Fix disk multiattach with VirtualBox 6
Starting with version 6.0, the behavior of VirtualBox with regards to disk multiattach changed. The result are error messages like: VBoxManage: error: Cannot change type for medium '<base_disk_path>': the media type 'MultiAttach' can only be used on media registered with a machine that was created with VirtualBox 4.0 or later The new code should work for both VirtualBox 6 and older versions. The workaround suggests that we may not be using the VirtualBox volumes the way they are meant to be used, but with scant documentation out there rewriting the volume logic may result in no improvement at all, so let's leave it at that for the time being. backport: rocky queens pike ocata Closes-Bug:
|1 week ago|
|doc||1 month ago|
|labs||3 days ago|
|playbooks/scripts||1 year ago|
|tools||2 years ago|
|.gitignore||9 months ago|
|.gitreview||1 month ago|
|.zuul.yaml||1 month ago|
|CONTRIBUTING.rst||3 years ago|
|HACKING.rst||7 months ago|
|LICENSE||3 years ago|
|README.rst||5 months ago|
|bindep.txt||1 year ago|
|labs.py||3 years ago|
|tox.ini||1 month ago|
Training-labs provides an automated way to deploy Vanilla OpenStack, closely following the OpenStack Install Guide.
Training-labs offers an easy way to set up an OpenStack cluster which is a good starting point for beginners to learn OpenStack, and for advanced users to test out new features, and check out different capabilities of OpenStack.
On top of that training-labs is also a good way to test the installation instructions on a regular basis.
Training-labs is a project under OpenStack Documentation. For more information see the OpenStack wiki.
VirtualBox is the default hypervisor used by training-labs. Alternatively, you can use KVM (just set
The current release is master which usually deploys the current stable OpenStack release. Unless you have a reason to go with an older release, we recommend using master.
For non-development purposes (training, etc.), the easiest way to get the code is through downloading the desired archive from OpenStack Training Labs. Unpack the archive and you are good to go.
$ cd training-labs/labs/
By default, the cluster is built on Virtualbox VMs.
Run the script by:
$ ./st.py -b cluster
The easiest and recommended way to get everything you need besides VirtualBox is to download a zip file for Windows from the Training Labs page.
The zip files include pre-generated Windows batch files.
Creates the host-only networks used by the node VMs to communicate:
Creates the base disk:
Creates the node VMs based on the base disk:
Running this will automatically spin up 2 virtual machines in VirtualBox/KVM:
Now you have a multi-node deployment of OpenStack running with the following services installed.
There are two ways to access the services:
You can access the dashboard at: http://10.0.0.11/horizon
Demo User Login:
You can ssh to each of the nodes by:
# Controller node $ ssh firstname.lastname@example.org # Compute node $ ssh email@example.com
Credentials for all nodes:
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:
Source the following credential files
For Admin user privileges:
$ source admin-openstackrc.sh
For Demo user privileges:
$ source demo-openstackrc.sh
Note: Instead 'source' you can use '.', or you define an alias. Now you can access the OpenStack services via CLI.
To review specifications, see Training-labs
To contribute, join the IRC channel,
#openstack-doc, on IRC freenode or write an e-mail to the OpenStack Development Mailing List
firstname.lastname@example.org. Please use
[training-labs] tag in the subject of the email message.
You may have to subscribe to the OpenStack Development Mailing List to have your mail accepted by the mailing list software.
Feel free to ping Roger, Julen, or Pranav via email or on the IRC channel
#openstack-doc regarding any queries about training-labs.
Training-labs uses the Doc Team Meeting: https://wiki.openstack.org/wiki/Meetings/DocTeamMeeting
Follow various links on training-labs here: https://wiki.openstack.org/wiki/Documentation/training-labs