Talking about stuff like this:
nodes =
node_data
|> Input.split_by_line(trim: true)
|> Enum.map(fn <<
t::binary-size(3),
" = (",
l::binary-size(3),
", ",
r::binary-size(3),
")"
>> ->
{t, {l, r}}
end)
|> Enum.into(%{})
Erlang knowledge is not needed for building products with Elixir at all unless you want to go very in-depth.
This argument lost me. If you’re running your own k8s install on top of servers, you’re doing it wrong. You don’t need highly specialized k8s engineers. Use your cloud provider’s k8s infrastructure, configure it once, put together a deploy script, and you never have to touch yaml files for typical deploys. You don’t need Lambda and the like to get the same benefits. And as a bonus, you avoid the premium costs of Lambda if you’re doing serious traffic (like a billion incoming API requests/day).
Every developer should be able to deploy at any time by running a single command to deploy the latest CI build. Here’s how: https://engineering.streak.com/p/implementing-bluegreen-depl...
From my experience Kubernetes is the most complex with most foot guns and most churn.
I'd argue between AWS serverless and AWS EKS fargate, the initial complexity is about the same. But serverless is a lot harder to scale cost efficiently and not accidentally go wild with function or sns loops.
idk what it is but when a new paradigm comes whether it is AI or AR the bigtech companies always want to ram it down everybody's throats rather than gentle opt-in. its not like they lack enthusiasts who WILL opt in to offer feedback.
you have billions of users, including many normies who just want to get shit done and dont even know that you have keynotes or shareholders to impress and dont care about the translucency of your "glass" when they're trying to call 911[0]
[0]: see talk (https://meyerweb.com/eric/thoughts/2016/01/25/designing-for-...) and tldr (https://hookedoncode.com/2015/02/designing-for-crisis-by-eri...)