In my last several presentations I briefly talked about using your tests as a monitoring tool. I've not been eating my own dog food and stuff failed in production!
What is monitoring via testing
This is a technique I coined 6 months ago while working with Tradeo's team. I'm not the first one to figure this out so if you know the proper name for it please let me know in the comments. So why not take a subset of your automated tests and run them regularly against production? Let's say every hour?
In my particular case we started with integration tests which interact with the product (a web app) in a way that a living person would do. E.g. login, update their settings, follow another user, chat with another user, try to deposit money, etc. The results from these tests are logged into a database and then charted (using Grafana). This way we can bring lots of data points together and easily analyze them.
This technique has the added bonus that we can cover the most critical test paths in a couple of minutes and do so regularly without human intervention. Perusing the existing monitoring infrastructure of the devops team we can configure alerts if need be. This makes it sort of early detection/warning system plus it gives a degree of possibility to spot correlations between data points or patterns.
As simple as it sounds I've heard about a handfull of companies doing this sort of continuous testing against production. Maybe you can implement something similar in your organization and we can talk more about the results?
Why does it matter
Anyway, everyone knows how to write Selenium tests so I'm not going to bother you with the details. Why does this kind of testing matter?
Do you remember a recent announcement by GitHub about Travis CI leaking some authentication tokens into their public log files? I did receive an email about this but didn't pay attention to it because I don't use GitHub tokens for anything I do in Travis. However as a safety measure GitHub had went ahead and wiped out my security tokens.
The result from this is that my automated upstream testing infrastructure had stopped working! In particular my requests to the GitHub API stopped working. And I didn't even know about it!
This means that since May 24th there have been at least 4 new versions of libraries and frameworks on which some of my software depends and I failed to test them! One of them was Django 1.11.2.
I have supplied a new GitHub token for my infra but if I had monitoring I would have known about this problem well in advance. Next I'm off to write some monitoring tests and also implement better failure detection in Strazar itself!
Thanks for reading and happy testing (in production)!