Skip to content

Module 8: Search Explorer & Portal Tools

Overview

The Azure portal provides powerful tools for working with Azure AI Search, including Search Explorer for testing queries, Import Data wizard for automated indexing, and various management interfaces. This module covers how to effectively use these portal tools for development, testing, and troubleshooting.

Learning Objectives

By the end of this module, you will be able to:

  • Navigate the Azure AI Search portal interface effectively
  • Use Search Explorer to test and debug queries
  • Utilize the Import Data wizard for rapid prototyping
  • Monitor indexer execution and performance
  • Debug search queries and analyze results
  • Manage indexes, indexers, and data sources through the portal
  • Understand portal limitations and when to use APIs instead

Key Concepts

Search Explorer

Interactive query testing tool that allows you to: - Test search queries without writing code - Experiment with different query parameters - Analyze search results and scoring - Debug query syntax and filters - Export queries for use in applications

Import Data Wizard

Automated tool for creating complete search solutions: - Creates data sources, indexes, and indexers - Supports multiple data source types - Provides AI enrichment capabilities - Generates working configurations - Enables rapid prototyping

Portal Management Features

  • Service overview and monitoring
  • Index management and statistics
  • Indexer execution monitoring
  • Data source configuration
  • API key management
  • Usage and quota monitoring

Prerequisites

Before starting this module, ensure you have: - Completed Module 1 (Introduction & Setup) - Access to Azure portal with appropriate permissions - Azure AI Search service deployed - Basic understanding of search concepts from previous modules - Sample data available for testing

Module Structure

This module is organized into the following sections:

  1. Prerequisites - Required setup and access
  2. Best Practices - Guidelines for effective portal usage
  3. Practice & Implementation - Hands-on exercises with portal tools
  4. Troubleshooting - Common issues and solutions
  5. Code Samples - Automating portal workflows with APIs

What You'll Build

Throughout this module, you'll learn to: - Navigate and use all major portal features - Create complete search solutions using wizards - Test and debug queries interactively - Monitor and troubleshoot indexer operations - Export configurations for programmatic use

Search Explorer Features

Query Testing Interface

  • Simple Search: Basic text search with default parameters
  • Advanced Search: Full control over query parameters
  • Query Syntax: Support for simple and full Lucene syntax
  • Filter Testing: Interactive filter expression testing
  • Result Analysis: Detailed result inspection and scoring

Supported Parameters

  • search: Search text and expressions
  • searchMode: Any or All search mode
  • queryType: Simple or Full Lucene syntax
  • searchFields: Fields to search in
  • select: Fields to return
  • filter: OData filter expressions
  • orderby: Sort expressions
  • top: Number of results to return
  • skip: Number of results to skip
  • count: Include total result count
  • highlight: Hit highlighting configuration
  • facet: Faceting configuration

Query Examples in Search Explorer

Basic Text Search

Search: luxury hotel
Query Type: Simple
Search Mode: Any

Advanced Filtering

Search: *
Filter: Rating gt 4.0 and Category eq 'Luxury'
Order By: Rating desc
Top: 10

Search: spa
Facets: Category,Rating,Location/City
Select: HotelName,Rating,Category

Import Data Wizard

Supported Data Sources

  • Azure SQL Database
  • Azure Cosmos DB
  • Azure Blob Storage
  • Azure Table Storage
  • Azure Data Lake Storage Gen2

Wizard Steps

  1. Connect to Data: Configure data source connection
  2. Add Cognitive Skills: Optional AI enrichment
  3. Customize Target Index: Define index schema
  4. Create Indexer: Configure indexer settings

AI Enrichment Options

  • Text extraction from images (OCR)
  • Key phrase extraction
  • Language detection
  • Entity recognition
  • Sentiment analysis
  • Text translation
  • Custom skills integration

Generated Artifacts

  • Data source connection
  • Search index with optimized schema
  • Indexer with field mappings
  • Skillset (if AI enrichment is used)

Portal Management Features

Service Overview

  • Service health and status
  • Usage statistics and quotas
  • Performance metrics
  • Recent activity logs
  • Quick access to common tasks

Index Management

  • Index list and statistics
  • Field definitions and attributes
  • Index size and document count
  • Index operations (rebuild, delete)
  • Schema modification capabilities

Indexer Monitoring

  • Indexer execution history
  • Success/failure statistics
  • Error details and warnings
  • Performance metrics
  • Manual execution controls

Data Source Management

  • Connection string configuration
  • Connection testing
  • Change detection policies
  • Security and authentication settings

Best Practices for Portal Usage

Development Workflow

  1. Prototyping: Use Import Data wizard for initial setup
  2. Testing: Use Search Explorer for query development
  3. Monitoring: Use portal for operational oversight
  4. Production: Transition to API-based management

Query Development

  1. Start with simple queries in Search Explorer
  2. Gradually add complexity (filters, facets, sorting)
  3. Test edge cases and error conditions
  4. Export working queries for application use
  5. Validate performance with realistic data volumes

Troubleshooting Approach

  1. Use portal monitoring to identify issues
  2. Test queries in Search Explorer to isolate problems
  3. Review indexer execution history for data issues
  4. Check service health and quotas
  5. Use diagnostic logs for detailed analysis

Portal Limitations

When to Use APIs Instead

  • Automation: Repetitive tasks and CI/CD pipelines
  • Complex Operations: Advanced configurations not supported in portal
  • Performance: High-frequency operations
  • Integration: Embedding in applications
  • Customization: Advanced field mappings and transformations

Portal Constraints

  • Limited batch operations
  • Simplified configuration options
  • No version control integration
  • Limited automation capabilities
  • Reduced programmatic control

Monitoring and Diagnostics

Key Metrics to Monitor

  • Search Latency: Query response times
  • Search QPS: Queries per second
  • Indexing Rate: Documents processed per second
  • Storage Usage: Index size and growth
  • Error Rates: Failed queries and indexing operations

Diagnostic Tools

  • Activity Log: Service-level operations
  • Metrics: Performance and usage statistics
  • Diagnostic Settings: Detailed logging configuration
  • Alerts: Proactive monitoring and notifications

Performance Analysis

  • Query performance trends
  • Indexer execution patterns
  • Resource utilization monitoring
  • Capacity planning insights

Integration with Development Workflow

Exporting Configurations

  • Copy index definitions for code
  • Export indexer configurations
  • Generate API calls from portal actions
  • Document working configurations

Testing Strategies

  • Use portal for initial query development
  • Validate configurations before API implementation
  • Test data source connections
  • Verify field mappings and transformations

Collaboration

  • Share Search Explorer URLs for query examples
  • Document portal-based troubleshooting steps
  • Use portal for stakeholder demonstrations
  • Provide access for non-technical team members

Next Steps

After completing this module, you'll be ready to: - Effectively use all Azure AI Search portal tools - Transition from portal-based to API-based development - Move on to intermediate modules for advanced features - Implement production-ready search solutions

Additional Resources