I’m absolutely thrilled to share that my tutorial on building hybrid search applications has been featured on the official OpenSearch blog! This is an incredible honor and recognition from the OpenSearch community.

A Major Milestone

Being featured on the official OpenSearch blog represents a significant milestone in my journey as a search technology expert. The OpenSearch project is used by thousands of organizations worldwide, and having my work showcased on their platform validates the practical value of the tutorial and my approach to vector search implementation.

What the Feature Covers

The blog post, titled “Recipes to vectors: Building a hybrid search app with OpenSearch”, presents the complete tutorial I originally developed for Big Data Boutique. The OpenSearch team recognized the educational value and practical applicability of the content, making it available to their broader developer community.

The tutorial demonstrates:

• Complete end-to-end implementation using real recipe data from Kaggle
• Practical embedding construction combining multiple fields for optimal semantic representation
• Index configuration with proper k-NN settings and vector field mappings
• Hands-on code examples available on GitHub
• Three search approaches: keyword search, semantic search, and hybrid search

The Power of Real-World Examples

What makes this tutorial particularly valuable is its use of actual recipe data - showing both structured fields (categories, cooking time) and unstructured content (ingredients, instructions). This demonstrates when to use traditional keyword search versus semantic search, and how to combine them effectively.

The tutorial includes practical examples like finding “Asian-inspired chicken recipes with noodles and peanuts” through semantic search, then filtering for specific categories using hybrid approaches.

Community Recognition

Having the OpenSearch team feature my work is especially meaningful given my background. As a former Elastic team member who now works extensively with both Elasticsearch and OpenSearch, I understand the importance of providing clear, practical guidance for developers building vector-powered applications.

The feature includes a dedicated author profile highlighting my work in search infrastructure, generative AI, and open source - positioning me as a trusted voice in the OpenSearch community.

Building on Previous Work

This recognition builds on the foundational vector search concepts and Elasticsearch implementations I’ve shared previously. It demonstrates how the same principles apply across different search platforms while highlighting OpenSearch-specific implementation details.

What This Means

Being featured on the official OpenSearch blog means:

• Community validation of my technical expertise and teaching approach
• Broader reach for practical vector search education
• Recognition as a contributor to the OpenSearch ecosystem
• Platform for sharing best practices with thousands of developers

Read the Featured Tutorial

Check out the complete tutorial on the official OpenSearch blog: Recipes to vectors: Building a hybrid search app with OpenSearch

I’m grateful to the OpenSearch team for this recognition and excited to continue contributing to the community’s understanding of vector search and hybrid retrieval systems. This feature reinforces my commitment to making advanced search technologies accessible and practical for developers worldwide.