paul vidal - pragmatic big data nerd

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True cloud automation for large organizations: a case of leading by example.

by paul 0 Comments
True cloud automation for large organizations: a case of leading by example.
If you're reading this Ashish, this is for you

Introduction

As a solution engineer, it is my mandate to advocate large IT organizations on how to best leverage the tools available in the market to empower their users to be autonomous. In the world of big data, this has many aspects from defining business processes to ensuring security and governance. The key aspect however is the ability to “shift to the left”, meaning that the end user is in control of the infrastructure necessary for his job.

Ultimately this is the unicorn every organization wants: a highly guarded infrastructure that feels like a plain of freedom to the end user.

Some organizations choose to use one vendor (e.g. cloud vendor) to implement this unicorn vision, but soon realize (or will soon) that the limiting yourself to one vendor not only restrict the plain field of end users it paradoxically make the implementation of consistent governance and security harder (because of vendor limitations and a tendency towards restricting cross platform compatibility)

The solution is what I advice my customer every day: building the backbone of an organization on open inter compatible standards that allow growth while maintaining consistency. In today’s world, it’s the hybrid cloud approach.

When I joined Hortonworks (now Cloudera) a few months ago I was impressed by the work done by a few Solution Engineers (Dan Chaffelson and Vadim Vaks). They had built an automation tool that would allow any Solution Engineer in the organization to spin their own demo cluster and load whatever demo they want called Whoville. I led a Pre-Sales organization before: this is the dream. Having consistency over demos for each member of the organization while empowering the herd of cats that Solution Engineers are is no easy feat. Not only that, we were eating our own dog food, leveraging our tools to instantiate what we had been preaching!

I’m still in awe of the intelligence and competency of the team I just joined. But, being as lazy as I am, I decided to try and build an even easier button for Whoville which would:
1. Empower the rest of our organization even more
2. Show true thought leadership to our customers

So with the help of my good friend Josiah Goodson and the support of the Solution Engineering team (allowing us to work on this during a hackathon for instabce) we built Cloudbreak Cuisine.

Introducing Cloudbreak Cuisine

Cuisine is fully featured application, running in containers, that allows, in its alpha version, Solution Engineers to:
1. Get access to Whoville library, deploy and delete demo clusters
2. Monitor clusters deployment via Cloudbreak API
3. Create your own combination of Cloudbreak Blueprints & Recipes (a.k.a. bundles) for your own demo
4. Push those bundles to Cloudbreak

Below is a high level architecture of Cuisine:

Cloudbreak Cuisine Architecture

The deployment of the tool is automated, but requires access to Whoville (restricted within our own organization). All details can be found here: https://github.com/josiahg/cloudbreak-cuisine

The couple of videos below showcase what Cuisine can do, in its alpha version.

Glossary: Cuisine Bundles are a combination of Cloudbreak Blueprints & Recipes.

Features

Push a bundle from Whoville

Push Bundle

Delete a Bundle via Cloudbreak

Delete Bundle

Add Custom Recipe

Add Recipe

Create Custom Bundle

Create Bundle

Download/Push Bundle

Download/Push Bundle

Additional tips/tricks

Tips & Tricks

Parting thoughts

First and foremost: thank you. Thank you Dan and Vadim for Whoville, thank you Josiah for your continuous help and thank you Hortonworks/Cloudera to allow us to be demonstrating such thought leadership.

Secondly, if you’re a Cloudera Solution Engineer, test it and let me know what you think!

Finally, for every other reader out there: this is what an open platform can do to your organization. Truly allow you to leverage any piece of data or any infrastructure available to you; from EDGE to AI :)

Use Altus Director to launch a Cloudera Data Science Workbench cluster on AWS

by paul 0 Comments
Use Altus Director to launch a Cloudera Data Science Workbench cluster on AWS

My blood recently turned from green to blue (after the Hortonworks-Cloudera merger) and I couldn’t be more excited to play with new toys. What I am particularly excited about is Cloudera Data Science Workbench. But, like in everything I do, I am very lazy. So here is a quick tutorial to install Altus Director, and use it to deploy a CDH 5.15 + CDSW cluster.

Step 1: Install Altus Director

Many ways to do that, but the one I chose was the AWS install, detailed here: https://www.cloudera.com/documentation/director/latest/topics/director_aws_setup_client.html

The installation documentation is very well done, but here are the important excerpts

Create a VPC for your Altus instance

Follow the documentation.

Few important points:

  • In the name of laziness I also recommend to add a 0-65535 rule from your personal IP.
  • Your VPC should have an internet gateway associated with it (you could do it without, but would require you manually pulling the CM/CDH software down and make internal repositories within your subnet)
  • Do not forget to open all traffic to your security group as described here. Your deployment will not work otherwise.

Launch a Redhat 7.3 instance

You can either search communities AMIs, or use this one: ami-6871a115

Install Altus

Connect to your ec2 instance:

ssh -i your_file.pem ec2-user@your_instance_ip

Install JDK and wget

sudo yum install java-1.8.0-openjdk
sudo yum install wget

Install/Start Altus server and client:

cd /etc/yum.repos.d/
sudo wget "http://archive.cloudera.com/director6/6.1/redhat7/cloudera-director.repo"
sudo yum install cloudera-director-server cloudera-director-client
sudo service cloudera-director-server start
sudo systemctl disable firewalld
sudo systemctl stop firewalld

Connect to Altus Director

Go to http://your_instance_ip:7189/ and connect with admin/admin

Step 2: Modify the Director configuration file

CDSW cluster configuration can be found here https://github.com/cloudera/director-scripts/blob/master/configs/aws.cdsw.conf

Modify the configuration file to use:

  • Your AWS accessKeyId/secretAccessKey
  • Your AWS region
  • Your AWS subnetId (same as the one you created for your Director instance)
  • Your AWS securityGroupsIds (same as the one you created for your Director instance)
  • Your private key path (e.g. /home/ec2-user/field.pem)
  • Your AWS image (e.g. ami-6871a115)

Step 3: Launch the cluster via director client

Go to your EC2 instance where Director is installed, and load your modified configuration file as well as the appropriate key.

Finally, run the following:

cloudera-director bootstrap-remote your_configuration_file.conf \
--lp.remote.username=admin \
--lp.remote.password=admin

Step 4: Access Cloudera Manager

You can follow the bootstrapping of the cluster both on command line or in the Director interface; once done, you can connect to Cloudera Manager using: http://your_manager_instance_ip:7180/

Step 5: Configure CDSW domain with your IP

Cloudera Data Science Workbench uses DNS. The correct approach is to setup a wildcard DNS record is required, as described here.

However, for testing purposes I used nip.io. The only parameter to change is the Cloudera Data Science Workbench Domain, from cdsw.my-domain.com as the conf file sets it up to, to cdsw.[YOUR_AWS_PUBLIC_IP].nip.io, as depicted below:

Restart the CDSW service, then you should be able to access CDSW by clicking on the CDSW Web UI link. Register for a new account and you will have access to CDSW: