Telemetry data is a powerful tool for understanding the behavior of complex systems. OpenTelemetry provides a platform-agnostic, open-source way to collect, process, and store telemetry data. This post explores the OpenTelemetry collector architecture, specifically focusing on the Collectors component. We'll look at how collectors work and how they can be used to process telemetry data from any system or application. We'll also discuss some benefits of using OpenTelemetry for your telemetry needs.

OpenTelemetry (OTEL) is a big data platform that enables the collection and analysis of large-scale telemetry data. Many companies have adopted it for use in their products. In this post, we’ll discuss semantic conventions in OpenTelemetry and how they are used to make data processing easier. We’ll also discuss the different types of semantic conventions and their importance.

The growth of technology has led to more efficient and relevant digital experiences, and customers continue to expect more out of those interactions. That’s true no matter their location and no matter which device they choose to use. Companies that cannot provide these kinds of personalized interactions for their customers find themselves falling behind the competition as technology continues to advance.

The OpenTelemetry Collector is an application written in Go. The GitHub readme does a great job of describing it: So the OpenTelemetry collector is a Go binary that does exactly what its name implies: it collects data and sends it to a back-end. But there’s a lot of functionality that lies in between. What a neat service! A local destination for data that handles the final sending of Open Telemetry information to your back end.

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.

Apache Flink monitoring support is now available in the open source OpenTelemetry collector. You can check out the OpenTelemetry repo here! You can utilize this receiver in conjunction with any OTel collector: including the OpenTelemetry Collector and observIQ’s distribution of the collector. Below are quick instructions for setting up observIQ’s OpenTelemetry distribution, and shipping Apache Flink telemetry to a popular backend: Google Cloud Ops.

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.