Logging traces in ASP.NET Core 2.0 with Application Insights

Application Insights (AI) is a great way to gather diagnostic information from your ASP.NET app, and with Core 2.0, itʼs even easier to get started. One thing that the tutorials don’t seem to cover is how to see your trace logs in AI. By “tracing”, I mean things like:

_logger.LogInformation("Loaded entity {id} from DB", id);

This can be an absolute life-saver during production outages. In simpler times, we might have used DebugView and a TraceListener to view this information (in our older, on-prem apps, we used log4net to persist some of this information to disk for more permanent storage). In an Azure world, this isn’t available to us, but AI in theory gives us a one-stop-shop for all our telemetry.

Incidentally, itʼs worth putting some care into designing your tracing strategy — try to establish conventions for message formats, what log levels to use when, and what additional data to record.

You can see the tracing data in the AI query view as one of the available tables:

tracing_table
The AI “traces” table

For our sample application, we’ve created a new website by using:

dotnet new webapi

We’ve then added the following code into ValuesController:

public class ValuesController : Controller
{
  private ILogger _logger;

  public ValuesController(ILogger<ValuesController> logger)
  {
    _logger = logger;
  }

  [HttpGet]
  public IEnumerable Get()
  {
    _logger.LogDebug("Loading values from {Scheme}://{Host}{Path}", Request.Scheme, Request.Host, Request.Path);
    return new string[] { "value1", "value2" };
  }
}

We have injected an instance of ILogger, and we’re writing some very basic debugging information to it (this is a contrived example as the framework already provides this level of logging).

Additionally, we’ve followed the steps to set our application up with Application Insights. This adds the Microsoft.ApplicationInsights.AspNetCore package, and the instrumentation key into our appsettings.json file. Now we can boot the application up, and make some requests.

If we look at AI, we can see data in requests, but nothing in traces (it may take a few minutes for data to show up after making the requests, so be patient). What’s going on?

By default, AI is capturing your application telemetry, but not tracing. The good news is that itʼs trivial to add support for traces, by making a slight change to Startup.cs:

public void Configure(IApplicationBuilder app, IHostingEnvironment env, ILoggerFactory logger)
{
  loggerFactory.AddApplicationInsights(app.ApplicationServices, LogLevel.Debug);
}

We have just added AI into our logging pipeline; the code above will capture all messages from ILogger, and, if they are at logging level Debug or above, will persist them to AI. Make some more requests, and then look at the traces table:

tracing_results1.PNG

One further thing that we can refine is exactly what we add into here. You’ll notice in the screenshot above that everything is going in: our messages, and the ones from ASP.NET. We can fine-tune this if we want:

loggerFactory.AddApplicationInsights(app.ApplicationServices, (category, level) =>
{
   return category.StartsWith("MyNamespace.") && level > LogLevel.Trace;
});

You’re free to do any filtering you like here, but the example above will only log trace messages where the logging category starts with one of your namespaces, and where the log level is greater than Trace. You could get creative here, and write a rule that logs any warnings and above from System.*, but everything from your own application.

Traces are one of the biggest life-savers you can have during a production issue — make sure that you donʼt lose them!

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