks and ensuring data integrity throughout the process.
