Search & Analytics

Elasticsearch Search Engine Development Elasticsearch Setup and Configuration Basic Cluster Configuration Production Configuration Index Design and Mapping Document Mapping Strategy Search Client Implementation TypeScript Client Setup Advanced Search Queries Multi-Field Search with Boosting Auto-Complete and Suggestions Completion Suggester Implementation Performance Optimization Query Optimization Strategies Analytics and Monitoring Search Analytics Implementation Real-time Indexing Pipeline Event-Driven Indexing Testing Strategy Comprehensive Test Suite Production Deployment Docker and Kubernetes Deployment Implementation Checklist [ ] Set up Elasticsearch cluster with proper configuration [ ] Design index mappings for your data structure [ ] Implement search service with TypeScript client [ ] Create advanced search queries with filters and aggregations [ ] Build auto-complete and suggestion features [ ] Optimize query performance and indexing strategies [ ] Implement search analytics and monitoring [ ] Set up real-time indexing pipeline [ ] Write comprehensive tests for search functionality [ ] Deploy to production with monitoring and alerting [ ] Configure index lifecycle management [ ] Implement security and access controls This guide provides a production-ready foundation for building sophisticated search engines with Elasticsearch, covering everything from basic setup to advanced features and deployment strategies.

MongoDB Database Design and Optimization Schema Design Patterns Document Structure Design Referenced vs Embedded Data Indexing Strategies Compound Index Design Index Performance Analysis Aggregation Pipeline Optimization Complex Aggregation Patterns Performance Optimization Techniques Data Modeling Patterns Polymorphic Pattern Bucket Pattern for Time Series Transaction Management Multi-Document Transactions Performance Monitoring and Optimization Database Profiling and Monitoring Query Optimization Strategies Data Validation and Schema Enforcement JSON Schema Validation Data Migration and Versioning Schema Migration Patterns Backup and Recovery Strategies Automated Backup Solutions Point-in-Time Recovery Security Best Practices Authentication and Authorization Implementation Checklist [ ] Design document schema based on access patterns [ ] Choose between embedding and referencing appropriately [ ] Create compound indexes for common query patterns [ ] Implement text search indexes for full-text search [ ] Set up geospatial indexes for location-based queries [ ] Use aggregation pipelines for complex data analysis [ ] Implement proper error handling and transactions [ ] Set up database validation rules [ ] Configure monitoring and profiling [ ] Implement automated backup strategy [ ] Set up proper authentication and authorization [ ] Plan for data migration and schema evolution [ ] Optimize queries based on explain plans [ ] Monitor collection and index statistics This comprehensive guide provides the foundation for building scalable, performant MongoDB applications with proper schema design, indexing strategies, and operational best practices.

Redis Caching Strategies and Implementation Redis Setup and Configuration Basic Redis Configuration Docker Compose Setup Cache Client Implementation TypeScript Redis Client Cache-Aside Pattern Implementation Repository with Caching Layer Write-Through and Write-Behind Patterns Write-Through Cache Implementation Write-Behind Cache with Queue Advanced Caching Patterns Multi-Level Cache Implementation Cache Warming Strategy Redis Data Structures for Caching Advanced Data Structure Usage Cache Monitoring and Metrics Performance Monitoring Testing Cache Implementation Comprehensive Test Suite Production Optimization Memory and Performance Tuning Deployment and Scaling Redis Cluster Configuration Implementation Checklist [ ] Set up Redis server with production configuration [ ] Implement cache service with proper error handling [ ] Choose appropriate caching patterns (cache-aside, write-through, etc.) [ ] Design cache key naming strategy [ ] Implement cache warming for critical data [ ] Set up multi-level caching if needed [ ] Use Redis data structures for advanced use cases [ ] Implement cache monitoring and metrics [ ] Write comprehensive tests for cache functionality [ ] Configure Redis cluster for high availability [ ] Set up cache invalidation strategies [ ] Monitor cache hit ratios and performance metrics This guide provides a comprehensive foundation for implementing Redis caching strategies that can significantly improve application performance and scalability while maintaining data consistency and reliability.