.NET Core  

OpenTelemetry in .NET: End-to-End Observability for Modern Applications

Introduction

Modern applications are no longer simple monolithic systems. Today's software often consists of microservices, APIs, cloud resources, databases, message queues, and third-party integrations working together to deliver business functionality. While this architecture improves scalability and flexibility, it also makes troubleshooting significantly more complex.

When an application becomes slow or starts failing, developers need visibility into what is happening across the entire system. Traditional logging alone is often insufficient because it cannot easily show how requests move between services or identify performance bottlenecks.

This is where OpenTelemetry comes in. OpenTelemetry has become the industry standard for observability, providing a unified way to collect telemetry data such as logs, metrics, and traces. In the .NET ecosystem, OpenTelemetry enables developers to gain end-to-end visibility into application behavior, helping teams diagnose issues faster and improve system reliability.

In this article, you'll learn what OpenTelemetry is, why observability matters, how OpenTelemetry works in .NET applications, and best practices for implementing effective observability.

What Is OpenTelemetry?

OpenTelemetry is an open-source observability framework that provides standardized APIs, SDKs, and tools for collecting telemetry data.

It helps developers capture three key observability signals:

  • Traces

  • Metrics

  • Logs

These signals work together to provide a complete view of application health and performance.

Instead of relying on vendor-specific monitoring solutions, OpenTelemetry offers a vendor-neutral approach that can integrate with various monitoring platforms.

The basic workflow looks like this:

Application
      ↓
OpenTelemetry SDK
      ↓
Telemetry Data
      ↓
Monitoring Platform

This standardized approach simplifies observability across different environments and technologies.

Understanding the Three Pillars of Observability

Traces

Tracing follows a request as it moves through multiple services.

Consider an e-commerce application:

User Request
      ↓
API
      ↓
Order Service
      ↓
Database
      ↓
Payment Service

Distributed tracing allows developers to see exactly where time is being spent and identify failures across service boundaries.

Metrics

Metrics provide numerical measurements about application behavior.

Examples include:

  • Request count

  • Response time

  • Error rate

  • CPU usage

  • Memory consumption

Metrics help teams monitor trends and detect potential problems before users are affected.

Logs

Logs provide detailed records of application events.

Examples include:

  • Exceptions

  • Warnings

  • Authentication failures

  • Business events

While traces show request flow and metrics show trends, logs provide detailed context.

Together, these three signals create a comprehensive observability strategy.

Why OpenTelemetry Matters for .NET Applications

Many organizations operate distributed systems built with:

  • ASP.NET Core APIs

  • Microservices

  • Azure services

  • Background workers

  • Containerized workloads

Without observability, diagnosing issues becomes difficult.

Common challenges include:

  • Slow API responses

  • Database bottlenecks

  • Service communication failures

  • Unexpected exceptions

  • Resource consumption spikes

OpenTelemetry helps developers quickly identify root causes by providing visibility across the entire application ecosystem.

Installing OpenTelemetry Packages

To get started, install the required packages.

dotnet add package OpenTelemetry.Extensions.Hosting
dotnet add package OpenTelemetry.Instrumentation.AspNetCore
dotnet add package OpenTelemetry.Instrumentation.Http
dotnet add package OpenTelemetry.Exporter.Console

These packages enable telemetry collection and export capabilities.

Configuring OpenTelemetry in ASP.NET Core

Register OpenTelemetry during application startup.

builder.Services.AddOpenTelemetry()
    .WithTracing(tracing =>
    {
        tracing
            .AddAspNetCoreInstrumentation()
            .AddHttpClientInstrumentation()
            .AddConsoleExporter();
    });

This configuration automatically captures:

  • Incoming HTTP requests

  • Outgoing HTTP requests

  • Request durations

  • Trace information

Developers immediately gain visibility into application activity.

Understanding Distributed Tracing

Distributed tracing is one of OpenTelemetry's most valuable capabilities.

Imagine a request flowing through multiple services.

Client
   ↓
API Gateway
   ↓
Product Service
   ↓
Inventory Service
   ↓
Database

Without tracing, identifying performance issues requires examining logs across multiple systems.

With distributed tracing:

Trace ID
   ↓
Entire Request Journey

Developers can follow a request from start to finish and quickly locate bottlenecks.

This is especially useful in microservices architectures.

Collecting Metrics

Metrics help monitor system health over time.

Add metrics support:

builder.Services.AddOpenTelemetry()
    .WithMetrics(metrics =>
    {
        metrics
            .AddAspNetCoreInstrumentation()
            .AddHttpClientInstrumentation()
            .AddRuntimeInstrumentation()
            .AddConsoleExporter();
    });

Common metrics include:

  • Request duration

  • Throughput

  • Memory usage

  • Garbage collection activity

These measurements help teams understand application performance trends.

Custom Tracing

In addition to automatic instrumentation, developers can create custom traces.

Example:

using System.Diagnostics;

var activitySource =
    new ActivitySource("OrderProcessing");

using var activity =
    activitySource.StartActivity("CreateOrder");

activity?.SetTag("OrderId", 1001);

Custom tracing is useful for:

  • Business workflows

  • Order processing

  • Payment operations

  • Inventory updates

This provides visibility into application-specific processes.

Exporting Telemetry Data

OpenTelemetry collects telemetry data, but organizations typically send it to monitoring platforms.

Popular destinations include:

  • Azure Monitor

  • Application Insights

  • Jaeger

  • Grafana

  • Prometheus

  • Datadog

The workflow becomes:

Application
      ↓
OpenTelemetry
      ↓
Collector
      ↓
Monitoring Platform

This flexibility is one of OpenTelemetry's biggest advantages.

Teams can change monitoring vendors without rewriting application instrumentation.

OpenTelemetry and Microservices

Observability becomes increasingly important as systems grow.

Consider a microservices environment:

API Gateway
     ↓
User Service
     ↓
Order Service
     ↓
Payment Service
     ↓
Notification Service

A failure in any component can affect the user experience.

OpenTelemetry helps answer questions such as:

  • Which service is slow?

  • Where did the error occur?

  • How long did each operation take?

  • Which dependency is causing issues?

Without observability, answering these questions can take hours.

With OpenTelemetry, answers are often available within minutes.

Best Practices

Instrument Early

Add observability during development rather than after deployment.

Retrofitting telemetry later is often more difficult.

Use Automatic Instrumentation

Leverage built-in instrumentation whenever possible.

This reduces implementation effort and ensures consistency.

Add Business-Level Traces

Technical telemetry is important, but business workflows should also be traced.

Examples include:

  • Order creation

  • Payment processing

  • User registration

These traces provide valuable operational insights.

Monitor Critical Metrics

Focus on metrics that directly impact users:

  • Latency

  • Error rates

  • Throughput

  • Availability

Avoid collecting unnecessary data.

Standardize Naming

Use consistent names for:

  • Services

  • Activities

  • Metrics

  • Tags

Consistency improves troubleshooting and reporting.

Protect Sensitive Information

Never expose:

  • Passwords

  • Access tokens

  • Personal information

through telemetry data.

Observability should enhance visibility without creating security risks.

Common Mistakes to Avoid

MistakeImpact
Relying only on logsLimited visibility
Excessive telemetry collectionHigher storage costs
Missing business tracesReduced operational insight
Inconsistent namingDifficult troubleshooting
Ignoring metricsDelayed issue detection
Exposing sensitive dataSecurity risks

Avoiding these mistakes helps create a more effective observability strategy.

Conclusion

As modern applications become increasingly distributed, observability is no longer optional. Development teams need visibility into application behavior, performance, and dependencies to maintain reliability and quickly resolve issues.

OpenTelemetry provides a standardized and vendor-neutral approach to collecting traces, metrics, and logs across .NET applications. By implementing OpenTelemetry early, leveraging automatic instrumentation, and adding meaningful business-level telemetry, teams can gain end-to-end visibility into their systems and significantly improve troubleshooting capabilities.

Whether you're building ASP.NET Core APIs, microservices, cloud-native applications, or enterprise platforms, OpenTelemetry offers a powerful foundation for modern observability. Investing in a strong observability strategy today can lead to faster issue resolution, improved system performance, and a better experience for both developers and users.