I'm confused as to why this is an anti-pattern? My understanding is that the CI pipeline should run unit tests and linting for every commit. But at the same time, developers should run their tests before pushing code.
Of course the CI should always run them, but that should normally be as a confirmation/safeguard.
I've seen too many cases where the devs wouldn't even run the code locally. They would push it and expect the CI to do all the work. That's how you get shitty CI that is always broken.
If you allow devs to push directly on release branch, thus breaking the CI, you’re absolutely doing it wrong.
Of course you can do it like you said but that means longer feedback loops in general. If the team wants to integrate more often and reduce feedback loops then that model evolves.
I'll give you an example. In the team I mentioned in my top comment we were initially using a branching model with master, releases/, hotfixes/, dev, features/, which gradually evolved into master, dev, features/, which finally ended up as master, features/*. With the important mention that for small changes/fixes that needed to get deployed quickly nobody would bother with a branch they would just push to master.
This allowed us multiple production deploys per day per developer with no risk. That's why I said I don't get the point of the article, you can absolutely get those short feedback loops and continuous integration if you want it, just need to setup the process that way.
Longer feedback loops =/= long feedback loops. You can definitely wait 5 to 10 minutes if it means doing it right.
> With the important mention that for small changes/fixes that needed to get deployed quickly nobody would bother with a branch they would just push to master.
From my experience, the 1-2 lines fixes are the ones that benefit the most from automated CI because you’re doing it in a rush. In my team just last week a junior dev asked us to review their PR quickly because it was just 2 lines, and it didn’t even compile. We told them to be more careful in the future, but in the end it didn’t impact anything. It couldn’t possibly have impacted anything thanks to CI, it just makes it impossible to fuck up too recklessly.
I agree with you though.
Not that I don't see the value proposed by TBD, but I think you can have >90% of said value and none of the downsides using a well thought out branching strategy.
[0] Trunk-Based Development: https://trunkbaseddevelopment.com/
> Depending on the team size, and the rate of commits, short-lived feature branches are used for code-review and build checking (CI). [...] Very small teams may commit direct to the trunk.
Sometimes TBD is the answer, sometimes you need something else.
What I did notice is that, with time, mature teams end up simplifying processes in order to reduce friction and increase output.
Lazy devs are going to be lazy no matter what processes their team uses.
It does take some extra work though, because GH and others don't really support this out of the box.
[0]: https://docs.gitlab.com/ee/ci/pipelines/merged_results_pipel...
My issue with this approach is that it becomes tricky to scale since you can only have one job running at a time. Allowing master to potentially break scales better because you can run a job for each commit on master which hasn't been evaluated. Technically you could make that approach work by instead of rebasing onto master rebasing onto the last commit that is being tested, but this adds extra complexity which I don't think standard tooling can easily handle.
https://zuul-ci.org/ and some other systems solve it by optimistic merges. If there's already a merge job running, the next one assumes that will succeed. And tests on merged master + first change + itself. If anything breaks, the optimistic merges are dropped from the queue and everything starts from the second chance only. Openstack uses it and it works pretty well if the merges typically don't fail.
The solution is to require that all PR must be rebased/synced to master before they can be merged. GitHub has an option for enforcing this. The downside is that this often results in lots of re-running of tests.
> something even more continuous than continuous integration. It might look like real-time integration of your changes, collaborative editing, or smarter build systems that produce near-live feedback
e.g. https://medium.com/darklang/how-dark-deploys-code-in-50ms-77...
I can have the normal flow, which takes minutes and runs all the tests and other stuff I might have on my pipeline (security, performance, etc). I use this for typical day to day work on features. I don't care if the deploy takes 50ms or 5 minutes.
I can have a fast-track for critical production patches. I skip all the main CI steps and just get my code quickly in production. If done right this takes seconds.
I didn't know about dark but I've seen this type of promise too many times, so I'm pretty sure there are many tradeoffs hidden under the nice shiny exterior. I can't know until I try it, but that kind of complexity doesn't all just disappear, i always has a cost even if it's out of sight.
Perhaps some of those teams and individuals are experts at determining the correct, minimal continuous integration suite to run on a per-commit basis to minimize time and energy expenditure without compromising correctness.
But I can guarantee that not all (in fact, not many) are, and that they pay maintenance and mental overheads to adhere to those practices.
It feels to me like there is a potentially massive opportunity to design an integrated language-and-infrastructure environment that only re-runs necessary checks based on each code diff.
- "Altered a single-line docstring in a Python file? OK, the data-flow from that infers a rebuild of one of our documentation pages is required, let's do that... done in 2ms"
- "Refactored the variable names and formatting within a C++ class without affecting any of the logic or ABI? OK, binary compatibility and test compatibility verified as unchanged, that's a no-op... done in 0ms"
- "Renamed the API spec so that the 'Referer' header is renamed 'Referrer'? OK, that's going to invalidate approximately a million downstream server and client implementations, would you like to proceed?"
(examples are arbitrary and should imply no specific limitations or characteristics of languages or protocols)
Doing this effectively would require fairly tight coupling between the syntax of the language, ability to analyze dataflows relating to variables and function calls, cross-package dependency management, and perhaps other factors.
Those properties can be achieved during design of a programming language, or they can iteratively be retrofitted into existing languages (with varying levels of difficulty).
Bazel[1] attempts to achieve much of this, although to my understanding it offloads a lot of the work of determining (re)build requirements onto the developer - perhaps a necessary migration phase until more languages and environments provide formats that have self-evident out-of-date status and dependency graphs.
We'll get there and the (sometimes uneasy) jokes will be about how often the software industry used to re-run huge continuous integration pipelines.
What happens is that people don't understand that most of these higher level solutions are very leaky abstractions, they aren't the silver bullet marketed in medium articles. Yes, they can save you a lot of time and headaches in specific scenarios but when you encounter one of the leaks it can take you weeks to get to the bottom of it.
If the teams doesn't understand what problems the tool is solving and if they have that problem then they might be just cargo-culting. An example of this is kubernetes. I know teams that used kubernetes just because everybody else is using it, they didn't actually need it for their monolithic java spring app. They think they avoided accidental complexity by using kubernetes but in fact they just added accidental complexity to their project. And then they add a new tool that makes it easier to manage the complexity of kubernetes, and so on.
Anyway, I'm probably just a rambling fool and I should appreciate that all this generating and shifting around of accidental complexity will actually mean future job safety for guys like us.
Of course there are many pitfalls. Like with any tool it becomes trivial to use it wrong. Integrating less than once per day and deferring all testing and linting to the CI process is an anti-pattern and the issue is not the CI process but how the team chooses to use it.
For example I worked in a team of 10 and we were doing multiple production deploys per day. This was made possible by a great CI workflow. Everyone was running tests precommit and focusing on keeping the pipeline green. Yes I've seen the opposite as well, but that usually is a symptom of issues with the team not the general concept of CI.
Not saying that there isn't room for improvement but all the real-time collaboration features I used on low-code platforms feel like a step back.