I’m excited to share that I’ve published a practical article on Medium demonstrating how to solve reporting performance challenges using Elasticsearch Transforms combined with the newly announced ES|QL (Elasticsearch Query Language) from ELK 8.14.

The Challenge: Slow and Cumbersome Reporting

The article addresses a real-world problem I encountered while working with a client whose reporting system was struggling with performance issues as data volumes increased. Generating reports had become a bottleneck, preventing timely business decisions and creating maintenance headaches for the development team.

The Solution: Elastic Transforms + ES|QL

I demonstrate how combining these two powerful Elasticsearch features can dramatically improve reporting performance while making queries more intuitive and maintainable.

Why Traditional Approaches Fall Short

The article explores why directly querying large indices with KQL (Kibana Query Language) creates problems:

• Complex and hard-to-maintain queries
• Nested JSON responses requiring additional server-side processing
• Performance degradation as data moves to cold storage or indices grow large

A Better Approach

Instead, I show how to:

1. Define transforms that continuously aggregate data from source indices
2. Create optimized reporting indices with pre-calculated metrics
3. Use ES|QL to query transformed data with SQL-like syntax

Read the Complete Guide

Check out the full article with detailed implementation steps: Create BLAZING fast reports with Elastic Transforms and ES|QL

This article represents the practical application of advanced Elasticsearch features to solve real business problems - something I’m passionate about as both a former Elastic team member and current consultant helping organizations optimize their search and analytics infrastructure.