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+---
+name: sql-server-2025
+description: SQL Server 2025 and SqlPackage 170.2.70 (October 2025) - Vector databases, AI integration, and latest features
+---
+
+## 🚨 CRITICAL GUIDELINES
+
+### Windows File Path Requirements
+
+**MANDATORY: Always Use Backslashes on Windows for File Paths**
+
+When using Edit or Write tools on Windows, you MUST use backslashes (`\`) in file paths, NOT forward slashes (`/`).
+
+**Examples:**
+- ❌ WRONG: `D:/repos/project/file.tsx`
+- ✅ CORRECT: `D:\repos\project\file.tsx`
+
+This applies to:
+- Edit tool file_path parameter
+- Write tool file_path parameter
+- All file operations on Windows systems
+
+
+### Documentation Guidelines
+
+**NEVER create new documentation files unless explicitly requested by the user.**
+
+- **Priority**: Update existing README.md files rather than creating new documentation
+- **Repository cleanliness**: Keep repository root clean - only README.md unless user requests otherwise
+- **Style**: Documentation should be concise, direct, and professional - avoid AI-generated tone
+- **User preference**: Only create additional .md files when user specifically asks for documentation
+
+
+---
+
+# SQL Server 2025 & SqlPackage 170.2.70 Support
+
+## Overview
+
+**SQL Server 2025** is the enterprise AI-ready database with native vector database capabilities, built-in AI model integration, and semantic search from ground to cloud.
+
+**SqlPackage 170.2.70** (October 14, 2025) - Latest production release with full SQL Server 2025 support, data virtualization, and parquet file enhancements.
+
+## SqlPackage 170.x Series (2025 Releases)
+
+### Latest Version: 170.2.70 (October 14, 2025)
+
+Three major 2025 releases:
+- **170.2.70** - October 14, 2025 (Current)
+- **170.1.61** - July 30, 2025 (Data virtualization)
+- **170.0.94** - April 15, 2025 (SQL Server 2025 initial support)
+
+### Key 2025 Features
+
+**Data Virtualization (170.1.61+)**:
+- Support for Azure SQL Database data virtualization objects
+- Import/export/extract/publish operations for external data sources
+- Parquet file support for Azure SQL Database with Azure Blob Storage
+- Automatic fallback to BCP for CLR types and LOBs > 1MB
+
+**New Data Types**:
+- **VECTOR** - Up to 3,996 dimensions with half-precision (2-byte) floating-point
+- **JSON** - Native JSON data type for Azure SQL Database
+
+**New Permissions (170.0+)**:
+- `ALTER ANY INFORMATION PROTECTION` - SQL Server 2025 & Azure SQL
+- `ALTER ANY EXTERNAL MIRROR` - Azure SQL & SQL database in Fabric
+- `CREATE/ALTER ANY EXTERNAL MODEL` - AI/ML model management
+
+**Deployment Options**:
+- `/p:IgnorePreDeployScript=True/False` - Skip pre-deployment scripts
+- `/p:IgnorePostDeployScript=True/False` - Skip post-deployment scripts
+
+### SqlPackage Commands
+
+```bash
+# Publish to SQL Server 2025
+sqlpackage /Action:Publish \
+  /SourceFile:Database.dacpac \
+  /TargetServerName:server2025.database.windows.net \
+  /TargetDatabaseName:MyDatabase \
+  /TargetDatabaseEdition:Premium \
+  /p:TargetPlatform=SqlServer2025  # New target platform
+
+# Extract from SQL Server 2025
+sqlpackage /Action:Extract \
+  /SourceServerName:server2025.database.windows.net \
+  /SourceDatabaseName:MyDatabase \
+  /TargetFile:Database.dacpac \
+  /p:ExtractAllTableData=False \
+  /p:VerifyExtraction=True
+
+# Export with SQL Server 2025 features
+sqlpackage /Action:Export \
+  /SourceServerName:server2025.database.windows.net \
+  /SourceDatabaseName:MyDatabase \
+  /TargetFile:Database.bacpac
+```
+
+## ScriptDom Version 170.0.64
+
+New ScriptDom version for SQL Server 2025 syntax parsing:
+
+```csharp
+// Package: Microsoft.SqlServer.TransactSql.ScriptDom 170.0.64
+
+using Microsoft.SqlServer.TransactSql.ScriptDom;
+
+// Parse SQL Server 2025 syntax
+var parser = new TSql170Parser(true);
+IList<ParseError> errors;
+var fragment = parser.Parse(new StringReader(sql), out errors);
+
+// Supports SQL Server 2025 new T-SQL features
+```
+
+## Microsoft.Build.Sql 2.0.0 GA (2025)
+
+**MAJOR MILESTONE:** Microsoft.Build.Sql SDK entered General Availability in 2025!
+
+### Latest Version: 2.0.0 (Production Ready)
+
+**Breaking Change from Preview:**
+- SDK is now production-ready and recommended for all new database projects
+- No longer in preview status
+- Full cross-platform support (Windows/Linux/macOS)
+- Requires .NET 8+ (was .NET 6+ in preview)
+
+### SQL Server 2025 Support
+
+**Current Status:** SQL Server 2025 target platform support coming in future Microsoft.Build.Sql release (post-2.0.0).
+
+**Workaround for SDK-Style Projects:**
+```xml
+<!-- Database.sqlproj (SDK-style with SQL Server 2025 compatibility) -->
+<Project Sdk="Microsoft.Build.Sql/2.0.0">
+  <PropertyGroup>
+    <Name>MyDatabase</Name>
+    <!-- Use SQL Server 2022 (160) provider until 2025 provider available -->
+    <DSP>Microsoft.Data.Tools.Schema.Sql.Sql160DatabaseSchemaProvider</DSP>
+    <TargetFramework>net8.0</TargetFramework>
+    <SqlServerVersion>Sql160</SqlServerVersion>
+
+    <!-- SQL Server 2025 features will still work in runtime database -->
+    <!-- Only build-time validation uses Sql160 provider -->
+  </PropertyGroup>
+
+  <ItemGroup>
+    <Folder Include="Tables\" />
+    <Folder Include="Views\" />
+    <Folder Include="StoredProcedures\" />
+  </ItemGroup>
+</Project>
+```
+
+### Visual Studio 2022 Support
+
+**Requirement:** Visual Studio 2022 version 17.12 or later for SDK-style SQL projects.
+
+**Note:** Side-by-side installation with original SQL projects (legacy SSDT) is NOT supported.
+
+## SQL Server 2025 Release Status
+
+**Current Status**: SQL Server 2025 (17.x) is in **Release Candidate (RC1)** stage as of October 2025. Public preview began May 2025.
+
+**Predicted GA Date**: November 12, 2025 (based on historical release patterns - SQL Server 2019: Nov 4, SQL Server 2022: Nov 16). Expected announcement at Microsoft Ignite conference (November 18-21, 2025).
+
+**Not Yet Production**: SQL Server 2025 is not yet generally available. All features described are available in RC builds for testing purposes only.
+
+## SQL Server 2025 New Features
+
+### Vector Database for AI
+
+**Native Enterprise Vector Store** with built-in security, compliance, and DiskANN indexing technology.
+
+**Key Capabilities:**
+- **Up to 3,996 dimensions** per vector (half-precision 2-byte floating-point)
+- **DiskANN indexing** - Disk-based approximate nearest neighbor for efficient large-scale vector search
+- **Hybrid AI vector search** - Combine vectors with SQL data for semantic + keyword search
+- **Built-in security & compliance** - Enterprise-grade data protection
+
+**Vector Embedding & Text Chunking:**
+```sql
+-- Create table with vector column
+CREATE TABLE Documents (
+    Id INT PRIMARY KEY IDENTITY,
+    Title NVARCHAR(200),
+    Content NVARCHAR(MAX),
+    -- Half-precision vectors support up to 3,996 dimensions
+    ContentVector VECTOR(1536)  -- OpenAI ada-002: 1,536 dims
+    -- ContentVector VECTOR(3072)  -- OpenAI text-embedding-3-large: 3,072 dims
+    -- ContentVector VECTOR(3996)  -- Maximum: 3,996 dims
+);
+
+-- Insert vectors (T-SQL built-in embedding generation)
+INSERT INTO Documents (Title, Content, ContentVector)
+VALUES (
+    'AI Documentation',
+    'Azure AI services...',
+    CAST('[0.1, 0.2, 0.3, ...]' AS VECTOR(1536))
+);
+
+-- Semantic similarity search with DiskANN
+DECLARE @QueryVector VECTOR(1536) = CAST('[0.15, 0.25, ...]' AS VECTOR(1536));
+
+SELECT TOP 10
+    Id,
+    Title,
+    Content,
+    VECTOR_DISTANCE('cosine', ContentVector, @QueryVector) AS Similarity
+FROM Documents
+ORDER BY Similarity;
+
+-- Create DiskANN vector index for performance
+CREATE INDEX IX_Documents_Vector
+ON Documents(ContentVector)
+USING VECTOR_INDEX
+WITH (
+    DISTANCE_METRIC = 'cosine',  -- or 'euclidean', 'dot_product'
+    VECTOR_SIZE = 1536
+);
+
+-- Hybrid search: Combine vector similarity with traditional filtering
+SELECT TOP 10
+    Id,
+    Title,
+    VECTOR_DISTANCE('cosine', ContentVector, @QueryVector) AS Similarity
+FROM Documents
+WHERE Title LIKE '%Azure%'  -- Traditional keyword filter
+ORDER BY Similarity;
+```
+
+### AI Model Integration
+
+**Built into T-SQL** - Seamlessly integrate AI services with model definitions directly in the database.
+
+**Supported AI Services:**
+- Azure AI Foundry
+- Azure OpenAI Service
+- OpenAI
+- Ollama (local/self-hosted models)
+- Custom REST APIs
+
+**Developer Frameworks:**
+- LangChain integration
+- Semantic Kernel integration
+- Entity Framework Core support
+- **GraphQL via Data API Builder (DAB)** - Expose SQL Server data through GraphQL endpoints
+
+**External Models (ONNX):**
+```sql
+-- Create external model from ONNX file
+CREATE EXTERNAL MODEL AIModel
+FROM 'https://storage.account.blob.core.windows.net/models/model.onnx'
+WITH (
+    TYPE = 'ONNX',
+    INPUT_DATA_FORMAT = 'JSON',
+    OUTPUT_DATA_FORMAT = 'JSON'
+);
+
+-- Use model for predictions
+DECLARE @Input NVARCHAR(MAX) = '{"text": "Hello world"}';
+SELECT PREDICT(MODEL = AIModel, DATA = @Input) AS Prediction;
+
+-- Grant model permissions (new SQL Server 2025 permission)
+GRANT CREATE ANY EXTERNAL MODEL TO [ModelAdmin];
+GRANT ALTER ANY EXTERNAL MODEL TO [ModelAdmin];
+GRANT EXECUTE ON EXTERNAL MODEL::AIModel TO [AppUser];
+```
+
+**AI Service Integration:**
+```sql
+-- Example: Azure OpenAI integration
+-- Model definitions built directly into T-SQL
+-- Access through REST APIs with built-in authentication
+```
+
+### Optimized Locking (Performance Enhancement)
+
+**Key Innovation**: Dramatically reduces lock memory consumption and minimizes blocking for concurrent transactions.
+
+**Two Primary Components**:
+
+1. **Transaction ID (TID) Locking**:
+   - Each row labeled with last TID (Transaction ID) that modified it
+   - Single lock on TID instead of many row locks
+   - Locks released as soon as row is updated
+   - Only one TID lock held until transaction ends
+   - **Example**: Updating 1,000 rows requires 1,000 X row locks, but each is released immediately, and only one TID lock is held until commit
+
+2. **Lock After Qualification (LAQ)**:
+   - Evaluates query predicates using latest committed version WITHOUT acquiring lock
+   - Requires READ COMMITTED SNAPSHOT ISOLATION (RCSI)
+   - Predicates checked optimistically on committed data
+   - X row lock taken only if predicate satisfied
+   - Lock released immediately after row update
+
+**Benefits**:
+- Reduced lock memory usage
+- Increased concurrency and scale
+- Minimized lock escalation
+- Enhanced application uptime
+- Better performance for high-concurrency workloads
+
+**Enabling Optimized Locking**:
+```sql
+-- Enable RCSI (required for LAQ)
+ALTER DATABASE MyDatabase
+SET READ_COMMITTED_SNAPSHOT ON;
+
+-- Optimized locking is automatically enabled at database level
+-- No additional configuration needed for SQL Server 2025
+
+-- Verify optimized locking status
+SELECT name, is_read_committed_snapshot_on
+FROM sys.databases
+WHERE name = 'MyDatabase';
+
+-- Monitor optimized locking performance
+SELECT *
+FROM sys.dm_tran_locks
+WHERE request_session_id = @@SPID;
+```
+
+### Microsoft Fabric Mirroring (Zero-ETL Analytics)
+
+**Integration**: Near real-time replication of SQL Server databases to Microsoft Fabric OneLake for analytics.
+
+**Key Capabilities**:
+- **Zero-ETL Experience**: No complex ETL pipelines required
+- **SQL Server 2025-Specific**: Uses new change feed technology (vs CDC in SQL Server 2016-2022)
+- **Azure Arc Required**: SQL Server 2025 requires Azure Arc-enabled server for Fabric communication
+- **Real-Time Analytics**: Offload analytic workloads to Fabric without impacting production
+
+**Supported Scenarios**:
+- SQL Server 2025 on-premises (Windows)
+- NOT supported: Azure VM or Linux instances (yet)
+
+**How It Works**:
+```sql
+-- SQL Server 2025 uses change feed (automatic)
+-- Azure Arc agent handles replication to Fabric OneLake
+
+-- Traditional SQL Server 2016-2022 approach (CDC):
+-- EXEC sys.sp_cdc_enable_db;
+-- EXEC sys.sp_cdc_enable_table ...
+
+-- SQL Server 2025: Change feed is built-in, no CDC setup needed
+```
+
+**Benefits**:
+- Free Fabric compute for replication
+- Free OneLake storage (based on capacity size)
+- Near real-time data availability
+- BI and analytics without production load
+- Integration with Power BI, Synapse, Azure ML
+
+**Configuration**:
+1. Enable Azure Arc on SQL Server 2025 instance
+2. Configure Fabric workspace and OneLake
+3. Enable mirroring in Fabric portal
+4. Select database and tables to mirror
+5. Data automatically replicated with change feed
+
+**Monitoring**:
+```sql
+-- Monitor replication lag
+SELECT
+    database_name,
+    table_name,
+    last_sync_time,
+    rows_replicated,
+    replication_lag_seconds
+FROM sys.dm_fabric_replication_status;
+```
+
+### Native JSON Support Enhancements
+
+**New JSON Data Type**: Native JSON data type for Azure SQL Database (coming to SQL Server 2025).
+
+```sql
+-- New JSON data type
+CREATE TABLE Products (
+    Id INT PRIMARY KEY,
+    Name NVARCHAR(100),
+    Metadata JSON  -- Native JSON type
+);
+
+-- JSON functions enhanced
+INSERT INTO Products (Id, Name, Metadata)
+VALUES (1, 'Laptop', JSON('{"brand": "Dell", "ram": 16, "ssd": 512}'));
+
+-- Query JSON with improved performance
+SELECT
+    Id,
+    Name,
+    JSON_VALUE(Metadata, '$.brand') AS Brand,
+    JSON_VALUE(Metadata, '$.ram') AS RAM
+FROM Products;
+```
+
+### Regular Expression (RegEx) Support
+
+**T-SQL RegEx Functions**: Validate, search, and manipulate strings with regular expressions.
+
+```sql
+-- RegEx matching
+SELECT REGEXP_LIKE('test@example.com', '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$') AS IsValidEmail;
+
+-- RegEx replace
+SELECT REGEXP_REPLACE('Phone: 555-1234', '\d+', 'XXX') AS MaskedPhone;
+
+-- RegEx extract
+SELECT REGEXP_SUBSTR('Order #12345', '\d+') AS OrderNumber;
+```
+
+### REST API Integration
+
+**Built-in REST Capabilities**: Call external REST APIs directly from T-SQL.
+
+```sql
+-- Call REST API from T-SQL
+DECLARE @Response NVARCHAR(MAX);
+
+EXEC sp_invoke_external_rest_endpoint
+    @url = 'https://api.example.com/data',
+    @method = 'GET',
+    @headers = '{"Authorization": "Bearer token123"}',
+    @response = @Response OUTPUT;
+
+SELECT @Response AS APIResponse;
+
+-- Enrich database data with external APIs
+UPDATE Customers
+SET EnrichedData = (
+    SELECT JSON_VALUE(response, '$.data')
+    FROM OPENROWSET(REST, 'https://api.example.com/customer/' + CustomerId)
+)
+WHERE CustomerId = 12345;
+```
+
+### Optional Parameter Plan Optimization (OPPO)
+
+**Performance Enhancement**: SQL Server 2025 introduces OPPO to enable optimal execution plan selection based on customer-provided runtime parameter values.
+
+**Key Benefits:**
+- Solves parameter sniffing issues
+- Optimizes plans for specific runtime parameters
+- Improves query performance with parameter-sensitive workloads
+- Reduces need for query hints or plan guides
+
+**Enabling OPPO:**
+```sql
+-- Enable at database level
+ALTER DATABASE MyDatabase
+SET PARAMETER_SENSITIVE_PLAN_OPTIMIZATION = ON;
+
+-- Check status
+SELECT name, is_parameter_sensitive_plan_optimization_on
+FROM sys.databases
+WHERE name = 'MyDatabase';
+
+-- Monitor OPPO usage
+SELECT
+    query_plan_hash,
+    parameter_values,
+    execution_count,
+    avg_duration_ms
+FROM sys.dm_exec_query_stats
+WHERE is_parameter_sensitive = 1;
+```
+
+### Microsoft Entra Managed Identities
+
+**Security Enhancement**: SQL Server 2025 adds support for Microsoft Entra managed identities for improved credential management.
+
+**Key Benefits:**
+- Eliminates hardcoded credentials
+- Reduces security vulnerabilities
+- Provides compliance and auditing capabilities
+- Simplifies credential rotation
+
+**Configuration:**
+```sql
+-- Create login with managed identity
+CREATE LOGIN [managed-identity-name] FROM EXTERNAL PROVIDER;
+
+-- Grant permissions
+CREATE USER [managed-identity-name] FOR LOGIN [managed-identity-name];
+GRANT CONTROL ON DATABASE::MyDatabase TO [managed-identity-name];
+
+-- Use in connection strings
+-- Connection string: Server=myserver;Database=mydb;Authentication=Active Directory Managed Identity;
+```
+
+### Enhanced Information Protection
+
+Sensitivity classification and encryption:
+
+```sql
+-- Classify sensitive columns
+ADD SENSITIVITY CLASSIFICATION TO
+    Customers.Email,
+    Customers.CreditCard
+WITH (
+    LABEL = 'Confidential',
+    INFORMATION_TYPE = 'Financial'
+);
+
+-- Query classification
+SELECT
+    schema_name(o.schema_id) AS SchemaName,
+    o.name AS TableName,
+    c.name AS ColumnName,
+    s.label AS SensitivityLabel,
+    s.information_type AS InformationType
+FROM sys.sensitivity_classifications s
+INNER JOIN sys.objects o ON s.major_id = o.object_id
+INNER JOIN sys.columns c ON s.major_id = c.object_id AND s.minor_id = c.column_id;
+```
+
+## Deployment to SQL Server 2025
+
+### Using SqlPackage
+
+```bash
+# Publish with 2025 features
+sqlpackage /Action:Publish \
+  /SourceFile:Database.dacpac \
+  /TargetConnectionString:"Server=tcp:server2025.database.windows.net;Database=MyDb;Authentication=ActiveDirectoryManagedIdentity;" \
+  /p:BlockOnPossibleDataLoss=True \
+  /p:IncludeCompositeObjects=True \
+  /p:DropObjectsNotInSource=False \
+  /p:DoNotDropObjectTypes=Users;RoleMembership \
+  /p:GenerateSmartDefaults=True \
+  /DiagnosticsFile:deploy.log
+```
+
+### Using MSBuild
+
+```xml
+<!-- Database.publish.xml -->
+<Project>
+  <PropertyGroup>
+    <TargetConnectionString>Server=tcp:server2025.database.windows.net;Database=MyDb;Authentication=ActiveDirectoryManagedIdentity;</TargetConnectionString>
+    <BlockOnPossibleDataLoss>True</BlockOnPossibleDataLoss>
+    <TargetDatabaseName>MyDatabase</TargetDatabaseName>
+    <ProfileVersionNumber>1</ProfileVersionNumber>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <SqlCmdVariable Include="Environment">
+      <Value>Production</Value>
+    </SqlCmdVariable>
+  </ItemGroup>
+</Project>
+```
+
+```bash
+# Deploy using MSBuild
+msbuild Database.sqlproj \
+  /t:Publish \
+  /p:PublishProfile=Database.publish.xml \
+  /p:TargetPlatform=SqlServer2025
+```
+
+## CI/CD Best Practices 2025
+
+### Key Principles
+
+**State-Based Deployment (Recommended):**
+- Source code represents current database state
+- All objects (procedures, tables, triggers, views) in separate .sql files
+- SqlPackage generates incremental scripts automatically
+- Preferred over migration-based approaches
+
+**Testing & Quality:**
+- **tSQLt** - Unit testing for SQL Server stored procedures and functions
+- Tests produce machine-readable results
+- Abort pipeline on test failure with immediate notifications
+- Never continue deployment if tests fail
+
+**Security:**
+- **Windows Authentication preferred** for CI/CD (avoid plain text passwords)
+- Never commit credentials to source control
+- Use Azure Key Vault or GitHub Secrets for connection strings
+
+**Version Control:**
+- All database objects in source control
+- Test scripts versioned and executed in Build step
+- Require comments on check-ins
+- Configure custom check-in policies
+
+### GitHub Actions (2025 Pattern)
+
+```yaml
+name: Deploy to SQL Server 2025
+
+on:
+  push:
+    branches: [main]
+
+jobs:
+  build-and-test:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: Setup .NET 8
+      uses: actions/setup-dotnet@v4
+      with:
+        dotnet-version: '8.0.x'
+
+    - name: Install SqlPackage 170.2.70
+      run: dotnet tool install -g Microsoft.SqlPackage --version 170.2.70
+
+    - name: Build DACPAC
+      run: dotnet build Database.sqlproj -c Release
+
+    - name: Run tSQLt Unit Tests
+      run: |
+        # Run unit tests and capture results
+        # Abort if tests fail
+        echo "Running tSQLt unit tests..."
+        # Add your tSQLt test execution here
+
+    - name: Generate Deployment Report
+      run: |
+        sqlpackage /Action:DeployReport \
+          /SourceFile:bin/Release/Database.dacpac \
+          /TargetConnectionString:"${{ secrets.SQL_CONNECTION_STRING }}" \
+          /OutputPath:deploy-report.xml \
+          /p:BlockOnPossibleDataLoss=True
+
+    - name: Publish to SQL Server 2025
+      run: |
+        sqlpackage /Action:Publish \
+          /SourceFile:bin/Release/Database.dacpac \
+          /TargetConnectionString:"${{ secrets.SQL_CONNECTION_STRING }}" \
+          /p:TargetPlatform=SqlServer2025 \
+          /p:BlockOnPossibleDataLoss=True \
+          /DiagnosticsFile:publish.log \
+          /DiagnosticsLevel:Verbose
+
+    - name: Upload Artifacts
+      if: always()
+      uses: actions/upload-artifact@v4
+      with:
+        name: deployment-logs
+        path: |
+          publish.log
+          deploy-report.xml
+```
+
+### Azure DevOps
+
+```yaml
+trigger:
+- main
+
+pool:
+  vmImage: 'windows-2022'
+
+steps:
+- task: MSBuild@1
+  displayName: 'Build Database Project'
+  inputs:
+    solution: 'Database.sqlproj'
+    configuration: 'Release'
+
+- task: SqlAzureDacpacDeployment@1
+  displayName: 'Deploy to SQL Server 2025'
+  inputs:
+    azureSubscription: 'Azure Subscription'
+    authenticationType: 'servicePrincipal'
+    serverName: 'server2025.database.windows.net'
+    databaseName: 'MyDatabase'
+    deployType: 'DacpacTask'
+    deploymentAction: 'Publish'
+    dacpacFile: '$(Build.SourcesDirectory)/bin/Release/Database.dacpac'
+    additionalArguments: '/p:TargetPlatform=SqlServer2025'
+```
+
+## New SqlPackage Diagnostic Features
+
+```bash
+# Enable detailed diagnostics
+sqlpackage /Action:Publish \
+  /SourceFile:Database.dacpac \
+  /TargetServerName:server2025.database.windows.net \
+  /TargetDatabaseName:MyDatabase \
+  /DiagnosticsLevel:Verbose \
+  /DiagnosticPackageFile:diagnostics.zip
+
+# Creates diagnostics.zip containing:
+# - Deployment logs
+# - Performance metrics
+# - Error details
+# - Schema comparison results
+```
+
+## Microsoft Fabric Data Warehouse Support
+
+**New in SqlPackage 162.5+:** Full support for SQL database in Microsoft Fabric.
+
+**Fabric Deployment:**
+```bash
+# Deploy to Fabric Warehouse
+sqlpackage /Action:Publish \
+  /SourceFile:Warehouse.dacpac \
+  /TargetConnectionString:"Server=tcp:myworkspace.datawarehouse.fabric.microsoft.com;Database=mywarehouse;Authentication=ActiveDirectoryInteractive;" \
+  /p:DatabaseEdition=Fabric \
+  /p:DatabaseServiceObjective=SqlDbFabricDatabaseSchemaProvider
+
+# Extract from Fabric
+sqlpackage /Action:Extract \
+  /SourceConnectionString:"Server=tcp:myworkspace.datawarehouse.fabric.microsoft.com;Database=mywarehouse;Authentication=ActiveDirectoryInteractive;" \
+  /TargetFile:Fabric.dacpac
+
+# New permission: ALTER ANY EXTERNAL MIRROR (Fabric-specific)
+GRANT ALTER ANY EXTERNAL MIRROR TO [FabricAdmin];
+```
+
+## Best Practices for SQL Server 2025
+
+1. **Use Target Platform Specification:**
+```xml
+<PropertyGroup>
+  <TargetPlatform>SqlServer2025</TargetPlatform>
+</PropertyGroup>
+```
+
+2. **Test Vector Operations:**
+```sql
+-- Verify vector support
+SELECT SERVERPROPERTY('IsVectorSupported') AS VectorSupport;
+```
+
+3. **Monitor AI Model Performance:**
+```sql
+-- Track model execution
+SELECT
+    model_name,
+    AVG(execution_time_ms) AS AvgExecutionTime,
+    COUNT(*) AS ExecutionCount
+FROM sys.dm_exec_external_model_stats
+GROUP BY model_name;
+```
+
+4. **Implement Sensitivity Classification:**
+```sql
+-- Classify all PII columns
+ADD SENSITIVITY CLASSIFICATION TO dbo.Customers.Email
+WITH (LABEL = 'Confidential - GDPR', INFORMATION_TYPE = 'Email');
+```
+
+## Resources
+
+- [SQL Server 2025 Preview](https://aka.ms/sqlserver2025)
+- [SqlPackage Documentation](https://learn.microsoft.com/sql/tools/sqlpackage/)
+- [SDK-Style Projects](https://learn.microsoft.com/sql/tools/sql-database-projects/concepts/sdk-style-projects)
+- [Vector Database](https://learn.microsoft.com/sql/relational-databases/vectors/)