[hinkley]

I did not find that manual instrumentation made things simpler. You’re trading a learning curve that now starts way before you can demonstrate results for a clearer understanding of the performance penalties of using this Rube Goldberg machine.

Otel may be okay for a green field project but turning this thing on in a production service that already had telemetry felt like replacing a tire on a moving vehicle.

[dmoy]

I've not used otel for anything not greenfield, but I just wanted to say

> felt like replacing a tire on a moving vehicle.

Some people do this as a joke / dare. I mean literally replacing a car tire on a moving vehicle.

You Saudi drift up onto one side, and have people climb out of the side in the air, and then swap the tire while the car is driving on two wheels.

It's pretty insane stuff: https://youtu.be/Str7m8xV7W8?si=KkjBh6OvFoD0HGoh

[hinkley]

That was the image I had in my head.

My whole career I’ve been watching people on greenfield projects looking down on devs on already successful products for not using some tool they’ve discovered, missing the fact that their tool only functions if you build your whole product around the exact mental model of the tool (green field).

Wisdom is learning to watch for people obviously working on brownfield projects espousing a tool. Like moving from VMs to Docker. Ansible to Kubernetes (maybe not the best example). They can have a faster adoption cycle and more staying power.

[PeterCorless]

SaS Institute used that exact same analogy & even this video in their talk about implementing ScyllaDB back in 2020 (check out 0:35 in the video):

https://www.scylladb.com/2020/05/28/sas-institute-changing-a...

Seems like moving to OTel might even be a bit more complex for some brownfield folks.