RETIRED, Deploy multi node OpenStack on Virtual Machines.
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Training labs

About

Provide an automated way to deploy Vanilla OpenStack and closely follow OpenStack Install Guide.

We strove to give easy way to setup OpenStack cluster which should be a good starting point for beginners to learn OpenStack, and for advanced users to test out new features, check out different capabilities of OpenStack. On top of that training-labs will also be a good way to test the install guides on a regular basis.

Training-labs is a project under OpenStack Documentation. For more information see the OpenStack wiki.

OpenStack Release

The current release is master which usually means that we are developing for the next OpenStack release. The current one is OpenStack Newton. For non-development purposes (training etc.) please checkout the stable branches. Assuming that $remote is your remote branch (usually origin) and $release is the release version.

$ git checkout $remote/stable/$release

Pre-requisite

How to run the scripts

Clone the training-labs repository:

$ git clone git://git.openstack.org/openstack/training-labs.git

Change directory:

$ cd training-labs/labs/osbash/

Run the script by:

$ ./osbash.sh -g gui -b cluster

What the script installs

Running this will automatically spin up 3 virtual machines in VirtualBox/KVM:

  • Controller node
  • Network node
  • Compute node

Now you have a multi-node deployment of OpenStack running with the below services installed.

OpenStack services installed on Controller node:

  • Keystone
  • Horizon
  • Glance
  • Nova
    • nova-api
    • nova-scheduler
    • nova-consoleauth
    • nova-cert
    • nova-novncproxy
    • python-novaclient
  • Neutron
    • neutron-server
  • Cinder

Openstack services installed on Network node:

  • Neutron
    • neutron-plugin-openvswitch-agent
    • neutron-l3-agent
    • neutron-dhcp-agent
    • neutron-metadata-agent

Openstack Services installed on Compute node:

  • Nova
    • nova-compute
  • Neutron
    • neutron-plugin-openvswitch-agent

How to access the services

There are two ways to access the services:

  • OpenStack Dashboard (horizon)

You can access the dashboard at: http://192.168.100.51/horizon

Admin Login:

  • Username: admin
  • Password: admin_pass

Demo User Login:

  • Username: demo
  • Password: demo_pass

You can ssh to each of the nodes by:

# Controller node
$ ssh osbash@10.0.0.11

# Network node
$ ssh osbash@10.0.0.21

# Compute node
$ ssh osbash@10.0.0.31

Credentials for all nodes:

  • Username: osbash
  • Password: osbash

After you have ssh access, you need to source the OpenStack credentials in order to access the services.

Two credential files are present on each of the nodes:

  • demo-openstackrc.sh
  • admin-openstackrc.sh

Source the following credential files

For Admin user privileges:

$ source admin-openstackrc.sh

For Demo user privileges:

$ source demo-openstackrc.sh

Now you can access the OpenStack services via CLI.

Specs

To review specifications, see http://specs.openstack.org/openstack/docs-specs/specs/liberty/traininglabs.html

Mailing lists, IRC

To contribute, join the IRC channel, #openstack-doc, on IRC freenode or write an e-mail to the OpenStack Documentation Mailing List openstack-docs@lists.openstack.org. Please use [training-labs] tag in the subject of the email message.

You might consider registering on the OpenStack Documentation Mailing List if you want to post your e-mail instantly. It may take some time for unregistered users, as it requires an administrator's approval.

Sub-team leads

Feel free to ping Roger or Pranav on the IRC channel #openstack-doc regarding any queries about the Labs section.

  • Roger Luethi
    • Email: rl@patchworkscience.org
    • IRC: rluethi
  • Pranav Salunke
    • Email: dguitarbite@gmail.com
    • IRC: dguitarbite

Meetings

Team meeting for training-labs is on alternating Thursdays on Google Hangouts. https://wiki.openstack.org/wiki/Documentation/training-labs#Meeting_Information

Wiki

Follow various links on training-labs here: https://wiki.openstack.org/wiki/Documentation/training-labs#Meeting_Information