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By Dormain Drewitz
I used to joke that I got my best parenting ideas from management books, and my best management ideas from parenting books. Now, I'm extending it to agents. Hear me out. When you're teaching a teen how to drive, you don't hand them the car keys on day one. You start in an empty parking lot. You ride along and ask them to talk through what they're doing.
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By Dan Juengst
The best alert is the one that never fires. Picture an idyllic Tuesday afternoon: last night's release nudged checkout p99 up 41%, but an agent noticed. Nobody got paged, and your SLOs didn't start burning. Instead, the agent acted and already narrowed it down to one retry change. It filed a ticket for the Payments team and flagged the PR. By the time anyone would have noticed, the fix is in review. That's what SRE was always supposed to feel like.
Yesterday, my partner told me about his new automated pipeline from a conversation recording to publication of a whole podcast, with social media blurbs and graphics and everything. It did more than he'd predicted the agent could do. "We are limited by what we can imagine," he said. Cheesy, but it kinda gave me goosebumps because it's (almost) true. Most of the experienced developers I know are concerned.
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By Ken Rimple
We just wrapped O11yDay London, and one theme ran through every session: writing code is no longer the hard part. Review queues, attention, operating agents in production, runaway token bills, and proving any of it is worth the money are where teams are getting stuck. The teams making progress are the ones who can see what's happening in production. Here are some highlights. We'll have videos available in the near future.
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By Jack Grisanti
We're excited to share that Honeycomb has achieved yet another Amazon Web Services (AWS) Competency—the Resilience Technology Competency—which recognizes our ability to help customers detect, investigate, and recover from failures in production systems running on AWS. While receiving the competency designation is a fantastic recognition of the capabilities of the Honeycomb platform (we also received one in Financial Services earlier this year), it's ultimately not the point.
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By Mike Goldsmith
Your LLM application emits telemetry unlike anything else in your stack. Model calls, tool invocations, retrieval steps, and token usage arrive as spans whose attributes carry entire prompts and completions. That data is bulky, it's full of user content you may not be allowed to export, and depending on which instrumentation each service uses, the same fact can arrive under different attribute names.
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By Fred Hebert
Back in July, I wrote about how the Tenant team (the team behind Honeycomb Private Cloud (HPC)) has embraced the code review bottleneck to focus more of its work. One of the other challenges we have is that we're downstream of almost all the other teams at Honeycomb, meaning that we have to package up everyone's code and services, and how it gets provisioned! This is something impossible to handle through code review since there are so many engineers on other teams, and so few of us.
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By Rox Williams
What happens when a software engineer who has put their entire identity into being the resident expert of an obscure technology or language with ten years of experience and who knows the codebase like the back of their hand now has to compete with AI? Psychologically speaking, according to Dr. Cat Hicks, author of The Psychology of Software Teams and founder of Catharsis, that's called identity threat, and it's a surefire way to feel unsafe. We were honored Dr.
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By Dan Juengst
Earlier this year, we introduced more capabilities to support agents in production, a more chaotic, complex environment that requires a tremendous amount of context to understand. Unlike tools that capture shallow, pre-aggregated metrics, or cannot join a metric, trace, and log in one query, Honeycomb retains the context and connective tissue from telemetry data to build a nuanced view of production.
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By Dan Juengst
A few months ago, we launched Agent Timeline to close the gap between knowing an agent failed and understanding why. It took the tangled reality of a multi-agent, multi-trace workflow and rendered it as a single, readable conversation: every LLM call, tool invocation, handoff, and downstream system span laid out in the order they happened.
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By Honeycomb
Watch all sessions from Day 2 of Honeycomb's Innovation Week in November 2026. Includes keynote from Graham Siener, a demo of Team Agents with Jessitron and MartinDotNet, Ben's talk on Agent Fleets, a demo of AI Ecosystem from Ken Rimple, and a chat between Christine and Daniel Worku of StarSling.
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By Honeycomb
Welcome to the Honeycomb Changelog B-Sides, Vol. 1, Fall 2026 Hear about important new features that didn't get fanfare!
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By Honeycomb
Watch all sessions from Day 1 of Honeycomb's Innovation Week in November 2026. Includes keynote from Christine Yen, Dormain's panel with RedMonk, AWS, and Checkly, Q&A with Charity Majors, a Team Agents demo with Jessitron and MartinDotNet, and a customer spotlight featuring Robert Goldsmith from Cruise.co.uk.
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By Honeycomb
Honeycomb AI Ecosystem shows you the performance and cost of every AI agent in one live view and drills straight to the conversation behind any number, so you can diagnose your whole fleet in minutes without switching tools or rebuilding a single query.
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By Honeycomb
Watch a 2-minute demo video of Honeycomb Anomaly Detection, part of the Honeycomb Intelligence suite.
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By Honeycomb
A few months ago, Darragh Curran, CTO at Fin (formerly Intercom) set a public goal to double productivity and nearly tripled it instead. They did so by pulling a few levers: AI writing code at scale, building an AI-driven PR review system, leveraging as a trust mechanism, and with leadership becoming more hands-on through the transition. Charity wanted to pick Darragh’s brain on the messy bits, not just the highlight reel, so she invited him to participate in our first episode of Leading With Observability.
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By Honeycomb
It started with a single log line taking up a massive amount of volume: 500 million emissions per hour. Pulling that thread led Emma and Steven into Slack's broader logging pipeline: 311 billion logs per day at 4.4M/sec peak, with no volume limits, no per-service attribution, and no feedback to the teams generating the noise.
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By Honeycomb
'The runbook lost. The trace is the documentation now.' In his O11yCon 2026 closing keynote, Corey Quinn of Duckbill Group makes the case that when your primary reader is an, not a person, are the only pillar built to survive.
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By Honeycomb
It started with a single log line taking up a massive amount of volume: 500 million emissions per hour. Pulling that thread led Emma and Steven into Slack's broader logging pipeline: 311 billion logs per day at 4.4M/sec peak, with no volume limits, no per-service attribution, and no feedback to the teams generating the noise.
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By Honeycomb
Stripe shares lessons from building an incident investigation agent, from context-window blowups to why the final 5% still needs a human. In this O11yCon 2026 talk, they dig into what it takes to go from 'it works' to 'it works reliably,' including how pointing agents at like Honeycomb's speeds up on-call investigations.
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By Honeycomb
Honeycomb is an event-based observability tool, but you can-and should-use metrics alongside your events. Fortunately, Honeycomb can analyze both types of data at the same time. When maturing from metrics-based application monitoring to an observability-based development practice, there are considerations that can make the transformation easier for you and your team.
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By Honeycomb
Evaluating observability tools can be a daunting task when you're unfamiliar with key considerations and possibilities. This guide steps through various capabilities for observability tooling and why they matter.
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By Honeycomb
This document discusses the history, concept, goals, and approaches to achieving observability in today's software industry, with an eye to the future benefits and potential evolution of the software development practice as a whole.
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Honeycomb is a tool for introspecting and interrogating your production systems. We can gather data from any source—from your clients (mobile, IoT, browsers), vendored software, or your own code. Single-node debugging tools miss crucial details in a world where infrastructure is dynamic and ephemeral. Honeycomb is a new type of tool, designed and evolved to meet the real needs of platforms, microservices, serverless apps, and complex systems.
Honeycomb provides full stack observability—designed for high cardinality data and collaborative problem solving, enabling engineers to deeply understand and debug production software together. Founded on the experience of debugging problems at the scale of millions of apps serving tens of millions of users, we empower every engineer to instrument and query the behavior of their system.