This article outlines how Honeycomb’s observability platform handles massive, distributed systems by shortening time-to-understanding, reducing alert fatigue with SLOs, and consolidating legacy tools. A Forrester TEI study reports a 296% ROI over three years, $2.68 M in incident-related savings, and a break-even point under six months.

Martin Kleppmann discusses his journey from startups to academia, and the new edition of his book Designing Data-Intensive Applications. They cover trade-offs in modern infrastructure, cloud scalability, distributed system challenges, and emerging topics like formal verification and local-first software.

In this Pragmatic Engineer episode, Martin Kleppmann walks through updates in the second edition of Designing Data-Intensive Applications and shares how his LinkedIn experience shaped the book’s core concepts. He breaks down trade-offs in multi-region and cloud architectures, explains why replication still matters more than sharding, and predicts a rise in formal verification and local-first software.