LaunchDarkly gets $8.7M to put the right features in front of right users
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Re: LaunchDarkly gets $8.7M to put the right features in front of right users
#2Feature Flags FTW!
Re: LaunchDarkly gets $8.7M to put the right features in front of right users
#3Feature Flags FTW!
Pretty much. The issue now is, can I implement feature flags faster than I can implement the LaunchDarkly API?
I think I can do feature flags faster.
Re: LaunchDarkly gets $8.7M to put the right features in front of right users
#4Anyone using LaunchDarkly, and willing to comment on the experience?
Code-wise, this seems like a pretty straightforward problem. I'm surprised there aren't more competitors.
Re: LaunchDarkly gets $8.7M to put the right features in front of right users
#5They should incorporate ML options too. They have multivariate testing + goal/conversion measurement, they should have multi-armed bandit ML methods as an option (epsilon-greedy, bayesian bandit etc).
Re: LaunchDarkly gets $8.7M to put the right features in front of right users
#6Not to take away from the fact that this is a very useful tool, but every time I have wanted this, I have built it myself. My general strategy is to store flags in the user's data and for A/B testing, randomly assign A% of users to have a certain flag set. Then somewhere in the admin dashboard I'll drop a set of switches/buttons for activating flags and running A/B testing scripts. Collecting test results is simply modifying the database query to only include users that had the flag set.
An external service for boolean flags seems a bit overkill to me.
Edit: I read the first comment, looked at the features, and read the case studies: I am guilty of vastly oversimplifying what this does. The value proposition is still not right for my particular business, but at my previous job at Big Company, we had a custom rollout dashboard that didn't have most of these features (targeting groups, percentage rollout), and it still saved us many hours of development time.
Re: LaunchDarkly gets $8.7M to put the right features in front of right users
#7Feature Flags FTW!
Pretty much. The issue now is, can I implement feature flags faster than I can implement the LaunchDarkly API? I think I can do feature flags faster.
Can you implement analytics on top of those flags, plus a nice UI for nontechnical employees to toggle them faster? If you don't need those, then you probably aren't in their target audience.
Disclaimer: no relation, just playing devil's advocate.
Re: LaunchDarkly gets $8.7M to put the right features in front of right users
#8Not to take away from the fact that this is a very useful tool, but every time I have wanted this, I have built it myself. My general strategy is to store flags in the user's data and for A/B testing, randomly assign A% of users to have a certain flag set. Then somewhere in the admin dashboard I'll drop a set of switches/buttons for activating flags and running A/B testing scripts. Collecting test results is simply m…
I hate to oversimplify something I don't know details on, but that's what popped into my mind as well. Just put an intern on it?
Obviously is must be more impressive than it sounds - people wrote 9 million in checks.
Re: LaunchDarkly gets $8.7M to put the right features in front of right users
#9They should incorporate ML options too. They have multivariate testing + goal/conversion measurement, they should have multi-armed bandit ML methods as an option (epsilon-greedy, bayesian bandit etc).
As a matter of fact, we have experimented with multi-armed bandit 'auto-pilot' to roll out a new feature while watching A/B test results. I'd like to see this make it to production as well; it was one of those things that sounded like a fun idea, but we weren't sure if actual customers would use it :).
nb: I work for LaunchDarkly, if it wasn't obvious from my comment.
Re: LaunchDarkly gets $8.7M to put the right features in front of right users
#10We've used LaunchDarkly (LD) for about a year now. We previously used our own Feature Flag library built by our CTO: https://www.npmjs.com/package/dipswitch. LD provided a lot more, and continues to release new features that would've been much more expensive for us to build vs. buy here.
We’ve been so pleased w/ LD that we agreed to do a case study with them if you want to take a gander: https://launchdarkly.com/casestudies/lanetix.html
Also, we implemented most of LD in a 24-hour quarterly hackathon we hold at my company: https://engineering.lanetix.com/2016-02-22/how-lanetix-does-...
Hope this helps!