Gepsens

Hey look here guys it's cheap to do html !

What have I not understood ? Please enlighten me.

Seeing the comments in this thread makes me think about only one place in not so distant history : puritan England.

I find it astonishing that nowadays an unpolished product can go to IPO.

It's not the same. Data fusion comes with ballista, with the goal of replacing spark for many usages. It also supports JSON and Avro

Noise. I don't care if it slows down a bit, i don't want my computer to sound like a plane taking off when I'm compiling. Which is why I went from MBP to Air this year, and at home I use my huge radiator cooled desktop PC to work.

I prefer to use Intellij now for reviews. How can people review any kind of code in that PR web UI ? I mean I used to do it but not anymore

offline monitoring is what caused tchernobyl, when will ppl learn ?

I have a a server engine that runs a lot of small (and potentially unique) tasks (say 0.2% of 1vCPU and 30Mb of RAM), but require durable disk (rocksdb, sqlite for instance + some random files) and I want to locate them in specific regions depending on the server they are targeting. Would Cloudflare workers be good enough for that or shall I stick to DO's cheap vms ?

Yeah I'd stay away from these French platforms, except perhaps Clever Cloud.

Erm no, I really liked your post

You're a fricking genius.

In fact you aren't just perspicacious, the entire system uses actors in Rust.

Yeah currently for me there's no tool like Rust for performance, the borrow-checker isn't that complicated. However, last month I started adding a python wrapper around the public api so I'm slowly going your way ;)

I use terraform and ansible, one droplet has monitoring (prom and grafana), 2 run services that currently run without any other infrastructure The rest of the cost is a 250 gb space on DO

It's not a single droplet, it's 3 + data

And you are totally right

I'm running a crypto trading platform I'm developing on 30$ on DigitalOcean. I coded exclusively in Rust and recently added a dynamic interface to python. Today during the BTC crash it spiked at 20k events/s, and that's only incoming data.

I hope you are kidding mate. I've been solo maintaining 50k lines of Rust iterating over a few months and it's a breeze.

I mean, I'm on the client side, so I don't need a ledger to manage wallets, for now. But as the system evolves, I'll definitely need to 'allocate' budgets in the form of ledgers, where an algorithm decides to move funds from one account to another.

I'm actually building a crypto trading system from scratch (like gekko but more sophisticated). For now not as a SaaS, but even with a simple system, all the transactional problems occur quite fast. This is really interesting !

Hey Dave, I'm currently building a sound management app in electron right now. I used the electron react boilerplate on github. Can you tell me what advantage using todesktop would bring ?

Thanks !

Github profile : http://github.com/Igosuki

Hey dude; nice stuff. Just letting you know I can't auth with Google from the desktop version.

As a side comment, did you use anything outside of pure js on that Electron app ? It seems pretty neat and fast.

So much confusion between Exceptions and Errors in this thread. Exception abuse is for bad code that needs to return early, because they have no pattern matching, like Java and JavaScript. Nice languages have error handling, think Go, Elixir, Rust, Scala.

That's exactly what I went to solve 6 years ago, didn't work, but the space is probably more mature now

For me, etcd is the go to for dynamic configuration management.

"Linux, Git, node and Kubernetes" putting Kubernetes at the same level as Linux and Git... Not a pre-crafted commercial message from M$ at all guyze lul

How does the wallaroo roadmap compare to other ambitious frameworks such as Flink and Beam ? Haven't had much time to look at the API, are there tools to reason about both processing / event time ? Is it possible to save state and restart processes with updated code ?

Anyone who has worked with redis at scale knows exactly how the persistent queue approach of Kafka is far superior for any robust system that relies on the queue for truth and scales out (aka not your tiny crud app).

And Kafka is hard to deploy ? Please... If you deploy a redis cluster without knowing the pitfalls of distributed systems, you'll have the same problems as with Kafka. Also, soon enough you can deploy brokers over jbods without ZK, what will be the argument then I wonder...

Of course author would compare apples and oranges. Druid is a Time series oriented bucketed OLAP database, not a two dimensional metrics db like dalmatiner or influx.

While I like all of these databases they don't cover the same spaces.

This blog post is useless