sitkevij

curl -L https://www.opscode.com/chef/install.sh | sudo bash
echo 'export PATH="/opt/chef/embedded/bin:$PATH"' >> ~/.bash_profile && source ~/.bash_profile
sudo chef-server-ctl reconfigure

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# test installed on ubuntu 14
# curl -L https://thisscript/install.sh | sudo bash
# curl -L https://gist.githubusercontent.com/sitkevij/3379c08292b34770e5cd/raw/16d2faae9c16556b1ad0bca075a2b51f960353e4/install-chef-server.sh | sudo bash
wget https://opscode-omnibus-packages.s3.amazonaws.com/ubuntu/12.04/x86_64/chef-server_11.1.3-1_amd64.deb
sudo dpkg -i chef-server_11.1.3-1_amd64.deb
sudo chef-server-ctl reconfigure

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# read http://www.unixmen.com/install-configure-nagios-ubuntu-14-04-lts/
# echo $HISTFILE
# ls /home/ubuntu/.bash_history 
# installation for fresh vm
sudo apt-get install nagios3 nagios-nrpe-plugin
sudo vim /etc/nagios3/nagios.cfg
#Find the line,
#
#check_external_commands=0
#And change it to:

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HEX=c9fc17d693b58ad31448d1177728964591ad1c720b545a05c700395c980a7029
i=1
while (( i <= ${#HEX} ))
do
    char=$(expr substr "$HEX" $i 2)
    # echo "<$char>"
    printf "%d\n" 0x$char
    (( i += 2 ))
done

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Setting up Caffe & ImageNet

Install and setup notes to get first get Caffe and then ImageNet up and running.

Caffe is a deep learning framework by Berkeley Artificial Intelligence Research BAIR

SETUP NOTES

• Amazon Cuda Ubuntu AMI https://github.com/BVLC/caffe/wiki/Caffe-on-EC2-Ubuntu-14.04-Cuda-7
• Ubuntu Installation http://caffe.berkeleyvision.org/install_apt.html
• git clone https://github.com/BVLC/caffe

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Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

sitkevij

#include <iostream>
#include <complex>
#define MAX 200

using namespace std;

#define M_PI 3.1415926535897932384

int log2(int N)    /*function to calculate the log2(.) of int numbers*/
{

sitkevij

#include <assert.h>
#include <math.h>
#include <stdio.h>
#include <stdlib.h>

#define q	3		/* for 2^3 points */
#define N	(1<<q)		/* N-point FFT, iFFT */

typedef float real;
typedef struct{

sitkevij

@see https://medium.com/google-developers/how-to-run-travisci-locally-on-docker-822fc6b2db2e

1. Install Docker
2. Install Travis on Docker

# choose the image according to the language chosen in .travis.yml
$ docker run -it -u travis quay.io/travisci/travis-jvm /bin/bash
# now that you are in the docker image, switch to the travis user
sudo — travis

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FaaS Serverless Technologies

This page has been migrated to https://github.com/sitkevij/serverless. This gist will no longer be updated.

• AWS Lambda https://aws.amazon.com/lambda/
• hook.io https://hook.io
• IronFunctions http://iron.io
• Google Cloud Functions https://cloud.google.com/functions/docs/
• Microsoft Azure Functions https://azure.microsoft.com/en-us/services/functions/
• OpenWhisk
• Apache OpenWhisk main http://openwhisk.org/