InfoQ - AI, ML & Data Engineering - Articles

Article: When Should You Use Liquid Clustering? Benchmarking Lakehouse Layout Strategies

Kushal Kumar Vishwakarma — Mon, 12 Oct 2026 11:00:00 GMT

Physical data layout is one of the most consequential decisions in lakehouse engineering. The author compares Liquid Clustering, ZOrdering, and partitioning across four workload types on Delta Lake, uncovering two undocumented failure modes that likely affect production systems today and offering a decision framework for choosing the right layout strategy.

By Kushal Kumar Vishwakarma

Article: Building a Session-Ordered Kafka Pipeline in Go

Joshua Oluikpe — Wed, 07 Oct 2026 09:00:00 GMT

The article describes a custom implementation that provides a session-level ordering on top of Apache Kafka partitions, supporting strict message ordering across 1000s of independent channels. The solution required application-level routing, consistent hashing, retries, and contiguous watermark commits. Engineers conducted operational hardening supported by extensive performance testing.

By Joshua Oluikpe

Article: The Platform Engineering Playbook for Production LLMs

Aditya Mulik — Mon, 05 Oct 2026 11:00:00 GMT

In this article, author discusses his experience with AI agent hallucinations in an inventory recommendation system and how this problem was solved by treating the LLM stack as a platform infrastructure concern instead of as an application one. He makes a case for a shared LLM platform with common services like prompt registry & versioning, schema enforcement and token cost attribution by request.

By Aditya Mulik