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Add and modify Azure Monitor OpenTelemetry for .NET, Java, Node.js, and Python applications

  • Artikkeli

This article provides guidance on how to add and modify OpenTelemetry for applications using Azure Monitor Application Insights.

To learn more about OpenTelemetry concepts, see the OpenTelemetry overview or OpenTelemetry FAQ.

Automatic data collection

The distros automatically collect data by bundling OpenTelemetry instrumentation libraries.

Included instrumentation libraries

Requests

Dependencies

Logging

  • ILogger

For more information about ILogger, see Logging in C# and .NET and code examples.

Footnotes

  • ¹: Supports automatic reporting of unhandled/uncaught exceptions
  • ²: Supports OpenTelemetry Metrics
  • ³: By default, logging is only collected at INFO level or higher. To change this setting, see the configuration options.
  • ⁴: By default, logging is only collected when that logging is performed at the WARNING level or higher.

Note

The Azure Monitor OpenTelemetry Distros include custom mapping and logic to automatically emit Application Insights standard metrics.

Tip

All OpenTelemetry metrics whether automatically collected from instrumentation libraries or manually collected from custom coding are currently considered Application Insights "custom metrics" for billing purposes. Learn more.

Add a community instrumentation library

You can collect more data automatically when you include instrumentation libraries from the OpenTelemetry community.

Caution

We don't support or guarantee the quality of community instrumentation libraries. To suggest one for our distro, post or up-vote in our feedback community. Be aware, some are based on experimental OpenTelemetry specs and might introduce future breaking changes.

To add a community library, use the ConfigureOpenTelemetryMeterProvider or ConfigureOpenTelemetryTracerProvider methods, after adding the NuGet package for the library.

The following example demonstrates how the Runtime Instrumentation can be added to collect extra metrics:

dotnet add package OpenTelemetry.Instrumentation.Runtime 

// Create a new ASP.NET Core web application builder.
var builder = WebApplication.CreateBuilder(args);

// Configure the OpenTelemetry meter provider to add runtime instrumentation.
builder.Services.ConfigureOpenTelemetryMeterProvider((sp, builder) => builder.AddRuntimeInstrumentation());

// Add the Azure Monitor telemetry service to the application.
// This service will collect and send telemetry data to Azure Monitor.
builder.Services.AddOpenTelemetry().UseAzureMonitor();

// Build the ASP.NET Core web application.
var app = builder.Build();

// Start the ASP.NET Core web application.
app.Run();

Collect custom telemetry

This section explains how to collect custom telemetry from your application.

Depending on your language and signal type, there are different ways to collect custom telemetry, including:

  • OpenTelemetry API
  • Language-specific logging/metrics libraries
  • Application Insights Classic API

The following table represents the currently supported custom telemetry types:

Language Custom Events Custom Metrics Dependencies Exceptions Page Views Requests Traces
ASP.NET Core
   OpenTelemetry API Yes Yes Yes Yes
   ILogger API Yes
   AI Classic API
Java
   OpenTelemetry API Yes Yes Yes Yes
   Logback, Log4j, JUL Yes Yes
   Micrometer Metrics Yes
   AI Classic API Yes Yes Yes Yes Yes Yes Yes
Node.js
   OpenTelemetry API Yes Yes Yes Yes
Python
   OpenTelemetry API Yes Yes Yes Yes
   Python Logging Module Yes
   Events Extension Yes Yes

Note

Application Insights Java 3.x listens for telemetry that's sent to the Application Insights Classic API. Similarly, Application Insights Node.js 3.x collects events created with the Application Insights Classic API. This makes upgrading easier and fills a gap in our custom telemetry support until all custom telemetry types are supported via the OpenTelemetry API.

Add custom metrics

In this context, the custom metrics term refers to manually instrumenting your code to collect additional metrics beyond what the OpenTelemetry Instrumentation Libraries automatically collect.

The OpenTelemetry API offers six metric "instruments" to cover various metric scenarios and you need to pick the correct "Aggregation Type" when visualizing metrics in Metrics Explorer. This requirement is true when using the OpenTelemetry Metric API to send metrics and when using an instrumentation library.

The following table shows the recommended aggregation types for each of the OpenTelemetry Metric Instruments.

OpenTelemetry Instrument Azure Monitor Aggregation Type
Counter Sum
Asynchronous Counter Sum
Histogram Min, Max, Average, Sum, and Count
Asynchronous Gauge Average
UpDownCounter Sum
Asynchronous UpDownCounter Sum

Caution

Aggregation types beyond what's shown in the table typically aren't meaningful.

The OpenTelemetry Specification describes the instruments and provides examples of when you might use each one.

Tip

The histogram is the most versatile and most closely equivalent to the Application Insights GetMetric Classic API. Azure Monitor currently flattens the histogram instrument into our five supported aggregation types, and support for percentiles is underway. Although less versatile, other OpenTelemetry instruments have a lesser impact on your application's performance.

Histogram example

Application startup must subscribe to a Meter by name:

// Create a new ASP.NET Core web application builder.
var builder = WebApplication.CreateBuilder(args);

// Configure the OpenTelemetry meter provider to add a meter named "OTel.AzureMonitor.Demo".
builder.Services.ConfigureOpenTelemetryMeterProvider((sp, builder) => builder.AddMeter("OTel.AzureMonitor.Demo"));

// Add the Azure Monitor telemetry service to the application.
// This service will collect and send telemetry data to Azure Monitor.
builder.Services.AddOpenTelemetry().UseAzureMonitor();

// Build the ASP.NET Core web application.
var app = builder.Build();

// Start the ASP.NET Core web application.
app.Run();

The Meter must be initialized using that same name:

// Create a new meter named "OTel.AzureMonitor.Demo".
var meter = new Meter("OTel.AzureMonitor.Demo");

// Create a new histogram metric named "FruitSalePrice".
Histogram<long> myFruitSalePrice = meter.CreateHistogram<long>("FruitSalePrice");

// Create a new Random object.
var rand = new Random();

// Record a few random sale prices for apples and lemons, with different colors.
myFruitSalePrice.Record(rand.Next(1, 1000), new("name", "apple"), new("color", "red"));
myFruitSalePrice.Record(rand.Next(1, 1000), new("name", "lemon"), new("color", "yellow"));
myFruitSalePrice.Record(rand.Next(1, 1000), new("name", "lemon"), new("color", "yellow"));
myFruitSalePrice.Record(rand.Next(1, 1000), new("name", "apple"), new("color", "green"));
myFruitSalePrice.Record(rand.Next(1, 1000), new("name", "apple"), new("color", "red"));
myFruitSalePrice.Record(rand.Next(1, 1000), new("name", "lemon"), new("color", "yellow"));

Counter example

Application startup must subscribe to a Meter by name:

// Create a new ASP.NET Core web application builder.
var builder = WebApplication.CreateBuilder(args);

// Configure the OpenTelemetry meter provider to add a meter named "OTel.AzureMonitor.Demo".
builder.Services.ConfigureOpenTelemetryMeterProvider((sp, builder) => builder.AddMeter("OTel.AzureMonitor.Demo"));

// Add the Azure Monitor telemetry service to the application.
// This service will collect and send telemetry data to Azure Monitor.
builder.Services.AddOpenTelemetry().UseAzureMonitor();

// Build the ASP.NET Core web application.
var app = builder.Build();

// Start the ASP.NET Core web application.
app.Run();

The Meter must be initialized using that same name:

// Create a new meter named "OTel.AzureMonitor.Demo".
var meter = new Meter("OTel.AzureMonitor.Demo");

// Create a new counter metric named "MyFruitCounter".
Counter<long> myFruitCounter = meter.CreateCounter<long>("MyFruitCounter");

// Record the number of fruits sold, grouped by name and color.
myFruitCounter.Add(1, new("name", "apple"), new("color", "red"));
myFruitCounter.Add(2, new("name", "lemon"), new("color", "yellow"));
myFruitCounter.Add(1, new("name", "lemon"), new("color", "yellow"));
myFruitCounter.Add(2, new("name", "apple"), new("color", "green"));
myFruitCounter.Add(5, new("name", "apple"), new("color", "red"));
myFruitCounter.Add(4, new("name", "lemon"), new("color", "yellow"));

Gauge example

Application startup must subscribe to a Meter by name:

// Create a new ASP.NET Core web application builder.
var builder = WebApplication.CreateBuilder(args);

// Configure the OpenTelemetry meter provider to add a meter named "OTel.AzureMonitor.Demo".
builder.Services.ConfigureOpenTelemetryMeterProvider((sp, builder) => builder.AddMeter("OTel.AzureMonitor.Demo"));

// Add the Azure Monitor telemetry service to the application.
// This service will collect and send telemetry data to Azure Monitor.
builder.Services.AddOpenTelemetry().UseAzureMonitor();

// Build the ASP.NET Core web application.
var app = builder.Build();

// Start the ASP.NET Core web application.
app.Run();

The Meter must be initialized using that same name:

// Get the current process.
var process = Process.GetCurrentProcess();

// Create a new meter named "OTel.AzureMonitor.Demo".
var meter = new Meter("OTel.AzureMonitor.Demo");

// Create a new observable gauge metric named "Thread.State".
// This metric will track the state of each thread in the current process.
ObservableGauge<int> myObservableGauge = meter.CreateObservableGauge("Thread.State", () => GetThreadState(process));

private static IEnumerable<Measurement<int>> GetThreadState(Process process)
{
    // Iterate over all threads in the current process.
    foreach (ProcessThread thread in process.Threads)
    {
        // Create a measurement for each thread, including the thread state, process ID, and thread ID.
        yield return new((int)thread.ThreadState, new("ProcessId", process.Id), new("ThreadId", thread.Id));
    }
}

Add custom exceptions

Select instrumentation libraries automatically report exceptions to Application Insights. However, you might want to manually report exceptions beyond what instrumentation libraries report. For instance, exceptions caught by your code aren't ordinarily reported. You might wish to report them to draw attention in relevant experiences including the failures section and end-to-end transaction views.

  • To log an Exception using an Activity:

    // Start a new activity named "ExceptionExample".
using (var activity = activitySource.StartActivity("ExceptionExample"))
{
    // Try to execute some code.
    try
    {
        throw new Exception("Test exception");
    }
    // If an exception is thrown, catch it and set the activity status to "Error".
    catch (Exception ex)
    {
        activity?.SetStatus(ActivityStatusCode.Error);
        activity?.RecordException(ex);
    }
}

  • To log an Exception using ILogger:

    // Create a logger using the logger factory. The logger category name is used to filter and route log messages.
var logger = loggerFactory.CreateLogger(logCategoryName);

// Try to execute some code.
try
{
    throw new Exception("Test Exception");
}
catch (Exception ex)
{
    // Log an error message with the exception. The log level is set to "Error" and the event ID is set to 0.
    // The log message includes a template and a parameter. The template will be replaced with the value of the parameter when the log message is written.
    logger.Log(
        logLevel: LogLevel.Error,
        eventId: 0,
        exception: ex,
        message: "Hello {name}.",
        args: new object[] { "World" });
}

Add custom spans

You might want to add a custom span in two scenarios. First, when there's a dependency request not already collected by an instrumentation library. Second, when you wish to model an application process as a span on the end-to-end transaction view.

Note

The Activity and ActivitySource classes from the System.Diagnostics namespace represent the OpenTelemetry concepts of Span and Tracer, respectively. You create ActivitySource directly by using its constructor instead of by using TracerProvider. Each ActivitySource class must be explicitly connected to TracerProvider by using AddSource(). That's because parts of the OpenTelemetry tracing API are incorporated directly into the .NET runtime. To learn more, see Introduction to OpenTelemetry .NET Tracing API.

// Define an activity source named "ActivitySourceName". This activity source will be used to create activities for all requests to the application.
internal static readonly ActivitySource activitySource = new("ActivitySourceName");

// Create an ASP.NET Core application builder.
var builder = WebApplication.CreateBuilder(args);

// Configure the OpenTelemetry tracer provider to add a source named "ActivitySourceName". This will ensure that all activities created by the activity source are traced.
builder.Services.ConfigureOpenTelemetryTracerProvider((sp, builder) => builder.AddSource("ActivitySourceName"));

// Add the Azure Monitor telemetry service to the application. This service will collect and send telemetry data to Azure Monitor.
builder.Services.AddOpenTelemetry().UseAzureMonitor();

// Build the ASP.NET Core application.
var app = builder.Build();

// Map a GET request to the root path ("/") to the specified action.
app.MapGet("/", () =>
{
    // Start a new activity named "CustomActivity". This activity will be traced and the trace data will be sent to Azure Monitor.
    using (var activity = activitySource.StartActivity("CustomActivity"))
    {
        // your code here
    }

    // Return a response message.
    return $"Hello World!";
});

// Start the ASP.NET Core application.
app.Run();

StartActivity defaults to ActivityKind.Internal, but you can provide any other ActivityKind. ActivityKind.Client, ActivityKind.Producer, and ActivityKind.Internal are mapped to Application Insights dependencies. ActivityKind.Server and ActivityKind.Consumer are mapped to Application Insights requests.

Send custom telemetry using the Application Insights Classic API

We recommend you use the OpenTelemetry APIs whenever possible, but there might be some scenarios when you have to use the Application Insights Classic API.

Events

  1. Add Microsoft.ApplicationInsights to your application.

  2. Create a TelemetryClient instance:

    Note

    It's important to only create once instance of the TelemetryClient per application.

    var telemetryConfiguration = new TelemetryConfiguration { ConnectionString = "" };
var telemetryClient = new TelemetryClient(telemetryConfiguration);

  3. Use the client to send custom telemetry:

    telemetryClient.TrackEvent("testEvent");

Modify telemetry

This section explains how to modify telemetry.

Add span attributes

These attributes might include adding a custom property to your telemetry. You might also use attributes to set optional fields in the Application Insights schema, like Client IP.

Add a custom property to a Span

Any attributes you add to spans are exported as custom properties. They populate the customDimensions field in the requests, dependencies, traces, or exceptions table.

To add span attributes, use either of the following two ways:

Tip

The advantage of using options provided by instrumentation libraries, when they're available, is that the entire context is available. As a result, users can select to add or filter more attributes. For example, the enrich option in the HttpClient instrumentation library gives users access to the HttpRequestMessage and the HttpResponseMessage itself. They can select anything from it and store it as an attribute.

  1. Many instrumentation libraries provide an enrich option. For guidance, see the readme files of individual instrumentation libraries:

  2. Use a custom processor:

    Tip

    Add the processor shown here before adding Azure Monitor.

    // Create an ASP.NET Core application builder.
var builder = WebApplication.CreateBuilder(args);

// Configure the OpenTelemetry tracer provider to add a new processor named ActivityEnrichingProcessor.
builder.Services.ConfigureOpenTelemetryTracerProvider((sp, builder) => builder.AddProcessor(new ActivityEnrichingProcessor()));

// Add the Azure Monitor telemetry service to the application. This service will collect and send telemetry data to Azure Monitor.
builder.Services.AddOpenTelemetry().UseAzureMonitor();

// Build the ASP.NET Core application.
var app = builder.Build();

// Start the ASP.NET Core application.
app.Run();

    Add ActivityEnrichingProcessor.cs to your project with the following code:

    public class ActivityEnrichingProcessor : BaseProcessor<Activity>
{
    public override void OnEnd(Activity activity)
    {
        // The updated activity will be available to all processors which are called after this processor.
        activity.DisplayName = "Updated-" + activity.DisplayName;
        activity.SetTag("CustomDimension1", "Value1");
        activity.SetTag("CustomDimension2", "Value2");
    }
}

Set the user IP

You can populate the client_IP field for requests by setting an attribute on the span. Application Insights uses the IP address to generate user location attributes and then discards it by default.

Use the custom property example, but replace the following lines of code in ActivityEnrichingProcessor.cs:

// Add the client IP address to the activity as a tag.
// only applicable in case of activity.Kind == Server
activity.SetTag("client.address", "<IP Address>");

Set the user ID or authenticated user ID

You can populate the user_Id or user_AuthenticatedId field for requests by using the following guidance. User ID is an anonymous user identifier. Authenticated User ID is a known user identifier.

Important

Consult applicable privacy laws before you set the Authenticated User ID.

Use the custom property example:

// Add the user ID to the activity as a tag, but only if the activity is not null.
activity?.SetTag("enduser.id", "<User Id>");

Add log attributes

OpenTelemetry uses .NET's ILogger. Attaching custom dimensions to logs can be accomplished using a message template.

Get the trace ID or span ID

You can obtain the Trace ID and Span ID of the currently active Span using following steps.

Note

The Activity and ActivitySource classes from the System.Diagnostics namespace represent the OpenTelemetry concepts of Span and Tracer, respectively. That's because parts of the OpenTelemetry tracing API are incorporated directly into the .NET runtime. To learn more, see Introduction to OpenTelemetry .NET Tracing API.

// Get the current activity.
Activity activity = Activity.Current;
// Get the trace ID of the activity.
string traceId = activity?.TraceId.ToHexString();
// Get the span ID of the activity.
string spanId = activity?.SpanId.ToHexString();

Next steps