Telemetry Pipelines, Collectors and Agents: What’s the Difference?

Not so long ago, choosing an observability solution was simpler: You went all-in with a vendor or you committed fully to open source. Never both.

But with standards like OpenTelemetry and Prometheus, those rigid boundaries have disappeared. Today you can mix vendor solutions with open source technologies to build your ideal observability stack. While this flexibility is powerful, it also means navigating a sea of ever-changing and overlapping terms.

Observability is for everyone, but it can feel challenging to understand when we can’t even agree on a definition of application performance monitoring (APM). Even after a decade working in observability, as a practitioner or at a vendor, I get puzzled by the glut of new terms and concepts. At times, it makes my head want to explode.

Take, for instance, telemetry pipelines.

When I first heard about it, I had endless questions: Was this a specific product? A new category of tools? How exactly was it different from the collectors and agents we’ve been using for years? These questions kicked off a long debate with my colleagues, each with their own definition

This led me down a research rabbit hole — and I’m clearly not alone in my curiosity. Gartner reported a 500% increase in inquiries about telemetry pipelines from client organizations between 2021 and 2023. Given how many of us are trying to wrap our heads around this concept, I knew it was time for a clear explanation. So here’s my definition:

A telemetry pipeline is a system that collects, transforms and routes telemetry data (logs, metrics and traces) from various sources to various monitoring and analysis tools. Instead of managing separate agents or collectors for different signals, a telemetry pipeline processes data through a unified route, making observability more efficient and scalable.

So, What Are Agents and Collectors?

If a telemetry pipeline’s job is to collect, process and export telemetry data, then what are agents and collectors for? If your head is already spinning, trust me, I’ve been there. When I first started exploring telemetry pipelines, I wanted to define clear, universal distinctions between agents, collectors and telemetry pipelines.

But the deeper I dug, the more I realized that these terms don’t always map neatly to strict definitions — different teams and vendors use them in slightly different ways. That said, it’s still helpful to have a general frame of reference.

Agents: The First Mile of Telemetry

Agents are like your local mail carrier — they operate at the source, collecting telemetry from a specific application or system and forwarding it onward to a central location. They typically run alongside applications as sidecars or on the same host, focusing on that “first mile” of data delivery.

Collectors: The Middle Mile Aggregators

Collectors are like a regional post office, gathering telemetry data from multiple agents (or directly from applications and infrastructure) before forwarding it to its final destination. Collectors can receive and route telemetry.

Telemetry Pipelines: The Entire System

A telemetry pipeline is like the entire postal system and is responsible for handling observability data end-to-end. It does not just forward data but can normalize, enrich, filter and dynamically route telemetry based on your needs.

Telemetry Pipelines in the Real World

While the postal service metaphor is useful to provide a base level of understanding, the reality is that the terms “agent,” “collector” and “telemetry pipeline” do not have universally accepted terms carved out in stone. The definitions shift depending on context and implementation. When you understand how these terms relate, it’s easier to navigate the terminology jungle — and more importantly, build a telemetry pipeline that works for you.

Let’s look at how the two leading open source telemetry pipelines use these terms.

OpenTelemetry Collector

The OpenTelemetry Collector docs describe it as “a vendor-agnostic way to receive, process and export data.” Sound familiar? That’s because it matches my definition of a telemetry pipeline perfectly.

But despite functioning as a telemetry pipeline, it’s called “Collector,” which might lead you to think it’s only a middle-mile relay without data processing capabilities. The terminology overlap doesn’t stop there. When setting up an OpenTelemetry Collector, you configure pipelines — specific data paths that handle logs, metrics, events or traces.

Then there’s the question of how the OpenTelemetry Collector is deployed. It can act as an agent (first-mile telemetry collection) or as a gateway (a centralized processing hub). But here’s where it gets even trickier: In other monitoring systems, that gateway deployment is called a “collector,” a term OpenTelemetry reserves for the program itself. This is the kind of subtle but significant inconsistency that forces you to rethink what these words mean depending on which ecosystem you’re using.

This isn’t specific to OpenTelemetry; Fluent Bit also checks all the boxes of a telemetry pipeline — it collects, processes and routes telemetry data — but it, too, is configured with “pipelines” and can be deployed as an agent or a centralized gateway. In the Fluent Bit world, a “pipeline” can be either Fluent Bit as a whole or the individual pipelines within it. Same core functionality but slightly different terminology.

The More You Know

I’ve given you my take on these terms and the insights here came from my research, real-world experience and long conversations with colleagues. But there’s always more to learn and language is fluid, ever-evolving and subject to interpretation. If you have suggestions or a different take, I’d love to hear them, reach out on Mastodon or Bluesky. And if you’re looking for a quick reference, our Telemetry Pipeline Glossary is a great resource to bookmark.