It’s no secret that CI/CD pipelines make the lives of engineering and operations easier by accelerating the feedback loop for higher quality code and apps. They build code, run tests, and safely deploy new versions of your application. But just like any aspect of development, poor integration, invisible bottlenecks, and bugs can plague your pipelines. And debugging them? Well, it’s complicated.

A prelude to our upcoming six-part Observability Maturity Model Fundamentals blog series. By Lodewijk Bogaards At StackState, we have spent eight years in the monitoring and observability spaces. During this time, we have spoken with countless DevOps engineers, architects, SREs, heads of IT operations and CTOs, and we have heard the same struggles over and over.

Technically speaking, observability offers visibility into the data being generated by your infrastructure devices, systems, and applications — but in reality, it offers the opportunity to see what’s happening, There’s no guarantee that you’ll get what you want; you have to set things up in a way that makes it possible for you to get the insights you need.

It’s already September! Time flies by when you’re getting things done, and we’ve been a busy bunch of bees here at Honeycomb. 🐝 We’re excited that we’ve gotten to share some of those changes with you already, like our relaunched interactive sandbox and the beta release of our OpenTelemetry log support and Go distribution, but that’s just the tip of the iceberg.

Pranay, one of the the co-founders at SigNoz, was recently invited as a guest speaker by Jonah Kowall, CTO at Logz.io on his OpenObservability Podcast. In the podcast, Pranay talks about the mission behind SigNoz - unifying traces, metrics, and logs in a single platform and interface. He also shared anecdotes about the evolution of SigNoz since its inception, the community adoption, and its contribution to SigNoz.

We recently hosted a Twitter Space, and a question came in regarding speaking to executives about instrumenting for observability. It’s a great topic we love expanding on. Here’s the answer we provided.

Artificial intelligence for IT operations (AIOps) is the application of artificial intelligence (AI) and associated technologies—like machine learning (ML) and natural language processing—for normal IT operations activities and endeavors. AIOps helps ITOps, DevOps, and site reliability engineer (SRE) teams work better by examining IT information and observability telemetry.

In Part 1 of this series, we talked about the origins of observability and why you need it. In this blog (Part 2), we will cover exactly what observability is, what it isn’t, and how to get started. Before we can dive into how to approach observability, let’s get one thing clear: You can’t buy a one-size-fits-all observability solution.

We’ve got a lot of OpenTelemetry-flavored honey to send your way, ranging from OpenTelemetry SDK distribution updates to protocol support. We now support OpenTelemetry logs, released a new SDK distribution for OpenTelemetry Go, and have some updates around OpenTelemetry + Honeycomb to share. Let’s see what all the buzz is about this time! 🐝🐝