Here's something wild: almost every major observability platform you've heard of—Datadog, New Relic, Honeycomb, Grafana, Splunk—is powered by the same underlying technology. OpenTelemetry (OTel for short) has quietly become the universal standard for collecting telemetry data.

What is OpenTelemetry?

OpenTelemetry is a collection of APIs, SDKs, and tools for instrumenting your applications to generate telemetry data—the signals that tell you what's happening inside your systems. It standardizes how we collect, process, and export three pillars of observability:

• Traces: The journey of a request through your distributed system
• Metrics: Numerical measurements of system health (CPU, latency, throughput)
• Logs: Timestamped records of discrete events

The brilliance is in the standardization. Before OTel, every vendor had their own SDK, their own format. Want to switch from Datadog to Honeycomb? Good luck ripping out all that vendor-specific instrumentation. OTel solved this by creating a vendor-neutral layer. Instrument once, export anywhere.

Why This Matters

Here's my honest take: observability seems like a luxury until you're debugging a production incident at 2 AM. Then it becomes existential.

Modern systems are distributed, ephemeral, and complex. Microservices, serverless functions, containers spinning up and down. You can't SSH into a Lambda function that ran for 200ms and is now gone.

What OTel does is give you visibility into the invisible. You instrument your code once, and suddenly you can ask questions you couldn't before:

• Which service is causing this spike in latency?
• What changed between this deployment and the last one?
• Why did this specific user's request fail?

And because it's vendor-neutral, you're not locked in. You can send your traces to Honeycomb, metrics to Prometheus, logs to Elasticsearch. Or switch providers tomorrow. The instrumentation stays the same.

Observability Over Monitoring

Monitoring tells you when something is broken. Observability lets you ask why.

Traditional monitoring is like having a check engine light. Observability is like having a full diagnostic system that lets you ask arbitrary questions about your system's state—even ones you didn't anticipate.

OpenTelemetry enables this by giving you rich, structured, correlated data through shared context like trace IDs and span IDs. When something goes wrong, you can jump from a trace span directly to the relevant logs and metrics.

The Beautiful Part

What I genuinely love about OpenTelemetry is that it's a rare example of the industry cooperating on something important. It's a CNCF project backed by Google, Microsoft, Amazon, and basically every observability vendor. Companies that compete fiercely have all agreed: this is too important to fragment.

And it works. OTel has become the de facto standard not because it was mandated, but because it's genuinely better than the alternative. Developers adopted it because it solved real problems. Vendors adopted it because developers demanded it.

The Future is Telemetry

As systems get more complex, observability stops being optional. You can't reason about distributed systems without it. And if you're going to invest in observability, you want to do it on an open standard that won't trap you with a single vendor.

That's why OpenTelemetry matters. It's the foundation that every modern observability solution is built on. And honestly? That's kind of beautiful. In an industry full of fragmentation and vendor lock-in, OTel is a rare win for interoperability and developer experience.

If you're building anything non-trivial in 2025, you should be thinking about how you're collecting telemetry. Because when things inevitably break—and they will—you'll want to know exactly what happened, why it happened, and how to fix it.

OpenTelemetry gives you that power. Use it.

Want to dive deeper? Check out the OpenTelemetry docs or explore the ecosystem of collectors, exporters, and instrumentation libraries.