So here is what's hopefully just the first in a series of blog posts I'll be doing on the topic, and I look forward to hearing your feedback.

www.honeycomb.io/blog/data-st...

And there's so little cross-functional knowledge sharing between the SRE and Data worlds, it's like they live on two different planets! It turns out that the Data folks have a many-year head start, particularly when it comes to formalizing data practices that Observability systems desperately need

The Observability 2.0 paradigm shift was a shock to many, coming from the metrics & logs world, suddenly being exposed to a richness of data and analytical capabilities they'd never had before in their careers.

At the same time, my day job was helping, studying, and learning from Honeycomb's customers in their Observability data practices.

After a major pricing project, I declared, "we are never doing it like this again" and justified a little budget to build our initial Data stack (Snowflake, Mode, Fivetran, dbt, and Census).

Back in 2020, I was leading and building out our nascent Customer Success team, and we were all drowning in a sea of data. There was no shortage of inputs, being SaaS, across all our tools as well as our own DBs, but it was being pulled together through spreadsheets.

Oh the strawmanity!

Hello!! 👋

Will follow on with some Mogwai

I’m in this post and I don’t like it

Thank you!

Thanks!!