Q Thank you very much. So using Kafka and Elastic, that's awesome if you have a really strong tech team. Did you guys think about this, I guess, in terms of alternatives to, you know, for something that would be simpler, and why did you choose those?
A Well, so one thing I'll say is that what's been challenging for us from kind of the get-go Uh, when we add new technologies is having to do it at a large scale. So if we're gonna, when we first put our Kafka cluster in, I mentioned we started this in 2016 with Currents, um, that was actually the first, uh, use of Kafka for us. Um, we'd already been around for five years doing a lot of other stuff. So we said, okay, as soon as we turn this on, we're gonna be sending, like, hundreds of billions of events through it. It needs to kind of scale. Um, so the, we went into it pretty cautiously because we said, like, we can't go Halfway. We're going to have to turn it on full throttle. Um, but we are looking at things of how can we get quick wins, um, through managed services. So that's actually why we started the Elastic Hash service. This diagnostic project, uh, actually started off, um, as a series of hack days to see how far we could kind of get this going, um, with like minimal kind of work. And we were able to put it into Amazon, um, and then we ran out of disk space, um, and then we overwhelmed it. Uh, and then we ran out of Elasticsearch nodes and had to increase our, our limit of more instances, and it was just like a whole thing. But we are evaluating ways in which we can use other services to just get us off the ground faster, um, and then manage it only kind of when we need …
AI assessment note: “we are looking at things of how can we get quick wins, um, through managed services.”