- Pusher - Real time apps
Pas de request/response mais une solution élégante en PUB/SUB
- Pubnub - The global data stream network for IoT, Mobile, and Web applications
Ultra overkill mais apparemment très puissant. Fait à peu près tout.
#! /bin/sh | |
readonly LIGHT_IMAGE=alpine:latest | |
generate() { | |
docker run ${LIGHT_IMAGE} sleep 0 | |
container_id=$(docker ps -a -l -q) | |
echo "$(docker inspect --format='{{ .Name }}' ${container_id} | tr '_/' ' ')" | |
docker rm ${container_id} &> /dev/null | |
} |
# You don't need Fog in Ruby or some other library to upload to S3 -- shell works perfectly fine | |
# This is how I upload my new Sol Trader builds (http://soltrader.net) | |
# Based on a modified script from here: http://tmont.com/blargh/2014/1/uploading-to-s3-in-bash | |
# export S3KEY="my aws key" | |
# export S3SECRET="my aws secret" # pass these in | |
BUCKET="apps-crawler-prod" | |
putS3 () { |
stream | |
// Select just the cpu_usage_idle measurement from our example database. | |
.from().measurement('cpu_usage_idle') | |
.alert() | |
.crit(lambda: "value" < 70) | |
// Whenever we get an alert write it to a file. | |
.log('/tmp/alerts.log') |
#!/usr/bin/env bash | |
# abort quietly if already setup | |
[ -z "${__PROJECT__}" ] || return | |
# generic project management | |
export __PROJECT__="$(basename $PWD)" | |
# go specific settings | |
export __GO_VERSION__="1.5.1" |
# Makefile | |
# vim:ft=make | |
PROJECT := $(shell basename $(PWD)) | |
SOURCEDIR=. | |
SOURCES := $(shell find $(SOURCEDIR) -path './vendor' -prune -o -type f -name '*.go' -print) | |
PACKAGES=$(shell go list ./... | grep -v /vendor/) | |
GIT_COMMIT=`git rev-parse HEAD` | |
GIT_USER=`git config --get user.name` |
# TODO Remove archives | |
FROM java:7 | |
# Constants | |
#ENV JAVA_VERSION 7 | |
ENV INSTALL_WORKSPACE /opt | |
#ENV ANDROID_SDK_VERSION r23.0.2-linux | |
ENV ANDROID_SDK_VERSION r24.2-linux | |
ENV ANDROID_BUILDER ant | |
ENV ANDROID_SDK_TOOLS android-21,build-tools-22.0.0,platform-tools,extra-android-support |
# The Brain | |
Compilation de services permettant de mettre en place des algorithmes de recommendation et, plus largement, de machine learning et d'analyse de data. | |
L'idée principale est de pouvoir considérer la partie machine learning comme un service brique lego : des requêtes pour trainer les modèles et récupérer les predictions. Une plateforme/des outils pour manipuler les données ou développer les modèles serait un + pour anticiper les besoins à venir. | |
## [Prediciton.io](https://prediction.io/) | |
> Build and Deploy Machine Intelligence in a fraction of the time |
As articles state everywhere, we're living in a fast pace digital age. Project complexity, or business growth, challenges existing development patterns. That's why many developers are evolving from [the monolithic application][16] toward [micro-services][17]. Facebook is moving away from its [big blue app][1]. Soundcloud is [embracing microservices][2].
Yet this can be a [daunting process][3], so what for ?
#!/bin/bash | |
DEFAULT_NAME="lab" | |
DEFAULT_IMAGE="ubuntu" | |
WORKDIR="/root/app" | |
REPL="bash" | |
usage() { | |
printf "hack --help\t\tprint help\n" | |
printf "hack <image> <name>\trun a lab container\n" |