Monday, April 20, 2020

How to profile ASP.NET apps using Application Insights

Application Insights can monitor, log, alert and even help us understand performance problems with our apps.
Photo by Marc-Olivier Jodoin on Unsplash
We've been discussing AppInsights in depth on this blog and to complete the series, I'd like to discuss the performance features it offers. On the previous posts, we learned how to collect, suppress and monitor our applictions using AppInsights data.

On this post let's understand how to use the performance features to identify and fix performance problems with our app.

What's profiling?

Wikipedia defines profiling as:
a form of dynamic program analysis that measures, for example, the space (memory) or time complexity of a program, the usage of particular instructions, or the frequency and duration of function calls. Most commonly, profiling information serves to aid program optimization.
Profiles usually monitor:
  • Memory
  • CPU
  • Disk IO
  • Network IO
  • Latency
  • Speed the of application
  • Access to resources
  • Databases
  • etc

Profiling ASP.NET Applications

ASP.NET developers have multiple ways of profiling our web applications, being the most popular: 
Those are awesome tools that definitely you should use. But today we'll focus on what can we do to inspect our deployed application using Application Insights.

How can Application Insights help

Azure Application Insights collects telemetry from your application to help analyze its operation and performance. You can use this information to identify problems that may be occurring or to identify improvements to the application that would most impact users. This tutorial takes you through the process of analyzing the performance of both the server components of your application and the perspective of the client so you understand how to:
  • Identify the performance of server-side operations
  • Analyze server operations to determine the root cause of slow performance
  • Identify slowest client-side operations
  • Analyze details of page views using query language

Using performance instrumentation to identify slow resources

Let's illustrate how to detect performance bottlenecks in our app with some some. The code for this exercise is available on my github. You can quickly get it by:
git clone https://github.com/hd9/aspnet-ai.git
cd aspnet-ai
git branch performance
# insert your AppInsights instrumentation key on appSettings.Development.json
dotnet run
This project contains 5 endpoints that we'll use to simulate slow operations:
  • SlowPage - async, 3s to load, throws exception
  • VerySlowPage - async, 8s to load
  • CpuHeavyPage - sync, loops over 1 million results with 25ms of interval
  • DiskHeavyPage - sync, writing 1000 lines to a file
 Running the tool and get back to azure. We should have some data there.

Performance Tools in AppInsights

Our AppInsights resource in Azure greets us with an overview page already that shows us consolidaded information about failed requests, server response time, server requests and availability:

Now, click on the Performance section. Out of the box, AppInsights has already captured previous requests and shows a consolidated view. Look below to already see our endpoints sorted out by duraction:

You should also have access to an Overall panel where you'd see requests per time:
There's also good stuff on the The End-to-end transaction details widget:

For example, we could click on a given request and  get additional information about it:

Tracing

We now know which are the slowest pages on our site, let's now try to understand why. Essentially, have two options:
  1. use AppInsights's telemetry api (as on this example) 
  2. or integrating directly to your logging provider, using System.Diagnostics.Trace on this case.

Tracing with AppInsights SDK

Tracing with AppInsights SDK is done via the TrackTrace method from TelemetryClient class an is as simple as:
public IActionResult Index()
{
    _telemetry.TrackPageView("Index");
    return View();
}

Tracing with System.Diagnostics.Trace

Tracing with System.Diagnostics.Trace is also not complicated but requires the NuGet package Microsoft.ApplicationInsights.TraceListener. For more information regarding other logging providers, please check this page. Let's start by installing it with:
dotnet add package Microsoft.ApplicationInsights.TraceListener --version 2.13.0

C:\src\aspnet-ai\src>dotnet add package Microsoft.ApplicationInsights.TraceListener --version 2.13.0
  Writing C:\Users\bruno.hildenbrand\AppData\Local\Temp\tmpB909.tmp
info : Adding PackageReference for package 'Microsoft.ApplicationInsights.TraceListener' into project 'C:\src\aspnet-ai\src\aspnet-ai.csproj'.
info : Restoring packages for C:\src\aspnet-ai\src\aspnet-ai.csproj...
(...)
info : Installing Microsoft.ApplicationInsights 2.13.0.
info : Installing Microsoft.ApplicationInsights.TraceListener 2.13.0.
info : Package 'Microsoft.ApplicationInsights.TraceListener' is compatible with all the specified frameworks in project 'C:\src\aspnet-ai\src\aspnet-ai.csproj'.info : PackageReference for package 'Microsoft.ApplicationInsights.TraceListener' version '2.13.0' added to file 'C:\src\aspnet-ai\src\aspnet-ai.csproj'.
info : Committing restore...
info : Writing assets file to disk. Path: C:\src\aspnet-ai\src\obj\project.assets.json
log  : Restore completed in 4.18 sec for C:\src\aspnet-ai\src\aspnet-ai.csproj.

Reviewing the results

Back in Azure we should now see more information about the performance of the pages:
And more importantly, we can verify that our traces (in green) were correctly logged:

Where from here

If you used the tools cited above, you now should have a lot of information to understand how your application performs on production. What next?

We did two important steps here: understood the slowest pages and added trace information to them. From here, it's with up to you. Start by identifying the slowest endpoints and add extra telemetry on them. The root cause could be in a specific query in your app or even on an external resource. The point is, each situation is peculiar and extends the scope of this post. But the essential you have: which are the pages, methods and even calls that take longer. On that note, I'd recommend adding custom telemetry data so you have a real, reproducible scenario.

Conclusion

On this post, the last on the discussion about AppInsights, we reviewed how Application Insights can be used to understand, quantify and report about the performance or our apps. Once again, AppInsights demonstrates to be an essential tool for developers using Azure.

More about AppInsights

For more information, consider reading my previous articles about App Insights:
  1. Adding Application Insights telemetry to your ASP.NET Core website
  2. Suppressing Application Insights telemetry on .NET applications
  3. Monitoring ASP.NET applications using Application Insights and Azure Alerts

References

See Also

Posted by
Labels: , , , , , , , , , , ,

Wednesday, April 1, 2020

Monitor ASP.NET applications using Application Insights and Azure Alerts

Using Application Insights? Learn how to trigger custom alerts for your application.
Photo by Hugo Jehanne on Unsplash

On this third article about Application Insights, we will review how to create custom alerts that trigger based on telemetry emitted by our applications. Creating Alerts on Azure is simple, cheap, fast and adds a lot of value to our operations.

Azure Alerts

But what are Azure Alerts? According to Microsoft:
Azure Alerts proactively notify you when important conditions are found in your monitoring data. They allow you to identify and address issues before the users of your system notice them.
With Azure Alerts we can create custom alerts based on metrics or logs using as data sources:
  • Metric values
  • Log search queries
  • Activity log events
  • Health of the underlying Azure platform
  • Tests for website availability
  • and more...

Customization

The level of customization is fantastic. Alert rules can be customized with:
  • Target Resource: Defines the scope and signals available for alerting. A target can be any Azure resource. For example: a virtual machine, a storage account or an Application Insights resource
  • Signal: Emitted by the target resource, can be of the following types: metric, activity log, Application Insights, and log.
  • Criteria: A combination of signal and logic. For example, percentage CPU, server response time, result count of a query, etc.
  • Alert Name: A specific name for the alert rule configured by the user.
  • Alert Description: A description for the alert rule configured by the user.
  • Severity: The severity of the alert when the rule is met. Severity can range from 0 to 4 where 0=Critical, 4=Verbose.
  • Action: A specific action taken when the alert is fired. For more information, see Action Groups.

Can I use Application Insights data and Azure Alerts?

Application Insights can be used as source for your alerts. Once you have your app hooked with Application Insights, creating an alert is simple. We will review how later on this post.

Creating an Alert

Okay so let's jump to the example. In order to understand how that works, we will:
  1. Create and configure an alert in Azure targeting our Application Insights instance;
  2. Change our application by creating a slow endpoint that will be used on this exercise.

To start, go to the Azure Portal and find the Application Insights instance your app is hooked to and click on the Alerts icon under Monitoring. (Don't know how to do it? Check this article where it's covered in detail).
And click on Manage alert rules and New alert rule to create a new one:

Configuring our alert

You should now be in the Create rule page. Here we will specify a resource, a condition, who should be notified, notes and severity. As previously, I'll use the same aspnet-ai AppInsights instance as previously:

Specifying a Condition

For this demo, we will be tracking response time so for the Configure section, select Server response time:

Setting Alert logic

On the Alert logic step we specify an operator and a threshold value. I want to track requests that take more than 1s (1000ms), evaluating every minute and aggregating data up to 5 minutes:

Action group

On the Add action group tab we specify who should be notified. For now, I'll send it only to myself:

Email, SMS and Voice

If you want to be alerted by Email and/or SMS, enter them below. We'll need them to confirm that notifications are sent to our email and phone:

Confirming and Reviewing our Alert

After confirming, saving and deploying your alert, you should see a summary like:

Testing the Alerts

With our alert deployed, let's do some code. If you want to follow along, download the source for this article and switch to the alerts branch by doing:
git clone https://github.com/hd9/aspnet-ai.git
cd aspnet-ai
git branch alerts

# insert your AppInsights instrumentation key on appSettings.Development.json
dotnet run
That code contains the endpoint SlowPage to simulate slow pages (and exceptions). To test it, make sure you have correctly set your instrumentation key and send a request to the endpoint at https://localhost:5001/home/slowpage and. It should throw an exception after 3s:

Reviewing the Exception in AppInsights

It may take up to 5 minutes to get the notifications. In the meantime, we can explore how AppInsights tracked our exception by going to the Exceptions tab. This is what was captured by default for us:
Clicking on the SlowPage link, I can see details about the error:

So let's quickly discuss the above information. I added an exception on that endpoint because I also wanted to highlight that without any extra line of code, the exception was automatically tracked for us. And look how much information we have there for free! Another reason we should use these resources proactively as much as possible.

Getting the Alert

Okay but where's our alert? If you remember, we configured our alerts to track intervals of 5 minutes. That's good for sev3 alerts but probably to much for sev1. So, after those long 5 minutes, you should get an easier alert describing the failure:
If you registered your phone number, you should also get an SMS. I got both with the SMS arriving a few seconds before the email.

Reviewing Alerts

After the first alert send, you should now have a consolidate view under your AppInsights instance where you'd be able to view previously send alerts group by severity. You can even click on them to get information and telemetry related to that event. Beautiful!

Types of Signals

Before we end, I'd like to show some of the signals that are available for alerts. You can use any of those (plus custom metrics) to create an alert for your cloud service.

Conclusion

Application Insights is an excellent tool to monitor, inspect, profile and alert on failures of your cloud resources. And given that it's extremely customizable, it's a must if you're running services on Azure.

More about AppInsights

Want to know more about Application Insights? Consider reading the following articles:
  1. Adding Application Insights telemetry to your ASP.NET Core website
  2. How to suppress Application Insights telemetry
  3. How to profile ASP.NET apps using Application Insights

References

See Also

For more posts about AppInsights, please click here.
Posted by
Labels: , , , , , , , , , , , , ,

About the Author

Bruno Hildenbrand      
Principal Architect, HildenCo Solutions.