It may surprise you to hear, but Honeycomb doesn’t currently have a platform team. We have a platform org, and my title is Director of Platform Engineering. We have engineers doing platform work. And, we even have an SRE team and a core services team. But a platform team? Nope. I’ve been thinking about what it might mean to build a platform team up from scratch—a situation some of you may also be in—and it led me to asking crucial questions. What should such a team own?

Written by Liz Fong-Jones and Phillip Carter. OpenTelemetry, also known as OTel, is a CNCF open standard that enables distributed tracing and metrics collection from your applications. At Honeycomb, we believe that OpenTelemetry is the best way to ingest the high-cardinality and high-dimensional data that every system, no matter how complex or distributed, needs for observability.

As long as humans have written software, we’ve needed to understand why our expectations (the logic we thought we wrote) don’t match reality (the logic being executed). To that end, we developed techniques to help measure reality—logging text strings, or capturing aggregated metrics—and persevered, seeking out newer and fancier logging or monitoring solutions over the intervening decades.

Today, we're announcing the launch of Honeycomb Service Map. This isn't your grandparent's version of a service map. This feature reimagines what it is that you want to know or investigate when looking at visualizations of how your services communicate with one another.

If you build or maintain code in GitHub, the Honeycomb Buildevents Action can help you optimize the performance of your build pipelines in GitHub Actions. This blog introduces you to the gha-buildevents Action and a new hands-on quickstart guide that will show you the inner workings of GitHub Actions workflows, the buildevents tool, and the Honeycomb UI.

Getting existing telemetry into Honeycomb just got easier! With the release of the Datadog APM Receiver, you can send your Datadog traces to the OpenTelemetry Collector, and from there, to any OpenTelemetry-compatible endpoint. Often, evaluating a new tracing solution requires re-instrumenting your applications from the ground up in a new vendor’s tooling. It’s a pretty high bar to clear just to see if a solution is worth adopting.

Network topology can get very complicated in the cloud, especially when you’re sending data to external SaaS providers. You will likely need to configure gateways and firewalls and keep close tabs on those points of egress. However, if your infrastructure exists within AWS, there’s a much simpler way and that’s through an AWS PrivateLink endpoint.

When you want to direct your observability data in a uniform fashion, you want to run an OpenTelemetry collector. If you have a Kubernetes cluster handy, that’s a useful place to run it. Helm is a quick way to get it running in Kubernetes; it encapsulates all the YAML object definitions that you need. OpenTelemetry publishes a Helm chart for the collector. When you install the OpenTelemetry collector with Helm, you’ll give it some configuration.

Today, I’d like to share with you a new community-contributed integration that helps you optimize and debug your Gradle builds. This new Gradle plugin is available today, is free to use, and you can use it immediately with a free Honeycomb account.

Just a few short months ago, we talked about a bunch of updates to Honeycomb’s support for OpenTelemetry. To the surprise of no one, we’ve got more updates to share!

BubbleUp is Honeycomb’s machine-assisted debugging feature and is one of our most powerful differentiators. It leverages machine analysis to cycle through all of the attributes found in billions of rows of telemetry to surface what is in common with problematic data compared to baseline data. This explains the context of anomalous code behavior by surfacing exactly what changed when you don’t know which attributes to examine or index, dramatically accelerating the debugging process.

You know that old adage about not seeing the forest for the trees? In our Authors’ Cut series, we’ve been looking at the trees that make up the observability forest—among them, CI/CD pipelines, Service Level Objectives, and the Core Analysis Loop. Today, I'd like to step back and take a look at how observability fits into the broader technical and cultural shifts in technology: cloud-native, DevOps, and SRE.

I am thrilled to share with you that Honeycomb now has a Field CTO: our very own Liz Fong-Jones. When Liz joined us, nearly four years ago, she was our first developer advocate and principal engineer. It was a bit of a risky move—on both our parts.

At Honeycomb, the datastore and query systems that we manage are sociotechnical in nature, meaning the move to observability requires a sociological shift as much as it does a technical one. We've covered the technical part in several prior discussions for our Authors’ Cut series, but the social aspect is a little squishier. Namely: How do you solve the people and culture problems that are necessary in making the shift to adopt observability practices?

Today, I’d like to tell you about a new community-contributed integration that connects Honeycomb to your ServiceNow workflows. My new integration reimagines what’s possible when connecting observability tools with ITSM systems. This post explains how it works and how to get started with it.

Another month has come to a close, so I’m back again to take you through what’s new and noteworthy from the month of September. If you missed last month’s blog, this will be a monthly recurring series to keep you posted with the latest and greatest at Honeycomb. There’s a ton to cover, so I’ll dispense with the preamble and dive right in.