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opentelemetry

codewithmukesh/dotnet-claude-kit

Distributed tracing, metrics, and logs for .NET 10 with OpenTelemetry and OTLP export.

What is opentelemetry?

OpenTelemetry observability for .NET 10 applications covering traces, metrics, and logs through a unified SDK setup. Use this when implementing distributed tracing, custom metrics, OTLP export to backends like Aspire Dashboard, or when working with ActivitySource, IMeterFactory, and telemetry instrumentation.

  • Configure traces, metrics, and logs through a single AddOpenTelemetry() call with UseOtlpExporter()
  • Create custom metrics using IMeterFactory with Counter, Histogram, UpDownCounter, and Gauge instruments
  • Implement distributed tracing with custom ActivitySource and null-safe Activity operations
  • Instrument ASP.NET Core, HTTP clients, Entity Framework Core, and runtime signals automatically
  • Export telemetry to any OTLP-compatible backend via environment variables (OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_SERVICE_NAME)
  • Integrate with Aspire Dashboard for local development observability

How to install opentelemetry

npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill opentelemetry
Prerequisites
  • .NET 10 SDK installed
  • OpenTelemetry NuGet packages (OpenTelemetry, OpenTelemetry.Exporter.OpenTelemetryProtocol, instrumentation packages)
  • OTLP-compatible backend (Aspire Dashboard, Jaeger, Grafana Tempo, or similar) for local or production use
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How to use opentelemetry

  1. 1.Add OpenTelemetry services in Program.cs with AddOpenTelemetry() and configure resource name and version
  2. 2.Register instrumentation for ASP.NET Core, HTTP clients, Entity Framework Core, and runtime as needed
  3. 3.Create a custom metrics class using IMeterFactory to define Counter, Histogram, UpDownCounter, and Gauge instruments
  4. 4.Register custom ActivitySource in the tracing builder and use it to create Activities with tags and events
  5. 5.Call UseOtlpExporter() to export all three signals (traces, metrics, logs) to your OTLP endpoint
  6. 6.Set OTEL_EXPORTER_OTLP_ENDPOINT and OTEL_SERVICE_NAME environment variables to control telemetry routing

Use cases

Good for
  • Set up end-to-end distributed tracing across microservices to track request flow and latency
  • Monitor custom business metrics like order processing duration and active queue depth with low-cardinality tags
  • Export application traces and metrics to a centralized OTLP collector for production observability
  • Debug performance issues locally using Aspire Dashboard without external infrastructure
  • Correlate logs with traces by automatically including TraceId and SpanId in structured logging
Who it's for
  • Backend engineers building .NET 10 microservices
  • DevOps and SRE teams implementing observability pipelines
  • Developers debugging distributed system performance issues
  • Teams adopting OpenTelemetry for vendor-neutral telemetry

opentelemetry FAQ

Why use IMeterFactory instead of creating Meter instances directly?

IMeterFactory manages Meter lifetime through dependency injection and prevents memory leaks. Creating Meter instances with 'new' per request causes unbounded resource growth.

What happens if I call StartActivity() when no listener is attached?

StartActivity() returns null when no listener is attached. Always use null-safe operators (?.SetTag, ?.AddEvent) to avoid NullReferenceException.

Can I use high-cardinality values like user IDs or request IDs as metric tags?

No. Keep metric tag combinations under ~1000 per instrument. Use span attributes or logs for high-cardinality data instead.

Should I call AddOtlpExporter() separately for each signal (traces, metrics, logs)?

No. Use UseOtlpExporter() once to export all three signals together. Mixing UseOtlpExporter with per-signal AddOtlpExporter calls throws NotSupportedException.

How do I run Aspire Dashboard locally without the full Aspire orchestration?

Run 'docker run --rm -it -p 18888:18888 -p 4317:18889 mcr.microsoft.com/dotnet/aspire-dashboard:latest' and point your app to OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317. The UI is at http://localhost:18888.

Full instructions (SKILL.md)

Source of truth, from codewithmukesh/dotnet-claude-kit.


name: opentelemetry description: > OpenTelemetry observability for .NET 10 applications. Covers traces, metrics, and logs using the OpenTelemetry SDK with OTLP export. Includes custom ActivitySource, IMeterFactory metrics, resource configuration, and Aspire Dashboard integration. Load this skill when setting up distributed tracing, custom metrics, OTLP export, or when the user mentions "OpenTelemetry", "OTLP", "traces", "spans", "Activity", "ActivitySource", "metrics", "IMeterFactory", "Meter", "Counter", "Histogram", "Gauge", "telemetry", "observability", "distributed tracing", "OTEL", or "Aspire Dashboard".

OpenTelemetry

Core Principles

  1. Three pillars, one setup — Configure traces, metrics, and logs through a single AddOpenTelemetry() call. Use UseOtlpExporter() for cross-cutting export to any OTLP-compatible backend.
  2. Use IMeterFactory for metrics — Never create Meter instances with new. The factory manages lifetime through DI and prevents leaks.
  3. Null-safe activities — StartActivity() returns null when no listener is attached. Always use ?. when setting tags or events.
  4. Environment variables over code — Use OTEL_EXPORTER_OTLP_ENDPOINT and OTEL_SERVICE_NAME so deployments control telemetry routing without code changes.
  5. Low-cardinality metric tags — Keep metric tag combinations under ~1000 per instrument. Use span attributes or logs for high-cardinality data like user IDs or request IDs.

Patterns

Full Setup with All Three Signals

// Program.cs
var builder = WebApplication.CreateBuilder(args);

builder.Services.AddOpenTelemetry()
    .ConfigureResource(resource => resource
        .AddService(
            serviceName: builder.Environment.ApplicationName,
            serviceVersion: "1.0.0"))
    .WithTracing(tracing => tracing
        .AddAspNetCoreInstrumentation()
        .AddHttpClientInstrumentation()
        .AddEntityFrameworkCoreInstrumentation()
        .AddSource("MyApp.Orders"))
    .WithMetrics(metrics => metrics
        .AddAspNetCoreInstrumentation()
        .AddHttpClientInstrumentation()
        .AddRuntimeInstrumentation()
        .AddMeter("MyApp.Orders"))
    .WithLogging()             // no per-signal exporter here —
    .UseOtlpExporter();        // UseOtlpExporter covers all three signals

// UseOtlpExporter replaces per-signal AddOtlpExporter calls. Never combine
// the two — mixing them throws NotSupportedException (see Anti-patterns).

The OTLP endpoint defaults to http://localhost:4317 (gRPC). Override via:

OTEL_EXPORTER_OTLP_ENDPOINT=http://collector:4317
OTEL_SERVICE_NAME=MyApp.Api

Custom Metrics with IMeterFactory

Register a metrics class as a singleton. IMeterFactory handles Meter disposal through DI.

public sealed class OrderMetrics
{
    private readonly Counter<int> _ordersCreated;
    private readonly Histogram<double> _orderDuration;
    private readonly UpDownCounter<int> _activeOrders;
    private readonly Gauge<double> _queueDepth;

    public OrderMetrics(IMeterFactory meterFactory)
    {
        var meter = meterFactory.Create("MyApp.Orders");

        _ordersCreated = meter.CreateCounter<int>(
            "myapp.orders.created", "{orders}", "Number of orders created");

        _orderDuration = meter.CreateHistogram<double>(
            "myapp.orders.duration", "s", "Order processing duration",
            advice: new InstrumentAdvice<double>
            {
                HistogramBucketBoundaries = [0.01, 0.05, 0.1, 0.5, 1, 5, 10]
            });

        _activeOrders = meter.CreateUpDownCounter<int>(
            "myapp.orders.active", "{orders}", "Currently active orders");

        _queueDepth = meter.CreateGauge<double>(
            "myapp.orders.queue_depth", "{items}", "Current queue depth");
    }

    public void OrderCreated() => _ordersCreated.Add(1);
    public void RecordDuration(double seconds) => _orderDuration.Record(seconds);
    public void OrderStarted() => _activeOrders.Add(1);
    public void OrderCompleted() => _activeOrders.Add(-1);
    public void SetQueueDepth(double depth) => _queueDepth.Record(depth);
}

// Registration
builder.Services.AddSingleton<OrderMetrics>();

Multi-Dimensional Metric Tags

Three or fewer tags are allocation-free. For more, use TagList.

// Allocation-free (3 or fewer tags)
_ordersCreated.Add(1,
    new KeyValuePair<string, object?>("order.type", "standard"),
    new KeyValuePair<string, object?>("payment.method", "credit_card"));

// 4+ tags — use TagList to avoid allocations
var tags = new TagList
{
    { "order.type", "standard" },
    { "payment.method", "credit_card" },
    { "region", "us-east" },
    { "priority", "high" }
};
_ordersCreated.Add(1, tags);

Custom ActivitySource for Distributed Tracing

public sealed class OrderService(ILogger<OrderService> logger)
{
    private static readonly ActivitySource Source = new("MyApp.Orders");

    public async Task<Order> ProcessOrderAsync(CreateOrderRequest request, CancellationToken ct)
    {
        using var activity = Source.StartActivity("ProcessOrder", ActivityKind.Internal);
        activity?.SetTag("order.customer_id", request.CustomerId);

        try
        {
            await ValidateOrder(request, ct);
            activity?.AddEvent(new ActivityEvent("OrderValidated"));

            var order = await SaveOrder(request, ct);
            activity?.SetTag("order.id", order.Id.ToString());
            activity?.SetStatus(ActivityStatusCode.Ok);
            return order;
        }
        catch (Exception ex)
        {
            activity?.SetStatus(ActivityStatusCode.Error, ex.Message);
            activity?.RecordException(ex);
            throw;
        }
    }
}

Register the source: .AddSource("MyApp.Orders") in the tracing builder.

Aspire Dashboard for Local Development

Run the standalone Aspire Dashboard without Aspire orchestration:

docker run --rm -it -p 18888:18888 -p 4317:18889 \
    mcr.microsoft.com/dotnet/aspire-dashboard:latest

Then point your app at it:

OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317

Dashboard UI is at http://localhost:18888.

Source-Generated Logging with OTel

For maximum performance, use [LoggerMessage] — eliminates boxing and allocations.

public partial class OrderService(ILogger<OrderService> logger)
{
    [LoggerMessage(Level = LogLevel.Information,
        Message = "Processing order {OrderId} for customer {CustomerId}")]
    partial void LogOrderProcessing(Guid orderId, Guid customerId);
}

OpenTelemetry logging automatically includes TraceId and SpanId when an Activity is current.

Anti-patterns

Don't Create Meters Per Request

// BAD — new Meter per request causes memory leaks
public void HandleRequest()
{
    var meter = new Meter("MyApp");
    meter.CreateCounter<int>("requests").Add(1);
}

// GOOD — singleton via IMeterFactory
public class MyMetrics(IMeterFactory meterFactory)
{
    private readonly Counter<int> _requests =
        meterFactory.Create("MyApp").CreateCounter<int>("myapp.requests");
    public void RequestHandled() => _requests.Add(1);
}

Don't Skip Null Checks on Activity

// BAD — NullReferenceException when no listener is attached
using var activity = source.StartActivity("Work");
activity.SetTag("key", "value");

// GOOD — null-safe
activity?.SetTag("key", "value");

Don't Use High-Cardinality Metric Tags

// BAD — unbounded cardinality causes memory explosion in collectors
_counter.Add(1, new("request.id", Guid.NewGuid().ToString()));
_counter.Add(1, new("user.id", userId));

// GOOD — low-cardinality dimensions only
_counter.Add(1, new("http.method", "GET"), new("http.status_code", 200));

Don't Mix UseOtlpExporter with AddOtlpExporter

// BAD — throws NotSupportedException at runtime
builder.Services.AddOpenTelemetry()
    .UseOtlpExporter()
    .WithTracing(t => t.AddOtlpExporter());

// GOOD — use one approach
builder.Services.AddOpenTelemetry().UseOtlpExporter();

Don't Forget to Register Custom Sources

// BAD — activities silently dropped (no listener registered)
var source = new ActivitySource("MyApp.Custom");
using var activity = source.StartActivity("Work"); // null!

// GOOD — register in the tracing builder
otel.WithTracing(t => t.AddSource("MyApp.Custom"));
otel.WithMetrics(m => m.AddMeter("MyApp.Custom"));

Decision Guide

ScenarioRecommendation
Full observability setupAddOpenTelemetry() with all three signals + UseOtlpExporter()
Custom business metricsIMeterFactory + singleton metrics class
Custom trace spansActivitySource + StartActivity()
Local development backendAspire Dashboard standalone container
Production backendOTel Collector as intermediary to Grafana/Datadog/etc.
Sampling in productionOTEL_TRACES_SAMPLER=parentbased_traceidratio with 10% ratio
High-performance logging[LoggerMessage] source generator
Metric tag cardinalityMax ~1000 combinations per instrument
Environment configurationOTEL_* env vars (also work via appsettings.json)