this post was submitted on 30 Aug 2023
34 points (100.0% liked)

Experienced Devs

4008 readers
13 users here now

A community for discussion amongst professional software developers.

Posts should be relevant to those well into their careers.

For those looking to break into the industry, are hustling for their first job, or have just started their career and are looking for advice, check out:

founded 2 years ago
MODERATORS
snowe
jmk1ng
drewsiferr
34
How much flakiness do you tolerate in end to end tests? (self.experienced_devs)
submitted 1 year ago* (last edited 1 year ago) by kersplort to c/experienced_devs
22 comments fedilink hide all child comments
 

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?

you are viewing a single comment's thread
view the rest of the comments
[–] [email protected] 2 points 1 year ago

My org has issues with e2e, but we keep them because they usually inform that something, somewhere isn't quite right.

Our CI/CD pipeline is configured to automatically re-run a build if a test in the e2e suite fails. If it fails a second time, then it sends up the usual alerts and a human has to get involved.

In addition to that, we track transient failures on the main branch and have stats on which ones are the noisiest. Someone is always peeling the noisiest one off the stack to address why it's failing (usually time zones or browser async issues that are easy to fix).

It's imperfect, and still results in a lot of developers just spam retrying builds to "get stuff done", but we've decided the signal to noise ratio is good enough that we want to keep things the way they are.