Gabriel Francisco gabfssilva

Referências sobre diversidade

Curadoria

Understanding Comparative Benchmarks

I'm going to do something that I don't normally do, which is to say I'm going to talk about comparative benchmarks. In general, I try to confine performance discussion to absolute metrics as much as possible, or comparisons to other well-defined neutral reference points. This is precisely why Cats Effect's readme mentions a comparison to a fixed thread pool, rather doing comparisons with other asynchronous runtimes like Akka or ZIO. Comparisons in general devolve very quickly into emotional marketing.

But, just once, today we're going to talk about the emotional marketing. In particular, we're going to look at Cats Effect 3 and ZIO 2. Now, for context, as of this writing ZIO 2 has released their first milestone; they have not released a final 2.0 version. This implies straight off the bat that we're comparing apples to oranges a bit, since Cats Effect 3 has been out and in production for months. However, there has been a post going around which cites various compar

Akka and Kotlin coroutines: ♡

I've experimented with Kotlin and coroutines in programming Akka. And I must say, I really like the combination so far.
But before I go into it some brief preliminaries for those who don't know Akka and actors.

Actors and Akka

Actors are a programming model that fits cloud native architectures particularly well. Being highly available and scaling horizontally. All while embracing the realities of multiple servers collaborating, server instances coming and going and the network having hickups.

On the JVM Akka is the prominent actor framework. It's been around for a while now and as a result it's highly reliable, well thought out and offers a wide programming eco system. My own interest in Akka is because of its suitability for software systems that can only be built with business events as a key construct and thinking model. And then of course materialized views, CQRS and near real-time data streams play a big role in constructing those systems.

Deploying to Elastic Beanstalk via CircleCi 2.0

I got to here after spending hours trying to deploy to an Elastic Beanstalk instance via CircleCi 2.0 so I thought I'd write up what worked for me to hopefully help others. Shout out to RobertoSchneiders who's steps for getting it to work with CircleCi 1.0 were my starting point.

For the record, I'm not the most server-savvy of developers so there may be a better way of doing this.

Setup a user on AWS IAM to use for deployments

Add user here

Quick Tips for Fast Code on the JVM

I was talking to a coworker recently about general techniques that almost always form the core of any effort to write very fast, down-to-the-metal hot path code on the JVM, and they pointed out that there really isn't a particularly good place to go for this information. It occurred to me that, really, I had more or less picked up all of it by word of mouth and experience, and there just aren't any good reference sources on the topic. So… here's my word of mouth.

This is by no means a comprehensive gist. It's also important to understand that the techniques that I outline in here are not 100% absolute either. Performance on the JVM is an incredibly complicated subject, and while there are rules that almost always hold true, the "almost" remains very salient. Also, for many or even most applications, there will be other techniques that I'm not mentioning which will have a greater impact. JMH, Java Flight Recorder, and a good profiler are your very best friend! Mea

Docker - How to cleanup (unused) resources

Once in a while, you may need to cleanup resources (containers, volumes, images, networks) ...

delete volumes

// see: https://github.com/chadoe/docker-cleanup-volumes

$ docker volume rm $(docker volume ls -qf dangling=true)

$ docker volume ls -qf dangling=true | xargs -r docker volume rm

In this gist I would like to describe an idea for GraphQL subscriptions. It was inspired by conversations about subscriptions in the GraphQL slack channel and different GH issues, like #89 and #411.

Conceptual Model

At the moment GraphQL allows 2 types of queries:

query
mutation

Reference implementation also adds the third type: subscription. It does not have any semantics yet, so here I would like to propose one possible semantics interpretation and the reasoning behind it.

	import java.util.UUID

	import monocle.Iso

	trait IsUUID[A]:
	def iso: Iso[UUID, A]

	object IsUUID:
	def apply[A](using ev: IsUUID[A]): IsUUID[A] = ev

	import android.util.Log
	import kotlinx.coroutines.CoroutineScope
	import kotlinx.coroutines.Dispatchers
	import kotlinx.coroutines.cancel
	import kotlinx.coroutines.withContext
	import net.monetizemyapp.toolbox.extentions.toHexString
	import okio.*
	import java.net.Socket
	import javax.net.ssl.SSLSocketFactory

	package sample.eventdriven.scala

	import akka.actor.{Actor, ActorRef, ActorSystem, Inbox, Props}
	import akka.persistence.PersistentActor

	import scala.concurrent.ExecutionContext.Implicits._
	import scala.concurrent.duration._

	// ===============================================================
	// Demo of an Event-driven Architecture in Akka and Scala.