honeycomb.io

Honeycomb has always been about teams. 🐝 From day one, we’ve believed that strong teams are built when a group of people with different roles, instincts, and expertise can get to a shared understanding of what’s happening around them. (That belief is rooted in the delta between me and Charity: two very different engineers, trying to make sense of the same messy system.) The agentic era changes who’s on the team, but to me it’s another variation on the same theme. Everyone has their own agent these days (and should!)—and that raises a fun set of questions about how all the pieces fit together: how humans and agents with different views of the world and different expertise collaborate, hand work off, and pass along what they’ve learned... while staying grounded in the same view of what’s real. Back in the early days, my LinkedIn bio described Honeycomb as “the next best member of your team.” I still think about it that way... there are just a lot more teammates in the picture now. Charity and I are digging into all of this Nov 3–4, and we’ll be announcing some very cool stuff along the way ✨ Day 1: Agents on your team. Instrumentation, context, and building trust in what your agents are doing. Day 2: The AI ecosystem at scale. Visibility across the whole fleet, keeping costs in check, and what platform teams need to observe all of it. There’s a live Q&A, so bring your questions (or your "well, actually"s). Join us! https://go.hny.co/4dsMocn

Align engineering priorities with what matters to the business. Explore modern SLI and SLO practices, delivery feedback loops, and ways to assess the value of observability investment. Sign up once for the Observability Engineering Masterclass with Liz Fong-Jones to watch all six sessions on demand.

Move beyond reactive troubleshooting. Learn how to approach SLOs, reliability, and production debugging with insights from Liz Fong-Jones, Honeycomb Technical Fellow and an SRE with over 20 years of experience. Get the second edition free.

More dashboards won't solve growing debugging complexity. Explore wide events, OpenTelemetry, and observability-driven development in the second edition of the book that helped shape modern observability. Get your free copy today.

Trustworthy AI requires more than accurate outputs. Teams need visibility into how decisions happen and the ability to trace results back to their source. Explore how telemetry and provenance can support more explainable AI systems in Chapter 17 of Observability Engineering.

Are rising APM costs and fragmented tooling making observability harder to manage? Explore sampling strategies, telemetry pipelines, and build-versus-buy decisions in this updated guide from Honeycomb CTO Charity Majors and fellow observability experts. Download your complimentary copy.