Our storage engine, affectionately known as Retriever, has served us faithfully since the earliest days of Honeycomb. It’s a tool that writes data to disk and reads it back in a way that’s optimized for the time series-based queries our UI and API makes. Its architecture has remained mostly stable through some major shifts in the surrounding system it supports, notably including our 2021 implementation of a new data model for environments and services. As usage of this feature has grown, however, we’ve noticed Retriever creaking in novel ways, pushing us to reconsider a core architectural choice.

Earlier this year, Honeycomb announced the launch of data residency in Europe. To meet the growing needs of our customers in the region, we are delighted to announce new Honeycomb Support business hours.

Software is in a crisis. This is nothing new. Complex distributed systems are perpetually in a state far from equilibrium, operating in what Richard Cook has called a “degraded mode.” It’s through a combination of technical artifacts, organizational practices and policies, and pure gumption that they manage to maintain themselves through time.

Amperity required an observability partner to facilitate their transition into the modern engineering era as their previous tooling struggled to support their growth strategy.

In my February 2024 piece The Cost Crisis in Observability Tooling, I explained why the cost of tools built atop the three pillars of metrics, logs, and traces—observability 1.0 tooling—is not only soaring at a rate many times higher than your traffic increases, but has also become radically disconnected from the value those tools can deliver. Too often, as costs go up, the value you derive from these tools declines.

Over the past five years, software and systems have become increasingly complex and challenging for teams to understand. A challenging macroeconomic environment, the rise of generative AI, and further advancements in cloud computing compound the problems faced by many organizations. Simply understanding what’s broken is difficult enough, but trying to do so while balancing the need to constantly innovate and ship makes the problem worse. Your end users have options, and if your software systems are unreliable, they’ll choose a different one.

Recently, Honeycomb released a Web Instrumentation package built around the OpenTelemetry browser JS packages. In this post, I’ll go over what the OpenTelemetry auto-instrumentation package gives you, and what Honeycomb’s distribution adds in order to give you even more insight into your web services. 

We recently introduced relational fields, a new feature that allows you to query spans based on their relationship to each other within a trace. This post identifies use cases that were previously impossible (or extremely difficult!) without these relational fields.

Fender faced challenges with log analysis, finding it slow and complex to navigate, leading to inefficient troubleshooting and a need for a more user-friendly and advanced observability solution.

Honeycomb for Frontend Observability gives frontend developers the ability to quickly identify opportunities for optimization within their web app. This starts with better OpenTelemetry instrumentation, available as an NPM package, that lets you instrument and collect attribution data on Core Web Vitals in under an hour.

The 1981 book Simulacra and Simulation by Jean Baudrillard is widely read and cited within academic circles but also permeates popular culture, influencing films, literature, and art. His theories notably influenced the Wachowski siblings' The Matrix series, bringing some of his ideas into mainstream awareness.

Expanded fields allow you to more easily find interesting traces and learn about the spans within them, saving time for debugging and enabling more curiosity within your team around how transactions perform throughout your services.