Joe O'Pecko jopecko

Greasing the Skids: Building Remote Teams

In the wake of the virus that-must-not-be-named (which most people misname anyway), it seems like everyone and their cat has posted some sort of opinion or how-to on making remote work, work. This is a good thing! Working remotely, particularly full-time, is hard! I've done it for my entire career (aside from an odd 14 month office period in the middle that we shall not speak of), but more relevantly, for the past two years I've been responsible for building, managing, and enabling an entirely remote team, distributed across nine timezones. Remote teams don't just happen by installing Slack and telling everyone to work on their couch: they require a lot of effort to do correctly and efficiently. But, done right, it can be a massive multiplier on your team efficiency and flexibility.

Here's how we do it. I'm going to attempt to structure this post more towards management than engineering, and so I apologize in advance if I assume terminology or knowledge which

TL;DR

We should use a type parameter with a context bound (e.g. F[_]: Sync) in library code so users can choose their IO monad, but we should use a concrete IO monad in application code.

Abstracting over IO

If you're writing a library that makes use of effects, it makes sense to use the cats-effect type classes so users can choose their IO monad (IO, ZIO, Monix Task, etc).

So instead of

Pixelbook or Pixel Slate Setup

Partly updated June 2023

General caution: Chrome OS is a secure OS by design, but this has at least one key consequence. If you change your Google account password, you will still be required to enter the old password the next time you access each Chrome OS device. Devices are encrypted with that password, so the OS needs to decrypt using the old password then re-encrypt using the new one. If you forget your old password you will lose access to your Chrome OS device data. As always, make sure you keep backups up to date.

Fast User Switching

If you have multiple Chrome OS accounts (Say, work and play), you can quickly sitch between them without logging out:

Thread Pools

Thread pools on the JVM should usually be divided into the following three categories:

CPU-bound
Blocking IO
Non-blocking IO polling

Each of these categories has a different optimal configuration and usage pattern.

Scaling your API with rate limiters

The following are examples of the four types rate limiters discussed in the accompanying blog post. In the examples below I've used pseudocode-like Ruby, so if you're unfamiliar with Ruby you should be able to easily translate this approach to other languages. Complete examples in Ruby are also provided later in this gist.

In most cases you'll want all these examples to be classes, but I've used simple functions here to keep the code samples brief.

Request rate limiter

This uses a basic token bucket algorithm and relies on the fact that Redis scripts execute atomically. No other operations can run between fetching the count and writing the new count.

What I Wish I'd Known About Equity Before Joining A Unicorn

Disclaimer: This piece is written anonymously. The names of a few particular companies are mentioned, but as common examples only.

This is a short write-up on things that I wish I'd known and considered before joining a private company (aka startup, aka unicorn in some cases). I'm not trying to make the case that you should never join a private company, but the power imbalance between founder and employee is extreme, and that potential candidates would

	# INSTRUCTIONS:
	# 1. Follow the installation instructions at
	# https://nixos.org/nixos/manual/index.html until
	# /mnt/etc/nixos/configuration.nix is edited
	# 2. Replace that file with this one:
	# -> curl -L -o /mnt/etc/nixos/configuration.nix https://go.nzbr.de/zoomvm
	# 3. You will need to edit this configuration if you want a locale other than
	# german (i18n and xserver.locale) or not use UEFI (boot.loader)
	# 4. Run `nix-env -i git` to install git on the live system (may take some time)
	# 5. Run nixos-install

	import io.estatico.newtype.ops._
	import io.estatico.newtype.macros.newtype
	import eu.timepit.refined.api.Refined
	import doobie.implicits._
	import doobie.postgres.implicits._
	import doobie.refined.implicits._

	/**
	* Derive a Put (so it can be interpolated in doobie sql expressions) for any newtype backed by a type that is
	* supported by doobie (e.g. any wrapper of String, UUID, Boolean etc)

	package fpmax

	import scala.util.Try
	import scala.io.StdIn.readLine

	object App0 {
	def main: Unit = {
	println("What is your name?")

	val name = readLine()

	/*
	This snippet is an example of backpressure implementation in Go.
	It doesn't run in Go Playground, because it starts an HTTP Server.

	The example starts an HTTP server and sends multiple requests to it. The server starts denying
	requests by replying an "X" (i.e. a 502) when its buffered channel reaches capacity.

	This is not the same as rate-limiting; you might be interested in https://github.com/juju/ratelimit
	or https://godoc.org/golang.org/x/time/rate.