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.

In a previous blog post, we outlined how to set up our own auto-instrumentation to send Core Web Vitals data to Honeycomb. We recently released a beta version of an OpenTelemetry wrapper to send traces from the browser to Honeycomb.

There’s a sentence that strikes fear into the heart of every frontend developer I've ever met: Users are reporting issues, and we don't know how to replicate them. What do you do when that happens? Do you cry? Do you mark the issue as wontfix and move on? Personally, I took the road less traveled: gave up frontend engineering and moved into product management (this is not actually accurate but it's a good joke and it feels truthy). 

We thought it'd be fun to give you some insights into what certain teams at Honeycomb do and how they spend their days, and who else would we start this experiment with than our fabulous customer success team? Without further ado, meet four of our bees!

As a new company poised to transform the financial services industry with its modern money movement platform, Moov wanted an equally modern observability platform as part of the company’s operational tech stack. 

For years, we’ve been installing what vendors have referred to as “agents” that reach into our applications and pull out useful telemetry information from them. From monitoring agents, to full-blown APM tools, this has been the standard for many decades. With OpenTelemetry though, the term “agent” isn’t used as much, and in most scenarios means something slightly different. In this post, we’ll talk about the fact that you can achieve the same “hands off” process with OpenTelemetry, but also when you should and shouldn’t consider using the more automatic approach to telemetry collection. 

We're excited to unveil a new collaboration with Focused Labs, a leap forward in our shared commitment to advancing modern observability practices and enhancing the robustness of legacy systems. This partnership is not just about scaling our service offerings but also about integrating Focused Labs' deep engineering expertise with our observability platform to deliver unparalleled customer experiences.

Naming things, and specifically consistently naming things, is still one of the most useful pieces of work you can do in telemetry. It’s often overlooked as something that will just happen naturally and won’t cause too much of an issue—but it doesn’t happen naturally, it does cause issues, and you end up having to fix the data in pipelines or your backend tool.