Weekend Reading #70

Weekend Reading: A weekly roundup of interesting Software Architecture and Programming articles from tech companies. Find fresh ideas and insights every weekend.

This week: distributed deadlocks, AI-assisted coding interviews, Uber’s Apache Hudi data lake at scale, and LinkedIn’s AI-powered search stack redesign.

Deadlocks in Distributed Systems: Detection, Prevention, Recovery

👉 Useful if you’re designing or operating distributed workflows and want to avoid system stalls.

A clear guide to what deadlocks look like in distributed services, why they’re harder to spot than in single systems, and how conditions like circular wait keep systems stuck.  

How AI coding interviews work at Meta

👉 Good insight if you’re preparing for or designing interviews that use AI tooling.

The article reviews how AI-assisted interviews are conducted at Meta.

Apache Hudi at Uber: Engineering for Trillion-Record-Scale Data Lake Operations

👉 Great read if you’re tackling large data lakes and need stronger ingestion & update semantics.

Uber is unveiling its Apache Hudi (Hadoop Upserts, Deletes, and Incrementals) solution to manage large volumes of data and improve the efficiency of real-time data processing.

Reimagining LinkedIn’s search tech stack

👉 Worth reading if you’re building search systems or integrating ML for semantic results.

LinkedIn describes the redesign of its search infrastructure to support semantic and AI-enhanced search, boosting relevance with large language models while maintaining low latency.