End to end and smoke tests give a really valuable angle on what the app is doing and can warn you about failures before they happen. However, because they’re working with a live app and a live database over a live network, they can introduce a lot of flakiness. Beyond just changes to the app, different data in the environment or other issues can cause a smoke test failure.
How do you handle the inherent flakiness of testing against a live app?
When do you run smokes? On every phoenix branch? Pre-prod? Prod only?
Who fixes the issues that the smokes find?
My team has just decided to make working smokes a mandatory part of merging a PR. If the smokes don’t work on your branch, it doesn’t merge to main. I’m somewhat conflicted - on one hand, we had frequent breaks in the smokes that developers didn’t fix, including ones that represented real production issues. On the other, smokes can fail for no reason and are time consuming to run.
We use playwright, running on github actions. The default free tier runner has been awful, and we’re moving to larger runners on the platform. We have a retry policy on any smokes that need to run in a step by step order, and we aggressively prune and remove smokes that frequently fail or don’t test for real issues.
Shouldn’t you find out, why the smoke tests keep failing? It’s not a good sign, if you can’t even guarantee stability in a controlled environment.
I think/hope that the wording you used was a mistake.
End to end tests do not introduce flakiness, but uncover it.
Whenever we discover flakiness, we try to fix it immediately. When there is no time for the fix (which is more than often the case) we create a ticket that vanishes in the backlog.
For a long time the company I currently work at didn’t have end to end tests save unit tests for a lot of their code.
Through a push of newcomers we finally managed to add end to end tests to many more parts of the code. However, these are still not properly documented. Some end to end tests overlap and some only cover a small part of one larger functionality. That is why we often find bugs that were introduced by us, because we had no end to end tests covering those parts.
We used to run end end tests only every night on the whole product. They usually take an hour or more to complete. This takes too long to run them before each merge. However, we have them organized enough such that for sub-product A we can run the sub-product A end to end tests only before each merge where we assume that we did only touch code affecting sub-product A. In case the code changes affected some other parts of the product, the nightly tests help us out. We are doing this in my team for a long while now. But we just recently started to establish this procedure in the other teams of the company, too.
You run E2E test before each merge. So, you don’t merge very often?
How about running an integration test before each merge instead of a full fledged E2E and mocking out external dependencies (other services) during the test, then do E2E testing on a schedule like nightly?
I prefer it this way, because mocking out external dependencies cut out network instability and bugginess from dependencies. So, we can merge faster. Agree that test scenarios are overlapping, and if your E2E is very stable then it is probably not worth it, but unfortunately it’s not so stable in my environment.
Luckily, our e2e tests are pretty stable. And unfortunately we are not given the time to write integration tests as you describe. The good thing would be that with these mocks we were then also be able to load test single services instead of the whole product.
We merge multiple times a day and run only those e2e tests we think are relevant. Of course, this is not optimal and it is not too rare that one of the teams merges a regression, where one team or more talented at that than the others.
You see, we have issues and we realize we have them. Our management just thinks these are not important enough to spend time on writing integration tests. I think money and developer time are two of the reasons, but the lack of feature documentation, the lack of experts for parts of the codebase (some already left for another employer), and the amount of spaghetti code and infrastructure we have are other important reasons.
Reading the 3rd paragraph and I see myself 😄. Glad that you and the team managed to add another layer of testing successfully.