In this article, I’m going to walk you through adding attributes to your spans in.NET that contain information about the code that generated the span. We’ll also look at ways to do this automatically using a library I’ve created.

An app that works as expected is great, but if expected means a beachball for 10 seconds before the page loads, that’s… not so great. Customers want it all; an application that is stable and fast… Luckily, Sentry does more than tell you when something is broken in your code, it also tells you what’s slow and how to fix it.

Tracing is often the last thought in any observability strategy. While engineers prioritize logs and metrics, tracing is truly the hallmark of a mature observability platform, but it is also the most difficult to implement. Once tracing is in place, engineers typically discover something else – many tracing solutions aren’t particularly feature-rich.

Joining a new dev team can be an exciting but somewhat intimidating experience. On one hand, you’re jumping into new adventures and opportunities. On the other hand, most onboarding experiences are fraught with stress and a sense of overwhelming from how much you have to learn, fast, to be able to contribute to your new team. To be honest, I’d never worked at a place where the developer onboarding experience was particularly memorable – until I joined Helios.

Observability is a mindset that lets you use data to answer questions about business processes. In short, collecting as much data as possible from the components of your business — including applications and key business metrics — then using an AI-powered tool to help consolidate and make sense of this huge volume of data gives you observability into your business. Having observability for your business and applications lets you make smarter decisions, faster.

Log tracking, trace log, or logging traces… Although these three terms are easy to interchange (the wordplay certainly doesn’t help!), compare tracing vs. logging, and you’ll find they are quite distinct. Logs, traces, and metrics are the three pillars of observability, and they all work together to measure application performance effectively. Let’s first understand what logging is.

With the introduction of container orchestration frameworks like Kubernetes, the adoption of cloud-native technologies, and the transition to microservices architectures, engineering organizations were empowered to build scalable and complex applications. DevOps engineers have had an indispensable role in this revolution, enabling and supporting these processes.

If you've stumbled (or purposefully landed) on this blog post, chances are you are new to—or diving deeper—into the observability space, o11y for short. Suffice it to say, you’re not in Kansas anymore. Honeycomb in a lot of ways can serve as a yellow brick road into o11y, and this article should serve as an introduction into how Honeycomb facilitates implementing o11y into applications and distributed services.

Tracing, or more specifically distributed tracing or distributed request tracing, is the ability to follow a request through a system, joining the dots between all the individual system calls required to service a particular request. Although tracing logs have been around for some time, the trend toward distributed architectures, microservices, and containerization has elevated it from nice-to-have status to an essential piece of the observability puzzle.

Earlier this year Gartner published a report discussing OpenTelemetry and its place in enhancing Application Performance Monitoring (APM).

OpenTelemetry (also known as OTel) is a popular open-source framework used to generate telemetry data for traces, metrics, events and logs. In this guide, we are going to cover the best observability and application performance management tools that can be used alongside OpenTelemetry to transform telemetry data into responsive reporting dashboards.

How do you go from A to Z with observability and OpenTelemetry? This post answers a question we hear often: “How do I get started on instrumentation with OpenTelemetry, while also following best practices for the long-term?” This article is all about taking you from A to Z on instrumentation. This will help you: We will use a simple greeting service application written in Node.js to understand the journey. You can find the pre-instrumented state here.

OpenTelemetry is one of the most fascinating and ambitious open source projects of this era. It’s currently the second most active project in the CNCF (the Cloud Native Computing Foundation), with only Kubernetes being more active. I was at KubeCon Europe last month, delivering a talk on OpenTelemetry and it was amazing to see the full house and the excitement and interest around the project.

At incident.io we use gorm.io as the ORM library for our Postgres database, it’s a really powerful tool and one I’m very glad for after years of working with hand-rolled SQL in Go & Postgres apps. You may have seen from our other blog posts that we’re heavily invested in tracing, specifically with Google Cloud Tracing via OpenCensus libraries.