This guide explains the key aspects of the OpenTelemetry Collector, including its features, use cases, and practical tips for managing telemetry data effectively.

The OpenTelemetry (OTel) project offers numerous components and instrumentations that support different languages and telemetry signals. However, this flexibility can be overwhelming, and new users often struggle to choose the right components and configure them properly for their specific use cases. To address this, OpenTelemetry defines the concept of a distribution, a tailored and customized version of OpenTelemetry components.

The OpenTelemetry Collector is a powerful tool for processing different types of telemetry data, such as metrics, traces, and logs, all in one place. This is important because traditional observability tools often require separate toolchains, which can be inconvenient and inflexible when changes are needed.

The OpenTelemetry project is changing how organizations approach observability. It aims to standardize monitoring across different systems. OpenTelemetry—commonly referred to as OTel—provides APIs, SDKs, exporters, and collectors. It is making data collection, analysis, and utilization more efficient, leading to better decision-making and technology adoption.

One of the things about OpenTelemetry that’s easy to miss if you’re not spending the whole day in the ins and outs of the project is just how much stuff it can do—but that’s what I’m here for! Today, I want to go through the project and give you a guide to the various parts of OpenTelemetry, how mature they are, and what you can expect over the next six months or so. I ranked these elements by relative maturity across the entire project.

How to identify root spans in OpenTelemetry Collector using filter and transform processors.

Are you looking for a way to increase your AIOps signal to noise ratio and get more value from your data? In this article we will explore how one can utilize OpenTelemetry’s collectors, processors and data models to add or enhance classification attributes. These attributes can help you use your AIOps tools more efficiently and derive more value from your current data.

Learn how to install and configure the OpenTelemetry Collector for enhanced observability. This guide covers Docker, Kubernetes, and Linux installations with step-by-step instructions and configuration examples.

One of the biggest advantages of the OpenTelemetry project is its vendor neutrality — something that many community members appreciate, especially if they’ve spent huge amounts of time migrating from one commercial vendor to another. Vendor neutrality also happens to be a core element of our big tent philosophy here at Grafana Labs. We realize, however, that this neutrality can have its limits when it comes to real-world use cases.

Learn about OTLP’s key features, and how it simplifies telemetry data handling, and get practical tips for implementation.