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In this article by James Singleton, author of the book,ASP.NET Core 1.0 High Performance,sheds some light on how to improve the performance of your web application by profiling and testing it. In this article, we will cover writing automated tests to monitor performance along with adding these to aContinuous Integration(CI) and deployment system by constantly checking for regressions.

(For more resources related to this topic, see here.)

Profiling and measurement

It’s impossible to overstate how important profiling, measuring, and analyzingreliable evidence is, especially when dealing with web application performance. Maybe you used Glimpseor MiniProfilerto provide insights into the running of your web application;or perhaps, you are familiar with the Visual Studio diagnostics tools and the Application InsightsSoftware Development Kit (SDK).

There’s another tool that’s worth mentioning and that’s the Prefix profiler, which you can get at prefix.io.Prefix is a free, web‑based,ASP.NET profiler thatsupports ASP.NET Core. However, it doesn’t yet support .NET Core (although this is planned),so you’ll need to run ASP.NETCore on .NET Framework 4.6, for now. There’s a live demo on their website (at demo.prefix.io) if you want to quickly check it out.

You may also want to look at the PerfView performance analysis tool from Microsoft, which is used in the development of .NET Core. You can download PerfView from https://www.microsoft.com/en-us/download/details.aspx?id=28567, as a ZIP file that you can just extract and run. It is useful to analyze the memory of .NET applications among other things.

You can use PerfView for many debugging activities, for example, to snapshot the heap or force GC runs. We don’t have space for a detailed walkthrough here, but the included instructions are good, and there blogs on MSDN with guides and many video tutorials on Channel 9 at channel9.msdn.com/Series/PerfView-Tutorial if you need more information.Sysinternals tools (technet.microsoft.com/sysinternals) can also be helpful, but as they are not focused on .NET, they are less useful in this context.

While tools such as these are great, what would be even better is building performance monitoring into your development workflow. Automate everything that you can and make performance checks transparent, routine, and run by default.

Manual processes are bad becausesteps can be skipped and errors can easily be made. You wouldn’t dream of developing software by e-mailing files around or editing code directly on a production server, so why not automate your performance tests too?

Change control processes exist to ensure consistency and reduce errors. This is why using a Source Control Management (SCM) system, such as git or Team Foundation Server (TFS) is essential. It’s also extremely useful to have a build server and perform Continuous Integration(CI) or even fully automated deployments.

If the code that is deployed in production differs from what you have on your local workstation, then you have very little chance of success. This is one of the reasons why SQL Stored Procedures (SPs/sprocs) are difficult to work with,at least without rigorous version control. It’s far too easy to modify an old version of an SP on a development database, accidentally revert a bug fix, and end up with a regression.If you must use sprocs, then you will need a versioning system such, as ReadyRoll (which Redgate has now acquired).

If you practice Continuous Delivery (CD),then you’ll have a build server, such as JetBrains TeamCity, ThoughtWorksGoCD, orCruiseControl.NET,or a cloud service, such as AppVeyor. Perhaps, you even automating your deployments using a tool, such as Octopus Deploy, and have your own internal NuGet feeds using software such as TheMotleyFool’s Klondike or a cloud service such as MyGet (which also supports npm, bower, and VSIX packages).

Bypassing processes and doing things manually will cause problems, even if you follow a script. If it can be automated, then it probably should be, and this includes testing.

Automated testing

As previously mentioned, the key to improving almost everything is automation. Tests thatare only run manually on developer workstations add very little value. It should of course be possible to run the tests on desktops, but this shouldn’t be the official result because there’s no guarantee that they will pass on a server (where the correct functioning matters more).

Although automation usually occurs on servers, it can be useful to automate tests running on developer workstations too. One way of doing this in Visual Studio is to use a plugin, such as NCrunch. This runs your tests as you work, which can be very useful if you practice Test-Driven Development (TDD) and write your tests before your implementations. You can read more about NCrunch and see the pricing at ncrunch.net, or there’s a similar open source project at continuoustests.com.

One way of enforcing testing is to use gated check-ins in TFS, but this can be a little draconian, and if you use an SCM-like git, then it’s easier to work on branches and simply block merges until all of the tests pass. You want to encourage developers to check-in early and often because this makes merges easier.Therefore, it’s a bad idea to have features in progress sitting on workstations for a long time (generally no longer than a day).

Continuous integration

CI systems automatically build and test all of your branches, and they feed this information back to your version control system. For example, using the GitHubAPI,you can block the merging of pull requests until the build server has reported success of the merge result.

Both Bitbucket and GitLab offer free CI systems called pipelines, so you may not need any extra systems in addition to one for source control because everything is in one place. GitLab also offers an integrated Docker container registry, and there is an open source version that you can install locally. Docker is well supported by .NET Core, and the new version of Visual Studio.You cando something similar with Visual Studio Team Services for CI builds and unit testing. Visual Studioalso has git services built into it.

This process works well for unit testing because unit tests must be quick so that you get feedback early.Shortening the iteration cycle is a good way of increasing productivity,and you’ll want the lag to be as small as possible.

However, running tests on each build isn’t suitable for all types of testing because not all tests can be quick. In this case, you’ll need an additional strategy so as not to slow down your feedback loop.

There are many unit testing frameworks available for .NET, for example NUnit, xUnit, and MSTest (Microsoft’s unit test framework), along with multiple graphical ways of running tests locally, such as the Visual Studio Test Explorer and the ReSharper plugin. People have their favorites, but it doesn’t really matter what you choose because most CI systems will support all of them.

Slow testing

Some tests are slow,but even if each test is fast they can easily add up to a lengthy time if you have a lot of them. This is especially true if they can’t be parallelized and need to be run in sequence.Therefore, you should always aim to have each test stand on its own, without any dependencies on others.

It’s good practice to divide your tests into rings of importance so that you can at least run a subset of the most crucial on every CI build. However, if you have a large test suite or some tests thatare unavoidably slow, then you may choose to only run these once a day (perhaps overnight) or every week (maybe over the weekend).

Some testing is simply slow by nature, and performance testing can often fall into this category, for example, load testing or User Interface (UI) testing. These are usually classed as integration testing, rather than unit testing, because they require your code to be deployed to an environment for testing, and the tests can’t simply exercise the binaries.

To make use of such automated testing, you will need to have an automated deployment system in addition to your CI system. If you have enough confidence in your test system, then you caneven have live deployments happen automatically. This works well if you also use feature switching to control the rollout of new features.

Realistic environments

Using a test environment that is as close to production (or as live-like) as possible is a good step toward ensuring reliable results. You cantry and use a smaller set of servers, and then scale your results up to get an estimate of live performance, but this assumes that you have an intimate knowledge of how your application scales, and what hardware constraints will be the bottlenecks.

A better option is to use your live environment or rather what will become your production stack. You first create a staging environment that is identical to live, then you deploy your code to it, and run your full test suite, including a comprehensive performance test, ensuring that it behaves correctly. Once you are happy, then you simply swap staging and production, perhaps using DNS or Azure staging slots.

Your old live environment now either becomes your test environment or if you use immutable cloud instances, then you can simply terminate it and spin up a new staging system. This concept is known as blue‑green deployment. You don’t necessarily have to move all users across at once in a big bang. You canmove a few over first to test whether everything is correct.

Web UI testing tools

One of the most popular web testing tools is Selenium, which allows you to easily write tests and automate web browsers using WebDriver. Selenium is useful for many other tasks apart from testing, and you can read more about it at docs.seleniumhq.org.

WebDriver is a protocol for remote controlling web browsers, and you can read about it at w3c.github.io/webdriver/webdriver-spec.html.

Selenium uses real browsers, the same versions your users will access your web application with. This makes it excellent to get representative results, but it can cause issues if itrunsfrom the command line in an unattended fashion. For example, you may find your test server’s memory full of dead browser processes, which have timed out.

You may find it easier to use a dedicated headless test browser, which while not exactly the same as what your users will see, is more suitable for automation. The best approach is of course to use a combination of both, perhaps running headless tests first and then running the same tests on real browsers with WebDriver.

One of the most well-known headless test browsers is PhantomJS. This is based on the WebKit engine, so it should give similar results to Chrome and Safari. PhantomJS is useful for many things apart from testing, such as capturing screenshots, and many different testing frameworks can drive it. As the name suggests,JavaScript can control PhantomJS, and you can read more about it at phantomjs.org.

WebKit is an open source engine for web browsers, which was originally part of the KDE Linux desktop environment. It is mainly used in Apple’s Safari browser, but a fork called Blink is used in Google Chrome, Chromium, and Opera. You can read more at webkit.org.

Other automatable testing browsers based on different engines are available, but they have some limitations. For example, SlimerJS (slimerjs.org) is based on the Gecko engine used by Firefox, but is not fully headless.

You probably want to use a higher-level testing utility rather than scripting browser engines directly. One such utility that provides many useful abstractions is CasperJS(casperjs.org),which supports running onboth PhantomJS and SlimerJS.

Another library is Capybara, which allows you to easily simulate user interactions in Ruby. It supports Selenium, WebKit, Rack, and PhantomJS (via Poltergeist), although it’s more suitable for Rails apps.You can read more at jnicklas.github.io/capybara.

There is also TrifleJS (triflejs.org), which uses the .NET WebBrowser class (the Internet Explorer Trident engine), but this is a work in progress. Additionally, there’s Watir (watir.com), which is a set of Ruby libraries that target Internet Explorer and WebDriver. However, neither have been updated in a while, and IE has changed a lot recently.

Microsoft Edge (codenamed Spartan)is the new version of IE, and the Trident engine has been forked to EdgeHTML.The JavaScript engine (Chakra) has been open sourced as ChakraCore (github.com/Microsoft/ChakraCore).

It shouldn’t matter too much what browser engine you use, and PhantomJS will work fine as a first pass for automated tests. You can always test with real browsers after using a headless one, perhaps with Selenium or with PhantomJS using WebDriver.

When we refer to browser engines (WebKit/Blink, Gecko, and Trident/EdgeHTML), we generally mean only the rendering and layout engine, not the JavaScript engine (SFX/Nitro/FTL/B3, V8, SpiderMonkey, and Chakra/ChakraCore).

You’ll probably still want to use a utility such as CasperJS to make writing tests easier, and you’ll likely need a test framework, such as Jasmine (jasmine.github.io) or QUnit (qunitjs.com), too. You can also use a test runner thatsupports both Jasmine and QUnit, such as Chutzpah (mmanela.github.io/chutzpah).

You can integrate your automated tests with many different CI systems, for example, Jenkins or JetBrains TeamCity. If you prefer a cloud-hosted option, then there’s Travis CI (travis-ci.org) andAppVeyor (appveyor.com), which is also suitableto build .NET apps.

You may prefer to run your integration and UI tests from your deployment system, for example, to verify a successful deployment in Octopus Deploy. There are also dedicated,cloud-based,web-application UI testing services available, such as BrowserStack (browserstack.com).

Automating UI performancetests

Automated UI tests are clearly great to check functional regressions, but they are also useful to test performance. You have programmatic access to the same information provided by the network inspector in the browser developer tools.

You can integrate the YSlow (yslow.org)performance analyzerwith PhantomJS, enabling your CI system to check for common web performance mistakes on every commit. YSlow came out of Yahoo!, and it provides rules used to identify bad practices, which can slow down web applications for users. It’s a similar idea to Google’s PageSpeed Insights service (which can be automated via its API).

However, YSlow is pretty old, and things have moved on in web development recently, for example, HTTP/2. A modern alternative is “the coach” from sitespeed.io, and you can read more at github.com/sitespeedio/coach.You should check out their other open source tools too, such as the dashboard at dashboard.sitespeed.io, which uses Graphite and Grafana.

You canalso export the network results (in industry standard HAR format) and analyze them however you like. For example, visualizing them graphically in waterfall format, as you might do manually with your browser developer tools.

The HTTP Archive (HAR) format is a standard way of representing the content of monitored network data to export it to other software. You can copy or save as HAR in some browser developer tools by right-clicking on a network request.


When using automation and techniques, such as feature switching, it is essential to have a good view of your environments so that you know the utilization of all the hardware. Good tooling is important to perform this monitoring, and you want to easily be able to see the vital statistics of every server. This will consist of at least the CPU, memory, and disk space consumption, but it may include more, and you will want alarms set up to alert you if any of these stray outside allowed bands.

The practice of DevOps is the culmination of all of the automation that we covered previously with development, operations, and quality assurance testing teams all collaborating. The only missing pieces left now are provisioning and configuring infrastructure and then monitoring it while in use. Although DevOps is a culture, there is plenty of tooling that can help.

DevOps tooling

One of the primary themes of DevOps tooling is defining infrastructure as code. The idea is that you shouldn’t manually perform a task, such as setting up a server, when you can create software to do it for you. You canthen reuse these provisioning scripts, which will not only save you time, but it will also ensure that all of the machines are consistent and free of mistakes or missed steps.


There are many systems available to commission and configure new machines. Some popular configuration management automation tools are Ansible (ansible.com), Chef (chef.io), and Puppet (puppet.com).

Not all of these tools work great on Windows servers, partly because Linux is easier to automate. However, you can run ASP.NETCore on Linux and still develop on Windows using Visual Studio, while testing in a VM. Developing for a VM is a great idea because it solves the problems in setting up environments and issues where it “works on my machine” but not in production.

Vagrant (vagrantup.com) is a great command line tool to manage developer VMs. It allows you to easily create, spin up, and share developer environments. The successor to Vagrant, Otto (ottoproject.io) takes this a step further and abstracts deployment too.Therefore,you can push to multiple cloud providers without worrying about the intricacies of CloudFormation, OpsWorks, or anything else.

If you create your infrastructure as code, then your scripts can be versioned and tested, just like your application code. We’ll stop before we get too far off-topic, but the point is that if you have reliable environments, which you can easily verify, instantiate, and perform testing on, then CI is a lot easier.


Monitoring is essential, especially for web applications, and there are many tools available to help with it. A popular open source infrastructure monitoring system is Nagios (nagios.org). Another more modern open source alerting and metrics tool is Prometheus(prometheus.io).

If you use a cloud platform, then there will be monitoring built in, for example AWS CloudWatch or Azure Diagnostics.There are also cloud servicesto directly monitor your website, such as Pingdom (pingdom.com), UptimeRobot (uptimerobot.com),Datadog (datadoghq.com),and PagerDuty (pagerduty.com).

You probably already have a system in place to measure availability, but you can also use the same systems to monitor performance. This is not only helpfulto ensure a responsive users experience, but it can also provide early warning signs that a failure is imminent. If you are proactive and take preventative action, then you can save yourself a lot of trouble reactively fighting fires.

It helps consider application support requirements at design time. Development, testing, and operations aren’t competing disciplines, and you will succeed more often if you work as one team rather than simply throwing an application over the fence and saying it “worked in test, ops problem now”.


In this article, we saw how wecan integrate automated testing into a CI system in order to monitor for performance regressions. We also learned some strategies to roll out changes and ensure that tests accurately reflect real life. We also briefly covered some options for DevOps practices and cloud-hosting providers, which together make continuous performance testing much easier.

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