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Search Services - Overview and Management

Key Components: Elasticsearch • Full-Text Search • Analytics Engine • Document Storage • Real-Time Search

File: docs/package-search-readme.md Purpose: Overview of search services available in Urbalurba infrastructure Target Audience: Developers, architects, and operations teams implementing search functionality Last Updated: September 23, 2025

📋 Overview​

The Search Services package provides powerful search and analytics capabilities for applications requiring advanced text search, real-time analytics, and document storage. These services enable full-text search, data exploration, log analysis, and complex aggregations across your applications.

Available Services:

  • Elasticsearch: Primary search and analytics engine with RESTful API
  • Future Services: Potential integration with OpenSearch, Solr, or specialized search solutions

🏗️ Architecture​

Service Categories​

Search Services Stack:
├── 04-search/
│   ├── not-in-use/
│   │   ├── 07-setup-elasticsearch.sh    # Elasticsearch deployment
│   │   └── 07-remove-elasticsearch.sh   # Elasticsearch removal
│   └── (Future search services)
├── manifests/
│   └── 060-elasticsearch-config.yaml    # Elasticsearch configuration
└── ansible/playbooks/
    ├── 060-setup-elasticsearch.yml      # Elasticsearch deployment logic
    └── 060-remove-elasticsearch.yml     # Elasticsearch removal logic

Service Integration​

Application Layer
├── Search API (Full-text search)
├── Analytics Dashboard (Real-time metrics)
├── Log Aggregation (Centralized logging)
└── Data Exploration (Interactive queries)
    ↓
Search Layer
├── Elasticsearch (8.16.1)
│   ├── Full-text search engine
│   ├── Real-time analytics
│   ├── Document storage
│   └── RESTful API
└── (Future: OpenSearch, Solr)
    ↓
Storage Layer
├── Persistent Volumes (Document storage)
├── Index Storage (Optimized for search)
└── Backup Storage (Snapshots)

🚀 Available Services​

Elasticsearch - Search & Analytics Engine 🔍​

Status: Available (not-in-use) | Port: 9200 | Type: Search Engine

Key Capabilities: Full-Text Search • Real-Time Analytics • Document Storage • RESTful API • Query DSL • Aggregations • Log Analysis

Elasticsearch provides comprehensive search and analytics capabilities for applications requiring advanced text search, real-time data exploration, and document storage. Essential for implementing search functionality, log aggregation, and analytics dashboards.

Key Features:

  • Search Engine: Advanced full-text search with relevance scoring
  • Analytics Platform: Real-time aggregations and data analysis
  • Document Store: JSON document storage with automatic indexing
  • RESTful API: HTTP-based API for all operations
  • Security: Centralized authentication via urbalurba-secrets

📚 Complete Documentation →

🔄 Service Selection Guide​

When to Use Elasticsearch​

✅ Choose Elasticsearch for:

  • Full-text search requirements: Product catalogs, content management, documentation search
  • Real-time analytics: Dashboards, metrics, business intelligence
  • Log aggregation: Centralized logging from multiple services
  • Complex data exploration: Interactive queries, faceted search
  • High-volume data: Large datasets requiring fast search and aggregation
  • RESTful integration: Applications preferring HTTP API access

❌ Consider alternatives when:

  • Simple key-value lookup: Use Redis or database indices instead
  • Very small datasets: Database LIKE queries may be sufficient
  • Real-time requirements: Sub-millisecond latency needs (use Redis)
  • Memory constraints: Elasticsearch requires significant RAM for optimal performance

Search Service Decision Matrix​

Use CaseVolumeComplexityReal-TimeRecommended Service
Product SearchHighHighModerateElasticsearch
Content SearchMediumHighLowElasticsearch
Log AnalysisHighMediumLowElasticsearch
Analytics DashboardHighHighHighElasticsearch
Simple SearchLowLowHighDatabase + Redis
AutocompleteMediumLowHighElasticsearch + Redis
Document StorageHighMediumLowElasticsearch
Geospatial SearchMediumHighModerateElasticsearch

🛠️ Common Operations​

Service Management​

# Check search services
kubectl get pods -l app.kubernetes.io/name=elasticsearch

# Monitor service logs
kubectl logs -l app.kubernetes.io/name=elasticsearch -f

# Check service status
kubectl get svc elasticsearch

Quick Health Check​

# Elasticsearch health
kubectl exec -it elasticsearch-0 -- curl -u "elastic:password" -s \
  "http://localhost:9200/_cluster/health"

# Resource usage
kubectl top pod elasticsearch-0

Deploy/Remove Services​

# Deploy Elasticsearch
cd provision-host/kubernetes/04-search/not-in-use/
./07-setup-elasticsearch.sh rancher-desktop

# Remove Elasticsearch
./07-remove-elasticsearch.sh rancher-desktop

🔧 Troubleshooting​

Common Issues​

  • Pod Won't Start: Check pod events, logs, and Java heap settings
  • Search Performance: Monitor cluster stats, heap usage, and query performance
  • Authentication Failed: Verify urbalurba-secrets configuration
  • Index Issues: Check index health, shard allocation, and cluster status

Quick Diagnostics​

# Check pod status
kubectl describe pod elasticsearch-0
kubectl logs elasticsearch-0

# Verify credentials
kubectl get secret urbalurba-secrets -o jsonpath="{.data.ELASTICSEARCH_PASSWORD}" | base64 -d

# Test connectivity
kubectl exec -it elasticsearch-0 -- curl -u "elastic:password" \
  "http://localhost:9200/_cluster/health"

📋 Service Documentation​

Detailed Service Guides​

  • Elasticsearch: Complete deployment, configuration, and management guide
  • Future Services: Documentation will be added as new search services are integrated

🚀 Integration Examples​

Common Integration Patterns​

  • Full-Text Search: Product catalogs, documentation search, content discovery
  • Log Aggregation: Centralized logging from multiple services
  • Analytics Dashboards: Real-time metrics and business intelligence
  • Monitoring: Application performance and system health tracking

See detailed implementation examples in Elasticsearch Documentation

💡 Key Insight: Search services are essential for modern applications requiring advanced data discovery, real-time analytics, and full-text search capabilities. Choose Elasticsearch for comprehensive search and analytics needs, and consider complementary services like Redis for high-speed caching and simple lookups to create a complete search architecture.