• Posted on January 31, 2023

  Does ChatGPT dream about cryptographic cats?

  Back in 2017, the tech world seemed to be constantly talking about a single subject: Blockchains. Two years ago, Vitalik Buterin revolutionized the nascent field by creating Ethereum. Ethereum was at the time a cryptographic protocol that would allow people to make distributed computations, without having to blindly trust the entire network. It was built on Bitcoin’s concept of blockchain: a distributed, unalterable public ledger of transactions secured through enormous amounts of computing power. But it was not just an alternative currency like Bitcoin. Ethereum was able to run any sort of computation, and could not only be used as a ledger for ETH, but as a database for distributed applications.

  

  This technological breakthrough led to a lot of promises being made at the time:

  • it would help us build smarter energy grids
  • it would prevent voter fraud and pave the way to direct democracy
  • it would simplify medical records
  • it was the “Driver of the Fourth Industrial Revolution”
  • it was the “Next Generation of the Internet”

  Sadly, Ethereum had a few issues. First, it was extremely slow. Unlike traditional distributed systems, its fault-tolerant nature required every node to run every computation. This also made the system costly, as node owners were to be compensated with a “gas fee” for running computations. And in addition to that, a public read-only ledger is by definition a privacy nightmare, and would not fare well with laws like the GDPR or HIPAA. Everybody wanted a secure, decentralized internet, but nobody wanted a slow, costly, and overly-public internet.

  While Ethereum has improved on many of its past technical issues, almost none of the wild promises made in 2017 have been fulfilled. However, Ethereum has been for the past few years one of the wildest avenues for financial speculators. Not only people can speculate on the price of ETH, but also on derivative tokens. After a wave of ICOs (the crypto equivalent of a penny stock entering the market), speculators decided to stop pretending to bet on anything that made sense and started trading jpeg files. The “CryptoKitties” application soon became the biggest hit on the Ethereum network.

  

  In 2023, everyone in the tech world is talking about Generative AI. Last year saw the release of multiple image generation models such as DALL-E 2, Stable Diffusion, and MidJourney. Also notably, OpenAI decided to tease the upcoming GPT-4 text generation model, by repackaging its GPT-3 model in the form of a chatbot: ChatGPT.

  Just like Ethereum, those are truly impressive technological breakthroughs. In less than a decade, image generation models went from being able to create vaguely psychedelic patterns (DeepDream) to completely generating paintings in the style of any popular artist. In the same way, text generation models are now good enough, they could easily be mistaken for a human. Thankfully, ChatGPT kindly discloses it’s an AI language model when asked.

  This progress in AI also comes with its set of crazy promises:

  • generative language models could replace search engines
  • AI could replace educators, financial analysts, software engineers, journalists, and graphic designers
  • AI could give legal advice and potentially replace lawyers
  • we have finally reached the “singularity”

  This optimism seems to forget a few limitations of this technology, which I did ask ChatGPT itself to tell us about:

  1. Lack of understanding: Generative models may generate outputs that lack context, meaning or coherence.
  2. Computational costs: Training generative models can be computationally expensive and require large amounts of data and computing power.
  3. Bias in data: If the training data is biased, the model may generate outputs that reflect this bias.
  4. Mode collapse: Models may generate limited outputs and fail to cover the diversity of the data.
  5. Overfitting: Generative models may memorize the training data and fail to generalize to new data.
  6. Explainability: Generative models are often complex and difficult to understand or explain, making it challenging to assess their decision-making processes.

  But just like Ethereum, it looks like ChatGPT is already attracting financial speculators. Last week, BuzzFeed, an usually pretty un-noticeable penny stock, rose by more than 300% on the simple news that the company would make use of generative AI. As the quote goes, “History never repeats itself, but it does often rhyme”.

• Posted on December 13, 2022

  Plaid Layoffs and beyond

  Last week, Plaid announced laying off 20% of its workforce (260 people). Today I signed my termination agreement, which makes this week my last week as part of Plaid’s infrastructure team.

  

  Moving forward

  While being laid off and having to leave a very talented team is never a happy moment, I have decided to use the time ahead of me as an opportunity to focus on personal growth and figure out were I want my career to go next. I will not be seeking new full-time employment immediately.

  First, I want to get back into actually building things by myself. My programming skills and technology knowledge has immensely increased since I left college. Since then, I have not had the time and energy to get into serious side projects. I intend to use the next few months to fix that, although I am not sure exactly what form my new projects will take.

  Second, I need some time to explore infrastructure tooling outside of kubernetes. I enjoy working with kubernetes, but I am also starting to suspect that we are close to the peak of the hype cycle. If that’s the case, having a career focused on k8s might become as attractive as being an Enterprise JavaBeans expert. To avoid that, I intend to seek out “what’s new” in the infrastructure space and explore new technologies.

  While I’m talking about diversifying my skill portfolio, I also intend to explore subjects that are way outside of my comfort zone, mainly regarding communication. I think effective communication is an essential skill to anyone working in tech, which is currently my weak point. To fix that, I will try to inform myself about writing and visual communication techniques. I intend to practice by writing and talking more about what I do. And while I’m at it, I might try to finish learning dutch.

  So with all that, expect more activity on this blog in the next few months. I will do my best to talk about the projects I’m creating, the technologies I’m trying and everything I discover along the way.

• Posted on November 20, 2022

  DEFCON 30

  This summer I had the opportunity to attend DEFCON 30, a cybersecurity conference gathering around 27000 hackers in the fabulous city of Las Vegas, Nevada. With more than 30 villages and 3 main conference tracks, the event managed to cover pretty much every subject from malware analysis to online drug dealing.

  

  Best talks

  Roger Dingledine from the Tor Project made a fairly news-relevant talk explaining how Russia is trying to block Tor. It gives an explanation of the software produced by the Tor project, such as Tor, Tor browser, and pluggable transports (like meek). Those last ones are the most important here since they can help bypass attempts made by dictatorships to block Tor. The talk dives a bit deeper into Russia’s censorship of Tor and explains its numerous flaws and shortcomings.

  Another very interesting talk was from Nikita Kurtin, about bypassing Android permissions. This talk shows perfectly how thinking outside the box can lead you to completely break complex permission systems. In this case, he uses a mix of UX and system tricks to get users to agree to anything, all the time.

  And lastly, Minh Duong gave the most fun talk of this conference by explaining how he Rick Roll’d his entire school district. It explains how he managed to take over his school network, using known vulnerabilities and software misconfigurations, and progressively escalated his position until he was able to play “Never gonna give you up” everywhere. Definitely, a good example of realistic hacking, far away from academic papers and armchair exploit development.

  The villages

  Each village provided either a set of talks, and activities. I didn’t stick too long in the Cloud and AppSec villages, as I wanted to use the conference to also discover subjects I am less used to. The physical security, tamper-evident, and lockpicking villages were particularly interesting to me, as I had not really explored non-computer topics of security before. And honestly, they almost made me think picking locks was going to be easy!

  The car hacking and voting machine villages also allowed me to have a glimpse into topics that will probably become quite important to the industry in the near future. The biohacking village was also interesting as it provided a few medical devices to try and break, although I am not sure if anyone managed to actually root anything during the conference.

  The other stuff

  At night, the talks and villages left room for parties. Not only this made for a good socializing opportunity, but we also managed to see an absolutely awesome show by Taiko Project.

  I didn’t really take the time to solve the badge challenges, but I still found it very cool that it contains an actual playable keyboard.

  

  And I was almost going to forget but, Vegas was strange, but also actually a nice city. I don’t think I would mind having to face the desert heat once more if I have the occasion.

• Posted on October 10, 2022

  Managing your Kubernetes cluster using Helm and Terraform

  In a previous post, I explained how to manage a Kubernetes cluster with FluxCD. This showed a way to implement a GitOps workflow, which means using a Git repository as the source of truth for the state of your cluster.

  Flux introduces multiple new objects in your Kubernetes clusters, and requires using custom software. This makes it harder to adopt by smaller teams without dedicated platform engineers. On the other hand, most teams are already using Terraform. In this article, I will show how to make use of Terraform to manage your kubernetes clusters. This way could be considered GitOps-lite because while changes are kept track of in a Git repository, they are neither enforced nor automatically pulled from the repository.

  I will use resources from Google Cloud Platform in the following examples, but everything in this article should be doable in any major cloud platform.

  

  Setting up a cluster with Terraform

  First, make sure you have the Terraform CLI installed or download it here. Then, create a new Git repository

  mkdir cluster
  cd cluster
  git init
  git remote add origin <your-github-repo>
  

  We will then define a basic Google Kubernetes Engine cluster (with two nodes) and indicate Terraform to store the state in a remote Google Cloud Storage bucket, which you will need to create manually. The following HCL should go in the main.tf file:

  terraform {
    required_providers {
      google = {
        source  = "hashicorp/google"
        version = "3.5.0"
      }
    }
    backend "gcs" {
      bucket = "your-unique-tf-state-bucket"
      prefix = "terraform/state"
    }
  }
  
  variable "project_id" {
    description = "project id"
  }
  
  variable "region" {
    description = "region"
  }
  
  provider "google" {
    project = var.project_id
    region  = var.region
  }
  
  resource "google_container_cluster" "primary" {
    name               = "${var.project_id}-gke"
    location           = var.region
    initial_node_count = 2
  }
  

  This defines the variables “region” and “project_id”, which we pass to the google provider, as those will contain the data relevant to our GCP project. The values of these variables can either be set interactively when running terraform commands or kept in the terraform.tfvars file.

  You can then proceed to run terraform init to initialize your project and state. After that, run terraform plan, which will display the changes terraform is about to do, and run terraform apply to apply those changes and create your cluster.

  Since GKE resources have a state that is a lot more complex than the HCL file above, I suggest using the output of terraform state show google_container_cluster.primary to refactor the HCL into a more complete overview of the state. This can in the future avoid unwanted changes to appear in the plans.

  Authenticating to your cluster

  You can now authenticate to your cluster using the Google Cloud CLI. First install it by following the instructions here. Then log into Google Cloud using gcloud auth login, which should open your browser for a login prompt. After that, use gcloud config set project to indicate which project you are working on. Finally, run gcloud container clusters get-credentials [YOUR_PROJECT_ID]-gke --zone=[YOUR_REGION]

  You should now see your cluster appear when you run kubectl config get-contexts and two nodes should be visible by running kubectl get nodes.

  

  Installing Helm charts

  We will now use the helm terraform provider to install podinfo and set the value replicaCount to 2. To do this, create a new HCL file, with the following content:

  provider "helm" {
    kubernetes {
      config_path = "~/.kube/config"
    }
  }
  
  resource "helm_release" "podinfo" {
    name       = "podinfo"
  
    repository = "https://stefanprodan.github.io/podinfo"
    chart      = "podinfo"
  
    set {
      name = "replicaCount"
      value = 2
    }
  }
  

  You’ll need to run terraform init -upgrade to install this new provider. Then you can run terraform plan and terraform apply, just like in the previous section.

  This will act just like helm upgrade -install and the podinfo release should now appear when running helm list. Using kubectl get pods should show you two podinfo pods running. You can access the service by running kubeclt port-forward service/podinfo 9898:9898 and then curl localhost:9898.

  Going further

  Directly applying changes from your local environment doesn’t scale well when multiple people are committing changes to the infrastructure. It also causes safety issues, as changes could be applied locally without having been through a PR review. One way to solve that problem would be to use GitHub Actions to automate planning the changes when a PR is applied and applying when a PR is merged. The SaaS Atlantis can also help solve that problem, as it will act as a GitHub bot that will plan/apply in response to comments.

• Posted on April 20, 2022

  A sensible NeoVim configuration

  I have been using NeoVim as my main editor for code since 2017. When discussing that with other engineers, a common complaint I hear about (Neo)Vim is that its configuration is overly complicated and confusing. In this post, I will try to address this point by showing simple steps to configure NeoVim into a development capable environment. This should allow you to get essential code editing features (ie. auto-completion, linting, search…) while keeping a minimalist and fast environment.

  Installing NeoVim

  First of all, install NeoVim by following the instructions on GitHub. Open NeoVim by simply typing nvim in a terminal.

  If you want to learn the basics of using vim, type :Tutor. This will take you to the built-in tutorial.

  Type the :CheckHealth command into NeoVim’s normal mode, this will tell you if you need to set up anything special.

  The most important dependency is to have python 3.6+ with the neovim pip package installed as well as node with the neovim npm package. Aside from that, you might need:

  • python 2.7 with the neovim package
  • ruby with the neovim gem
  • perl with the Neovim::Ext module

  Once everything is green, let’s go over some basic configurations

  

  Basic configuration

  First, you should create your configuration file at ~/.config/nvim/init.vim.

  To be able to exit NeoVim’s terminal emulator (:term) by simply pressing escape instead of the Ctrl+\ Ctrl+n combo, add this line to your config file (~/.config/nvim/init.vim):

  tmap <Esc> <C-\><C-n>
  

  map is the basic operator for mapping keyboard shortcuts. tmap indicates that you want to map these keys in terminal mode only. imap and nmap are respectively for insert and normal mode. As an alternative to map you might have to sometimes use noremap to non-recursively map (this is meant to avoid propagating to mappings you’ve already changed).

  You’ll also want to be able to switch between windows without having to type a complete command:

  nmap <silent> k :wincmd k<CR>
  nmap <silent> j :wincmd j<CR>
  nmap <silent> h :wincmd h<CR>
  nmap <silent> l :wincmd l<CR>
  

  These lines will map the switching of commands to Alt+hjkl. (Note, on mac the only way I’ve managed to configure that was by using the characters output when I press Alt+hjkl on my keyboard).

  Then, you can do a few tweaks to the appearance. I recommend displaying numbers next to lines, displaying line wrapping, and allowing horizontal scrolling.

  set number
  set nowrap
  set sidescroll=1
  

  You should then add some default tab configurations.

  set tabstop=2
  set softtabstop=2
  set shiftwidth=2
  set expandtab
  set autoindent
  set fileformat=unix
  

  You also want to be able to override those configurations for each project with a local .nvimrc:

  set exrc
  

  And lastly, this line will allow scripts to run for specific file types:

  :filetype plugin on
  

  Plugins

  Since NeoVim doesn’t have every feature developers usually need out of the box, you will need to be able to install plugins. For that purpose, we will use vim-plug. Installing by runnning:

  sh -c 'curl -fLo "${XDG_DATA_HOME:-$HOME/.local/share}"/nvim/site/autoload/plug.vim --create-dirs \
         https://raw.githubusercontent.com/junegunn/vim-plug/master/plug.vim'
  

  We will then do the first edit to your configuration file ~/.config/nvim/init.vim. Add the following lines to install the plugins you will need:

  call plug#begin('~/.vim/plugged')
  Plug 'ctrlpvim/ctrlp.vim'
  Plug 'tpope/vim-fugitive'
  Plug 'vim-airline/vim-airline'
  Plug 'tpope/vim-sleuth'
  Plug 'neoclide/coc.nvim', {'branch':'release'}
  call plug#end()
  

  Each of the lines starting with Plug indicates the GitHub repository of a plugin. Save your config file and type :PlugInstall in NeoVim’s normal mode to install them.

  The plugins this will have installed are the following:

  • coc.nvim gives you essential code-editing features like auto-completion using the language server protocol (like VScode)

  Ctrlp.vim

  Ctrlp.vim is a very efficient file search plugin.

  To use it simply press CTRL+P, this will open a file list that you can navigate with arrow keys. Typing any characters will make it search for matching files. You can use CTRL-F and CTRL-B to cycle between the different search modes (files, buffers, or most recently used). CTRL-R will allow you to type in regexes, while CTRL-D will search only in the filenames instead of the full path.

  

  Use the following line to stop this plugin from indexing files outside of your source code:

  let g:ctrlp_custom_ignore = '\v[\/](node_modules|target|dist|venv)|(\.(swp|ico|git|svn))$'
  

  If you want to integrate more file handling into vim, you can also try NERDTree, which will provide you with a complete file system explorer.

  Vim-fugitive

  Vim-fugitive is a wrapper around git. It doesn’t require any special configuration to work, as long as you have a git CLI configured on your machine.

  It will allow you to use any git command in vim using :G, you can try it with :G status to display the result of git status. One neat trick is that you can use :G grep to send the result of a git grep directly into vim’s quickfix list.

  Vim-airline

  Vim-airline will display the status of your current file as the last line of the editor. It’s basically plug and play and will even automatically detect other plugins you use (like ctrpl or fugitive) and integrate them.

  The status line is divided into 6 sections (A, B, C, X, Y, Z) and can be customized with the statusline syntax:

  let g:airline_section_b = 'Filetype: %y'
  

  

  Vim-sleuth

  Vim-sleuth aims at automatically adjusting indentation to the file you’re editing. It works by simply overriding the shiftwidth and expandtab variables (which you can set manually in your config file if you want). It doesn’t require any configuration either and generally works pretty well.

  An alternative to it would be to use editorconfig-vim. This plugin will instead follow the configuration written in a .editorconfig file at the root of a project.

  Coc.nvim

  Coc.nvim is really what will give you an IDE-like experience. This plugin will give you auto-complection, linting, and formatting, using language servers protocols. For that part, I recommend using the configuration sample they provide on GitHub. It will give you useful shortcuts to IDE-like features, like gd to go to a definition, gr to list references, and \t for automatic renaming.

  

  To support every possible language, CoC has its own plugin system. For example, :CocInstall coc-go will install the coc-go plugin for the Go programming language and use gopls.

  Alternatively, NeoVim now has built-in support for LSPs, you can read more about how to configure that in this repo. As this solution still requires to install a few plugins for auto-completion, I consider CoC to be the simplest option around at the moment.

  Theming

  Of course, everyone loves some colors! Vim and Neovim have a ton of themes that you can example at vimcolorscheme. Each one can be installed with vim-plug like any other plugin. Once it is installed you can use the colorscheme function to enable it from your vim config file. For example with the dracula theme:

  colorscheme dracula
  

  Conclusion

  This post is only scratching the surface of what can be done with NeoVim. As you use this editor more and more, you will probably want to use different configurations, and will probably end up with a few more (or fewer plugins).

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