You know, it's a great question and I think in my personal opinion, the thing that matters most at every scale is the product, right? Data doesn't matter if you don't have a product or like if you're selling something, if it's B2B, B2C, whatever.
I would let that be the driver, the way I look at things nowadays, is scale when you need to. I think that's why these managed services are amazing because they work zero to one and one to a hundred. Maybe they don't work to a thousand or 10,000, you know, and I'm talking, when I talk scale, then its factors.
I would argue at every factor you should just deal with the scale when it comes. You know, I think what was it, Knuth that basically said like premature optimization is like the worst thing you can do effectively. And arguably I think that is actually the pitfall that many people fall into is we think we can get ahead of the game and predict it. It's pretty rare, right? Even if, let's say you go hire a senior engineer who had done way more scale or whatever, and they come in and you're like, Hey, I want you to prep for X, Y, or Z. Well, what you still don't know is whether you're actually gonna hit X, Y, or Z scale. And you may end up wasting effectively those resources, right?
Everything comes down to money at the end of the day. And while it'd be great to be prepared for it, if it never comes that's probably a worse problem than if it does come and then you kind of need to put some band-aids on it. Or to the same point, there are a number of managed services that can handle the scale for what is a lot less price than to go off and run your own whatever, build your own X, Y, Z thing that is exponentially more, more cost-prohibitive, I think in the moment.
Like it's not gonna come out well on your balance sheet for many years. And again, so I think taking that risk is almost in my mind nowadays just not worth it. It's better to start with a bunch of managed services or a lot of these the vendor solutions and things.
I think they work great. Personally, I wish vendors and these other companies had a better relationship to know when their scale ended and you could say- hey it's not for us anymore, you know, and it unfortunately you have to go through that sad divorce which doesn't always work out super well.
But I think at the end of the day, that's, that in my mind is what I would advise everyone. Scale when you're there, right? Don't scale thinking you're gonna be there. I guess the other caveat I will say is for Lyft, we've done a lot of work in effectively simulating our ride volume.
So one thing that I can say is basically it's a giant performance stress test on all of our services, microservices, API data platform, et cetera. And I think, that allows us to handle peak loads when they happen. I think as you're looking towards scale and you need to be at least dynamic to handle these random peaks, those are the next kind of worlds that you would want to invest in. Then that'll usually shed light on areas in which you can go focus on.