Getting Started with Open Telemetry (OTEL)

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Introduction

OpenTelemetry (OTel) is a vendor-neutral, open-source observability framework that provides a standardized way to collect, process, and export telemetry data—including traces, metrics, and logs—from across the stack. OpenTelemetry forms the backbone of instrumentation and observability, enabling teams to trace requests as they travel through microservices, monitor model inference performance, and correlate logs and metrics in real time. It supports both automatic and manual instrumentation, offering flexibility for deep introspection without sacrificing developer velocity.

Key benefits of using OpenTelemetry include:

  • Unified Telemetry Collection: Provides a consistent SDK and protocol for capturing traces, metrics, and logs across languages (e.g., Python, Go, JavaScript), frameworks, and environments.

  • Distributed Tracing for Debugging: Enables tracing of complex, cross-service requests to pinpoint latency bottlenecks, failures, and dependency issues in real time.

  • Metrics and Logs Correlation: Captures telemetry data in a structured format that can be exported to backends like Prometheus, Grafana, Jaeger, Tempo, or DataDog for unified analysis and alerting.

  • Vendor-Agnostic and Extensible: Avoids vendor lock-in by allowing Cake to route observability data to multiple destinations via the OpenTelemetry Collector and exporter plugins.

  • Rich Ecosystem and Auto-Instrumentation: Supports integration with common frameworks (e.g., FastAPI, Flask, gRPC, Kubernetes, PostgreSQL) for rapid, low-effort observability setup.

OpenTelemetry is used to instrument services at every layer—from API gateways and inference servers (e.g., LiteLLM, Ray Serve, Triton) to background data pipelines and model monitoring endpoints. It enables deep insight into request paths, service interactions, and system health—all while maintaining consistency in observability tooling. By adopting OpenTelemetry, you can ensure its systems are transparent, traceable, and measurable across services and workloads—empowering teams to detect issues faster and operate with greater confidence and precision.

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