Technical Deep Dives

The Most Important Developer Productivity Metric

January 14, 2025

The Most Important Developer Productivity Metric

At Honeycomb, we believe in ensuring an awesome developer experience for our own engineering teams; it’s the only way that we can compete with companies that have way more engineers than we do. We’ve historically tried to keep our build times under 15 minutes, taking percussive action when build times got over 15 minutes.

Software Engineering

Technical Deep Dives

Observable Frontends: the State of OpenTelemetry in the Browser

April 27, 2023

Jessica Kerr

Observable Frontends: the State of OpenTelemetry in the Browser

The modern standard for observability in backend systems is: distributed traces with OpenTelemetry, plus dynamic aggregations over these events. This works very well in the world of web servers. But what about the web client?

Observability

Technical Deep Dives

Achieving Great Dynamic Sampling with Refinery

April 18, 2023

Irving Popovetsky

Achieving Great Dynamic Sampling with Refinery

Refinery, Honeycomb’s tail-based dynamic sampling proxy, often makes sampling feel like magic. This applies especially to dynamic sampling, because it ensures that interesting and unique traffic is kept, while tossing out nearly-identical “boring” traffic. But like any sufficiently advanced technology, it can feel a bit counterintuitive to wield correctly, at first.

Sampling

Technical Deep Dives

November 18, 2022

Nathan Lincoln

Scaling Ingest With Ingest Telemetry

With the introduction of Environments & Services, we’ve seen a dramatic increase in the creation of new datasets. These new datasets are smaller than ones created with Honeycomb Classic, where customers would typically place all of their services under a single, large dataset. This change has presented some interesting scaling challenges, which I’ll detail in this post, along with the solution we used, and how we leveraged Honeycomb’s own telemetry to scale Honeycomb.

Dogfooding

Technical Deep Dives

January 11, 2022

Mike Goldsmith

What Is Auto-Instrumentation?

In the past, we’ve written about what instrumentation is and the insights it provides. Instrumenting your code generates telemetry that shows you how your system is performing, and whether your system is healthy. Like…

Instrumentation

Technical Deep Dives

November 30, 2021

Liz Fong-Jones

Scaling Kafka at Honeycomb

When you send telemetry into Honeycomb, our infrastructure needs to buffer your data before processing it in our “retriever” columnar storage database. For the entirety of Honeycomb’s existence, we have used Apache Kafka to…

Technical Deep Dives

October 12, 2021

Alex Vondrak

How Time Series Databases Work—and Where They Don’t

In my previous post, we explored why Honeycomb is implemented as a distributed column store. Just as interesting to consider, though, is why Honeycomb is not implemented in other ways. So in this post, we’re going to dive into the topic of time series databases (TSDBs) and why Honeycomb couldn’t be limited to a TSDB implementation.

Databases

Observability

Technical Deep Dives