Observability with OpenTelemetry
.NET OpenTelemetry enables you to instrument applications with standardized traces, metrics, and logs, then export them to observability backends like Jaeger, Prometheus, and Loki. This series teaches you how to add production-grade observability to .NET microservices step-by-step, starting from your first span and progressing to multi-signal correlation and performance tuning.
Observability is the practice of understanding system behavior through external outputs—logs, metrics, and traces. Unlike traditional monitoring, which requires you to define alerting rules in advance, observability lets you ask ad-hoc questions about failures, bottlenecks, and user experience in real time. OpenTelemetry is the open standard (endorsed by the Cloud Native Computing Foundation and adopted by over 450 organizations) that makes observability vendor-agnostic and language-neutral.
In this series, Dr. Alex Turner covers the complete journey: initial setup and SDK configuration, how to instrument application code to emit traces and metrics, context propagation across distributed systems, and practical integration with industry-standard backends (Jaeger for tracing, Prometheus for metrics). By the end, you will design observable .NET systems that communicate failures clearly and respond to them faster than traditional logs alone permit.
Articles in this series
- .NET OpenTelemetry: Getting Started
- OpenTelemetry Traces: Complete Setup for .NET
- Instrument Code for Tracing: .NET Example
- OpenTelemetry Metrics in .NET Applications
- Collecting Logs with OpenTelemetry in .NET
- Context Propagation in .NET Microservices
- Export Traces to Jaeger from .NET Apps
- Prometheus Metrics Export: .NET Guide
- Correlate Signals: Traces, Metrics, Logs
- OpenTelemetry Performance: Sampling & Optimization