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Earlier quoted context omitted.
this eliminates the ability to do a revert though if things don't work as expected at %100
I'm not doubting it's impossible, but I can't come up with any scenarios where something would work perfectly at 95% but then break at 100%. What could be some examples of things that can break like that?
Earlier quoted context omitted.
this eliminates the ability to do a revert though if things don't work as expected at %100
I'm not doubting it's impossible, but I can't come up with any scenarios where something would work perfectly at 95% but then break at 100%. What could be some examples of things that can break like that?
Most of the time this would happen, the difference between "95% of people can't see a posting" and "100% of people can't see a posting" would be pretty small, but I guess if the marketplace is very liquid the difference might actually be substantial. But unless you're uber or someplace like that, where there's a big difference between "95% of drivers can't see a ride request (so it takes slightly longer to find a driver)" and "100% of drivers can't see a ride request (so no driver is ever found)", I can't imagine too many cases where the difference is likely to make a practical difference.
Earlier quoted context omitted.
this eliminates the ability to do a revert though if things don't work as expected at %100
I'm not doubting it's impossible, but I can't come up with any scenarios where something would work perfectly at 95% but then break at 100%. What could be some examples of things that can break like that?
Earlier quoted context omitted.
I'm not doubting it's impossible, but I can't come up with any scenarios where something would work perfectly at 95% but then break at 100%. What could be some examples of things that can break like that?
This would assume that all types of activity are evenly distributed across all users. In practice, I've seen many things where a small, small subset of users are responsible for a disproportionate amount of volume, and the odds of all of them being in the 5% allocation of "old" code is higher than you'd think.
Earlier quoted context omitted.
This would assume that all types of activity are evenly distributed across all users. In practice, I've seen many things where a small, small subset of users are responsible for a disproportionate amount of volume, and the odds of all of them being in the 5% allocation of "old" code is higher than you'd think.
Assuming your rollout is truly randomised, I find it highly unlikely that an absolutely random 5% of your users (randomised everytime as well) are going to cause your fall. It's still possible, but I'm not giving up on an elegant idea for that reason.
Can someone point to a good write-up on how to introduce and start using feature flags in a repo? Seems like I just can't find any good resources on this topic!
Can someone point to a good write-up on how to introduce and start using feature flags in a repo? Seems like I just can't find any good resources on this topic!
If you're looking to try it out in a simple way, you could probably dynamically load different functionality or modules with environment variables. But I'm also looking for a good resource
Can someone point to a good write-up on how to introduce and start using feature flags in a repo? Seems like I just can't find any good resources on this topic!
If you're looking to try it out in a simple way, you could probably dynamically load different functionality or modules with environment variables. But I'm also looking for a good resource
Can someone point to a good write-up on how to introduce and start using feature flags in a repo? Seems like I just can't find any good resources on this topic!
One of the best ways to start is add a simple kill-switch to low-impact code. (More about that in the book.) But, I have to ask: what are the main issues that are blocking you from starting? Is it that you need ideas for cases, or are worried about breaking something, or just want to ensure best practices from the start?
We're constantly writing new guides, both as blog posts[2] and long-lived guide articles on our documentation site[3]. Feel free to message me on Twitter[4] if you need more help!
[1] https://launchdarkly.com/effective-feature-management-ebook/
[2] https://blog.launchdarkly.com/