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Creating an Advanced Analytics Server in 15 minutes using AWS

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Creating an Advanced Analytics Server in 15 minutes using AWS

This guide will help you to create an Advanced Analytics Server running Python into AWS infrastructure in less than 15 minutes 

EC2 Provisioning

Prereqs

  • AWS account

  • Basic EC2 Knowledge (Instances and Securit Groups)

  • Basic Linux command line usage

Steps

  1. Go to EC2 Console

  2. Click "Launch Instance"

  3. Choose your favorite Linux distro (Used Ubuntu 18.04 into this tutorial, docker installation could differ slightly on Centos or another distro)

  4. Choose your Instance Type (t2.micro is enough for standard demos and is eligible to free tier)

  5. Use the button "Review and Launch" option and then "Launch"

  6. Choose an existing key pair or create a new one

  7. Launch your instance

  8. Release ports into security groups of your instance

    Security GroupsSecurity Groups

Click into "launch-wizard-1" and then into Actions / Edit Inbound Rules and release TCP ports 50055, 22 all incoming trafficReleasing PortsReleasing Ports

 

 

Docker installation

 

Prereqs

  • EC2 Linux instance provisioned and running

  • Basic Putty usage

Steps

  1. Connect to your instance using Putty (https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/putty.html)
  2. https://docs.docker.com/install/linux/docker-ce
  3. Remove old docker installations
    $ sudo apt-get remove docker docker-engine docker.io​
  4. Update the apt package

    $ sudo apt-get update​

    QMCQMC
  5. Install packages to allow apt to use a repository over HTTPS:

    $ sudo apt-get install \
    apt-transport-https \
    ca-certificates \
    curl \
    software-properties-common

  6. Add Docker’s official GPG key

    $ curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -

  7. Update and install docker

    $ sudo apt-get update
    $ sudo apt-get install docker.io
    $ sudo apt-get install docker-compose
  8. Add the current user to manage docker

    $ sudo usermod -aG docker $USER​

     

  9. Log out and log back

 
Installing Nabeel Asif work and dependencies.

 

Prereqs

  • EC2 instance provisioned

  • Docker installed

  • Basic docker command line usage

Steps

1.Run the container

$ docker pull nabeeloz/qlik-py-tools

$ docker run -p 50055:80 -it nabeeloz/qlik-py-tools

 

Configure your Qlik Sense Enterprise to use

Prereqs

  • All previous steps fullfilled

  • Admin role to your QSE

Steps

QMC > Start >Analytic Connections > New

QMCQMC

then import the apps from https://github.com/nabeel-oz/qlik-py-tools/tree/master/docs as usual

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Version history
Last update:
‎2020-12-16 10:54 AM
Updated by: