opentelemetry-api

The OpenTelemetry API package delivers on its core promise: providing instrumentation hooks without forcing implementation details. The API-only design means near-zero performance impact when tracing is disabled, and the no-op implementations are genuinely lightweight. Context propagation works reliably across async boundaries, threads, and even greenlets with proper configuration.

Resource management is well thought out - tracers and meters are cached properly, and there's no connection pooling to worry about since this is just the API layer. The separation between API and SDK is brilliant for library authors but adds initial complexity for application developers who need to install both packages and wire them together.

The biggest operational win is the stability guarantee: the API rarely changes, so upgrading doesn't break instrumentation. However, debugging why traces aren't appearing requires understanding the SDK layer, and error messages don't always make this distinction clear. Timeout behavior and retry logic live in the exporter implementations, which can make troubleshooting span loss challenging when you're only familiar with the API surface.

The OpenTelemetry API provides a clean abstraction layer for instrumentation that genuinely works well in production. The no-op default implementations mean zero performance penalty until you wire up an actual SDK, which is critical for library authors. Context propagation is robust and the trace/meter/logger provider patterns are well-designed. Resource management is straightforward with proper cleanup hooks.

The biggest operational win is the flexibility around SDK implementation swapping without code changes. You instrument once with the API, then choose your backend later. Spans are lightweight, baggage propagation works reliably across service boundaries, and the semantic conventions package provides consistent attribute naming.

The main frustration is the API/SDK split confusion for newcomers—you need opentelemetry-sdk for actual functionality, which isn't obvious from package names. Documentation assumes familiarity with OTel concepts. Metric instrument selection (counter vs histogram vs gauge) requires careful reading to get right. The auto-instrumentation packages sometimes conflict with manual instrumentation in subtle ways around middleware ordering.

The opentelemetry-api package provides a clean abstraction for instrumenting Python applications with traces, metrics, and logs. The API follows OpenTelemetry specifications closely, which means concepts transfer across languages but requires understanding the broader OTel ecosystem first. Getting a basic tracer up and running is straightforward, but the documentation assumes familiarity with observability concepts.

Day-to-day usage is pleasant once you grasp the context propagation model and span lifecycle management. The decorator-based approach for tracing functions works well, and manually creating spans gives you fine-grained control. Error messages are generally informative, though you'll occasionally hit cryptic issues related to missing exporters or SDK configuration since the API package is deliberately minimal.

The community support is strong - GitHub issues get responses within days, and Stack Overflow has decent coverage for common patterns. The auto-instrumentation libraries handle most frameworks well, but custom instrumentation requires reading both API docs and best practices guides. Debugging can be tricky when traces don't appear, usually due to SDK/exporter misconfiguration rather than API issues.