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System Design Masterclass · Observability Monitoring
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Before OpenTelemetry, every observability vendor had its own instrumentation library. If you used Datadog, you installed the Datadog SDK. Jaeger? Jaeger SDK. New Relic? New Relic agent. Switching vendors meant re-instrumenting every service, a migration so painful that most teams simply didn't.
OpenTelemetry (OTel) changed this. It's a single, vendor-neutral set of APIs, SDKs, and tools for generating and collecting telemetry data, traces, metrics, and logs. Instrument your code once with OpenTelemetry, and export to any backend: Datadog, Jaeger, , New Relic, AWS X-Ray, or any combination.
It's the second-most active project in the Cloud Native Computing Foundation (after ). Every major observability vendor supports it. It's available in 11 languages. And it's becoming the default way the industry instruments software.
OTel has three core components:
1. API. Defines the interfaces for creating traces, metrics, and logs. Your application code uses the API to create spans, record metrics, and emit log records. The API is lightweight, adding it to your code has near-zero overhead.
2. SDK. The implementation of the API. Configures how telemetry data is processed, sampled, and exported. You configure the SDK once at application startup: which exporter to use, what sampling rate, which resource attributes to attach.
3. Collector. A standalone process that receives, processes, and exports telemetry data. It sits between your applications and your backend, providing a centralized point for configuration, filtering, sampling, and fan-out to multiple backends.
Application (SDK) → OTLP → Collector → Backend (Jaeger, Datadog, etc.)
Auto-instrumentation. OTel provides automatic instrumentation for popular frameworks and libraries in every supported language. In Node.js, you add one package and get automatic spans for Express routes, client calls, database queries, and more, without changing application code.