Neil Patel

I don't need to talk about it. I don't need to do those kinds of things. And so it actually helps on the hiring side as well, because. as people go through and new people want to join this group, you're looking at them with those eyes and you're like, hey, whether you're a junior, whether you're senior, do you have those same elements inside of you? And are you going to help make that team better?

I don't need to talk about it. I don't need to do those kinds of things. And so it actually helps on the hiring side as well, because. as people go through and new people want to join this group, you're looking at them with those eyes and you're like, hey, whether you're a junior, whether you're senior, do you have those same elements inside of you? And are you going to help make that team better?

I don't need to talk about it. I don't need to do those kinds of things. And so it actually helps on the hiring side as well, because. as people go through and new people want to join this group, you're looking at them with those eyes and you're like, hey, whether you're a junior, whether you're senior, do you have those same elements inside of you? And are you going to help make that team better?

Are you going to fill more gaps that we have in ability, et cetera, and also share and learn and all the things that we've been doing just naturally over this much time?

Are you going to fill more gaps that we have in ability, et cetera, and also share and learn and all the things that we've been doing just naturally over this much time?

Are you going to fill more gaps that we have in ability, et cetera, and also share and learn and all the things that we've been doing just naturally over this much time?

Definitely built to scale and scaling in mind. So what I'd say is our data store, it's not one binary thing. It's pieces. And we've put those pieces together inside of a cloud. And that's really the way we always thought about building Axiom, where the ingest can be isolated here, storage can be isolated here, search can be isolated, etc.,

Definitely built to scale and scaling in mind. So what I'd say is our data store, it's not one binary thing. It's pieces. And we've put those pieces together inside of a cloud. And that's really the way we always thought about building Axiom, where the ingest can be isolated here, storage can be isolated here, search can be isolated, etc.,

Definitely built to scale and scaling in mind. So what I'd say is our data store, it's not one binary thing. It's pieces. And we've put those pieces together inside of a cloud. And that's really the way we always thought about building Axiom, where the ingest can be isolated here, storage can be isolated here, search can be isolated, etc.,

We looked at it at the time and when we were whiteboarding stuff, we had to kind of circle things away and say, this is okay to deal with when we have users. And then there was other parts which were very clear where if we don't deal with this well now, it's just going to be painful for every X terabytes we would have extra. Like we can see that is such a clear pain point that's going to happen.

We looked at it at the time and when we were whiteboarding stuff, we had to kind of circle things away and say, this is okay to deal with when we have users. And then there was other parts which were very clear where if we don't deal with this well now, it's just going to be painful for every X terabytes we would have extra. Like we can see that is such a clear pain point that's going to happen.

We looked at it at the time and when we were whiteboarding stuff, we had to kind of circle things away and say, this is okay to deal with when we have users. And then there was other parts which were very clear where if we don't deal with this well now, it's just going to be painful for every X terabytes we would have extra. Like we can see that is such a clear pain point that's going to happen.

And so on our side, we tried to plan it in that way, which was this was OK to scale later, maybe because you can just throw machines at it initially and you don't need to worry as much. Or maybe it's just going to be a problem and we have to defer it for a while until someone's actually using it in angle, right? Instead of just us theoretically thinking people use it.

And so on our side, we tried to plan it in that way, which was this was OK to scale later, maybe because you can just throw machines at it initially and you don't need to worry as much. Or maybe it's just going to be a problem and we have to defer it for a while until someone's actually using it in angle, right? Instead of just us theoretically thinking people use it.

And so on our side, we tried to plan it in that way, which was this was OK to scale later, maybe because you can just throw machines at it initially and you don't need to worry as much. Or maybe it's just going to be a problem and we have to defer it for a while until someone's actually using it in angle, right? Instead of just us theoretically thinking people use it.

On the flip side, I touched on this with S3 and Lambda, thinking about how are we going to scale our ingest so we can write as many objects as we want to write into S3? What is the partitioning that works best for S3 on read? How do we avoid getting hot partitions, etc.? There's one thing changing a schema in a table, something really different changing the way a data store looks up blocks.

On the flip side, I touched on this with S3 and Lambda, thinking about how are we going to scale our ingest so we can write as many objects as we want to write into S3? What is the partitioning that works best for S3 on read? How do we avoid getting hot partitions, etc.? There's one thing changing a schema in a table, something really different changing the way a data store looks up blocks.

On the flip side, I touched on this with S3 and Lambda, thinking about how are we going to scale our ingest so we can write as many objects as we want to write into S3? What is the partitioning that works best for S3 on read? How do we avoid getting hot partitions, etc.? There's one thing changing a schema in a table, something really different changing the way a data store looks up blocks.

for querying, right? It's one of those things where you don't want to come in afterwards and actually play around too much with that. You can always make changes but you don't want to completely change it, especially once you have users. We anticipated those issues, but we definitely ran into things which we didn't. We found the edges of Lambda.

for querying, right? It's one of those things where you don't want to come in afterwards and actually play around too much with that. You can always make changes but you don't want to completely change it, especially once you have users. We anticipated those issues, but we definitely ran into things which we didn't. We found the edges of Lambda.