garthk

FROM amazonlinux:2
COPY scalyr.key /etc/pki/rpm-gpg/RPM-GPG-KEY-scalyr-1
COPY scalyr.repo /etc/yum.repos.d/
RUN yum install -y jq systemd-python python2-pip scalyr-agent-2
RUN pip2 install docker-py
CMD ["python2", "-c", "import docker; docker.APIClient"]

garthk

#! /usr/bin/env elixir

defmodule FindEmoji do
  def find_emoji_in_git_log do
    :ok =
      stream_executable("git", ["log"])
      |> Stream.filter(&contains_emoji?/1)
      |> Stream.each(&IO.puts/1)
      |> Stream.run()
  end

garthk

Collisions in Key-Sortable Unique Identifiers (KSUIDs)

Expanding on my thread, it’s been nagging me that the random tail on small key sortable unique IDs (KSUID) might not provide as much protection vs collision as I’d trusted. Segment were able to throw bits at the problem, but I needed to pack my identifiers in smaller spaces.

After sparing 32 bits for the timestamp I might have room for only 32, 40, or 96 random bits. There’s that cryptographers’ rule of thumb about collision needing half the bit count… but how likely is it we’ll get at least one collision?

My math being a bit rusty, I decided to brute force it (birthday.exs). I didn't like my results.exs:

• 39% failure for 2¹⁶ random choices from 2³² possible keys (3443 rounds)
• 45% failure for 2²⁰ random choices from 2⁴⁰ possible keys (163 rounds)

garthk

  @doc "Convert a string or atom to a pascal case string"
  @spec pascal_case(String.t() | atom()) :: String.t()
  def pascal_case(name)
  def pascal_case(name) when is_atom(name), do: name |> Atom.to_string() |> pascal_case()

  def pascal_case(name) when is_binary(name) do
    ~r{(\W|_)+}
    |> Regex.split(name)
    |> Enum.map(&capitalise/1)
    |> Enum.to_list()

garthk

FROM elixir:1.9.4-alpine
ADD . /root
WORKDIR /root
RUN mix do local.hex --force, deps.get
ENTRYPOINT []
CMD ["mix", "credo", "--strict", "credo732.ex"]

garthk

Basic Risk Register Workflow for Slack

Slack workflow inspired by Mikala Easte's presentation risk management without slowing down at Purplecon.

Purplecon haven't yet published the video, and might not, so check out @jpdanner's epic summary.

garthk

defmodule Opencensus.Honeycomb.PhoenixIntegrationTest do
  use ExUnit.Case, async: false
  use Phoenix.ConnTest

  alias Jason
  alias Opencensus.Honeycomb.Event
  alias Opencensus.Honeycomb.Sampler

  defmodule HelloWeb.OpencensusTracePlug do
    use Opencensus.Plug.Trace, attributes: [:release]

garthk

Strikes me I'm just re-inventing poolboy, here.

garthk

Seemed like a great idea until I was assured that the momentum was with Opencensus, not Spandex. Between this and the recently announced merger of Opencensus and OpenTracing, it strikes me that it's a reasonable bet to invest on Opencensus propagation headers instead.

garthk

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