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.

You're probably familiar with the concept of real user monitoring (RUM) and how it's used to monitor websites or mobile applications. If not, here's the short version: RUM requires telemetry data, which is generated by an SDK that you import into your web or mobile application. These SDKs then hook into the JS runtime, the browser itself, or various system APIs in order to measure performance. These SDKs are usually pretty optimized for both speed and size—you don't want the dependency that tells you how fast or slow your application is to impact your application speed, after all.

Relying on their traditional observability 1.0 tool, Pax8 faced hurdles in fostering a culture of ownership and curiosity due to user-based pricing limitations and an impending steep price increase.

This article touches on how we at Birdie handled our transition from logs towards using OpenTelemetry as the primary mechanism for achieving world-class observability of our systems.

Today at Google Next, Charity Majors demonstrated how to use Honeycomb to find unexpected problems in our generative AI integration. Software components that integrate with AI products like Google’s Gemini are powerful in their ability to surprise us. Nondeterministic behavior means there is no such thing as “fully tested.” Never has there been more of a need for testing in production!

A few days ago, I was in a meeting with a prospect who was just starting to try out OpenTelemetry. One of the things that they did was to create an observability demo project which contained an HTTP reverse proxy, a web frontend, three microservices, a database, and a message queue.