[wwwpatdelcom]

As a both devops and ML professional at my job (it's a small company), I viscerally cringe at the same kurtosis for this company (which I just learned about). There could be some kind of latent jealously/projection causing that cringe, but here's my rationale (could be very specific to my career):

* Devops folks don't seem to tend to like math and often got there by practicing, "computers, IT, having fun hooking things together and getting them running."

* Data science folks don't tend to like devops and prefer to bash around on a jupyter notebook that's already given to them and then maybe extract that python and see if it runs, but they tend to come from more of a science background and got into python as a hobby or incidentally. They do not like bashing around and getting things running.

So now this company is combining a math term that has a specific meaning to an ML ops space, which is going to cause confusion.

Different sets of data can have different kurtosis measures. Sets can be platykurtic (flat gaussian curve or high kurtosis) or leptokurtic (tall gaussian curve, low kurtosis).

Now this company is coming in and telling a bunch of devops people, "Kurtosis means helm but automatically migrate data too." So they are applying the idea of, "leptokurtic deployments," presumably with the metric being, variation between the code and data parameters on those servers. Data science people who are told about it from devops people are going to initially hear, "somehow dealing with cleaning the data, like an ETL pipeline, perhaps an Airflow with data cleaning tools built in or something."

It's very confusing and not helpful to customers, I hate it. There are going to be meetings where ML/Devops people are very confused.

Naming is hard though -- but I wish they would have gone with something like, "platypus" and just have a cute little platypus baby as the logo and say, "yeah we liked the word platykurtic because we like making things regular and platykurtic sounds like platypus."

[galenmarchetti]

Hi! Founder here…thanks for the feedback, deeply appreciate it. Especially the last bit about how hard naming is haha.

To give a bit of context on the name, our first set of use cases was all about test engineers using this tool to testbeds for end to end or large scale integration tests.

Since we are pretty mathy ourselves, we called it “Kurtosis” because we imagined the distribution of errors arising from service to service interactions to have a high Kurtosis - in the sense that there’s a lot of errors you wouldn’t “expect” to happen from a first principles understanding of each component. You’d have put them all together to see those, they’d be “far off the mean”. There’s also a lot of stuff about how we view our work, where we like exposing ourselves to outlier opportunities that we hadn’t previously imagined to produce results that would only happen in a “high Kurtosis results distribution”.

Now that being said, I definitely hear what you’re saying. It’s not obvious that’s where the name came from…and just because we were thinking that when we named it doesn’t mean it resonates with our users the same way!

[wwwpatdelcom]

That feedback came straight from my basal ganglia.

Though I'm guessing that was a pretty expensive domain name. So in lieu of changing it, on this issue I can be bought off.

But I will accept a bribe in the form of a medium sized T-Shirt to not make fun of you further. The T-Shirt must include an anthropomorphized gaussian curve in a math meme format and the curve-person must be clearly labeled as being name, "Kurt Osis."

Any Kurtosis logo must be either non-existent or super non-prominent so that I can at least pretend that it's a meme and then maybe tail into where it came from. A huge emblazoned Kurtosis logo on the back or front will be unacceptable (although Kurt Osis could have that logo on his or her or their shirt).

[SpaceNoodled]

It's not too late to rebrand with the cute platypus idea.

[rdtsc]

> * Devops folks don't seem to tend to like math and often got there by practicing, "computers, IT, having fun hooking things together and getting them running." * Data science folks don't tend to like devops and prefer to bash around on a jupyter notebook that's already given to them and then maybe extract that python and see if it runs, but they tend to come from more of a science background and got into python as a hobby or incidentally. They do not like bashing around and getting things running.

Everyone likes cool sounding terms though! Any such term will eventually end up being co-opted. We have isomorphic Javascript and all kinds of stuff like that.

Not saying it’s good or bad, it will just happen.

Are customers really going to be confusing a CI system vs a data statistic? It’s a bit like being confused about apple the fruit and an Apple iPhone. The confusion will clear up pretty quickly.