Kamil Sindi ksindi

## docker-compose.yml
version: "3"

services:
  localstack:
    image: localstack/localstack
    ports:
      - "4568-4576:4568-4576"
      - "${PORT_WEB_UI-8080}:${PORT_WEB_UI-8080}"
    environment:
      - DOCKER_HOST=unix:///var/run/docker.sock

## ssm_parameter_store.py
# Copyright (c) 2018 Bao Nguyen <b@nqbao.com>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all

## kubernetes_add_service_account_kubeconfig.sh
#!/bin/bash
set -e
set -o pipefail

# Add user to k8s using service account, no RBAC (must create RBAC after this script)
if [[ -z "$1" ]] || [[ -z "$2" ]]; then
 echo "usage: $0 <service_account_name> <namespace>"
 exit 1
fi

## docker-ssh-forward.bash
docker run -rm -t -i -v $(dirname $SSH_AUTH_SOCK) -e SSH_AUTH_SOCK=$SSH_AUTH_SOCK ubuntu /bin/bash

## gh-deploy-clone.sh
#!/usr/bin/env bash

read -r -d '' usage << EOM
Usage:

  gh-deploy-clone user/repo [ENVIRONMENT]
EOM

[ -z "$1" ] && echo && echo "$usage" && echo && exit 1

## example.py
import asyncio
import random
import time


async def worker(name, queue):
    while True:
        # Get a "work item" out of the queue.
        sleep_for = await queue.get()

## postgres_to_kafka.sh
# Run postgres instance
docker run --name postgres -p 5000:5432 debezium/postgres

# Run zookeeper instance
docker run -it --name zookeeper -p 2181:2181 -p 2888:2888 -p 3888:3888 debezium/zookeeper

# Run kafka instance
docker run -it --name kafka -p 9092:9092 --link zookeeper:zookeeper debezium/kafka

# Run kafka connect

## load_jpeg_with_tensorflow.py
# Typical setup to include TensorFlow.
import tensorflow as tf

# Make a queue of file names including all the JPEG images files in the relative
# image directory.
filename_queue = tf.train.string_input_producer(
    tf.train.match_filenames_once("./images/*.jpg"))

# Read an entire image file which is required since they're JPEGs, if the images
# are too large they could be split in advance to smaller files or use the Fixed

## Git: Automatically delete merged branches
[alias]
  delete-merged-branches = "!f() { git checkout --quiet master && git branch --merged | grep --invert-match '\\*' | xargs -n 1 git branch --delete; git checkout --quiet @{-1}; }; f" # http://stackoverflow.com/a/6127884/2624466

## k8s-svc-annotations.md

      
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                ksindi
                / k8s-svc-annotations.md
            
            
              Created
              December 8, 2017 18:14
                — forked from mgoodness/k8s-svc-annotations.md
            
              
                AWS ELB-related annotations for Kubernetes Services (v1.5)
              
          
    AWS Service annotations


service.beta.kubernetes.io/aws-load-balancer-access-log-emit-interval (in minutes)
service.beta.kubernetes.io/aws-load-balancer-access-log-enabled (true|false)
service.beta.kubernetes.io/aws-load-balancer-access-log-s3-bucket-name
service.beta.kubernetes.io/aws-load-balancer-access-log-s3-bucket-prefix
service.beta.kubernetes.io/aws-load-balancer-backend-protocol (http|https|ssl|tcp)
service.beta.kubernetes.io/aws-load-balancer-connection-draining-enabled (true|false)
service.beta.kubernetes.io/aws-load-balancer-connection-draining-timeout (in seconds)
	version: "3"

	services:
	localstack:
	image: localstack/localstack
	ports:
	- "4568-4576:4568-4576"
	- "${PORT_WEB_UI-8080}:${PORT_WEB_UI-8080}"
	environment:
	- DOCKER_HOST=unix:///var/run/docker.sock
	# Copyright (c) 2018 Bao Nguyen <b@nqbao.com>
	#
	# Permission is hereby granted, free of charge, to any person obtaining a copy
	# of this software and associated documentation files (the "Software"), to deal
	# in the Software without restriction, including without limitation the rights
	# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
	# copies of the Software, and to permit persons to whom the Software is
	# furnished to do so, subject to the following conditions:
	#
	# The above copyright notice and this permission notice shall be included in all
	#!/bin/bash
	set -e
	set -o pipefail

	# Add user to k8s using service account, no RBAC (must create RBAC after this script)
	if [[ -z "$1" ]] \|\| [[ -z "$2" ]]; then
	echo "usage: $0 <service_account_name> <namespace>"
	exit 1
	fi
	#!/usr/bin/env bash

	read -r -d '' usage << EOM
	Usage:

	gh-deploy-clone user/repo [ENVIRONMENT]
	EOM

	[ -z "$1" ] && echo && echo "$usage" && echo && exit 1
	import asyncio
	import random
	import time


	async def worker(name, queue):
	while True:
	# Get a "work item" out of the queue.
	sleep_for = await queue.get()
	# Run postgres instance
	docker run --name postgres -p 5000:5432 debezium/postgres

	# Run zookeeper instance
	docker run -it --name zookeeper -p 2181:2181 -p 2888:2888 -p 3888:3888 debezium/zookeeper

	# Run kafka instance
	docker run -it --name kafka -p 9092:9092 --link zookeeper:zookeeper debezium/kafka

	# Run kafka connect
	# Typical setup to include TensorFlow.
	import tensorflow as tf

	# Make a queue of file names including all the JPEG images files in the relative
	# image directory.
	filename_queue = tf.train.string_input_producer(
	tf.train.match_filenames_once("./images/*.jpg"))

	# Read an entire image file which is required since they're JPEGs, if the images
	# are too large they could be split in advance to smaller files or use the Fixed
	[alias]
	delete-merged-branches = "!f() { git checkout --quiet master && git branch --merged \| grep --invert-match '\\*' \| xargs -n 1 git branch --delete; git checkout --quiet @{-1}; }; f" # http://stackoverflow.com/a/6127884/2624466