A collection of Ansible playbooks to detect and report potential issues during TripleO deployments
The validations will help detect issues early in the deployment process and prevent field engineers from wasting time on misconfiguration or hardware issues in their environments.
All validations are written in Ansible and are written in a way that’s consumable by the Mistral validation framework or by Ansible directly. They are available independently from the UI or the command line client.
The TripleO validations require Ansible 2.0 or above:
$ sudo pip install 'ansible>=2'
Here are all the validations that currently exist. They’re grouped by the deployment stage they’re should be run on.
Validations can belong to multiple groups.
Validations that are run on a fresh machine before the undercloud is installed.
Validations that are run when the undercloud is ready to perform hardware introspection.
Validation that are run right before deploying the overcloud.
Validations that are run after the overcloud deployment finished.
Validations that are run right before a minor update of the undercloud or overcloud.
Validations that are run right before a major upgrade of the undercloud or overcloud.
All validations are written in standard Ansible with a couple of extra meta-data to provide information to the Mistral validation framework.
For people not familiar with Ansible, get started with their excellent documentation.
After the generic explanation on writing validations is a couple of concrete examples.
All validations are located in the validations
directory. It
contains a couple of subdirectories:
files
directory contains scripts that are directly executable;library
one is for custom Ansible modules available to the
validations;tasks
is for common steps that can be shared between the validations.Here is what the tree looks like:
validations
├── first_validation.yaml
├── second_validation.yaml
├── files
│ └── some_script.sh
├── library
│ ├── another_module.py
│ └── some_module.py
└── tasks
└── some_task.yaml
Each validation is an Ansible playbook with a known location and some meta-data. Here is what a minimal validation would look like:
---
- hosts: overcloud
vars:
metadata:
name: Hello World
description: This validation prints Hello World!
tasks:
- name: Run an echo command
command: echo Hello World!
It should be saved as validations/hello_world.yaml
.
As shown here, the validation playbook requires three top-level directives:
hosts
, vars -> metadata
and tasks
.
hosts
specify which nodes to run the validation on. Based on the
hosts.sample
structure, the options can be all
(run on all nodes),
undercloud
, overcloud
(all overcloud nodes), controller
and
compute
.
The vars
section serves for storing variables that are going to be
available to the Ansible playbook. The validations API uses the metadata
section to read each validation’s name and description. These values are then
reported by the API and shown in the UI.
The validations can be grouped together by specifying a groups
metadata.
Groups function similar to tags and a validation can thus be part of many
groups. Here is, for example, how to have a validation be part of the
pre-deployment and hardware groups:
metadata:
groups:
- pre-deployment
- hardware
tasks
contain a list of Ansible tasks to run. Each task is a YAML
dictionary that must at minimum contain a name and a module to use.
Module can be any module that ships with Ansible or any of the custom
ones in the library
subdirectory.
The Ansible documentation on playbooks provides more detailed information.
Tripleo-validations ships with a dynamic inventory, which contacts the various OpenStack services to provide the addresses of the deployed nodes as well as the undercloud.
Just pass -i /usr/bin/tripleo-ansible-inventory
to ansible-playbook
command:
ansible-playbook -i /usr/bin/tripleo-ansible-inventory validations/hello_world.yaml
When more flexibility than what the current dynamic inventory provides is
needed or when running validations against a host that hasn’t been deployed via
heat (such as the prep
validations), it is possible to write a custom hosts
inventory file. It should look something like this:
[undercloud]
undercloud.example.com
[overcloud:children]
controller
compute
[controller]
controller.example.com
[compute]
compute-1.example.com
compute-2.example.com
[all:vars]
ansible_ssh_user=stack
ansible_sudo=true
It will have a [group]
section for each role (undercloud
,
controller
, compute
) listing all the nodes belonging to that group. It
is also possible to create a group from other groups as done with
[overcloud:children]
in the above example. If a validation specifies
hosts: overcloud
, it will be run on any node that belongs to the
compute
or controller
groups. If a node happens to belong to both, the
validation will only be run once.
Lastly, there is an [all:vars]
section where to configure certain
Ansible-specific options.
ansible_ssh_user
will specify the user Ansible should SSH as. If that user
does not have root privileges, it is possible to instruct it to use sudo
by
setting ansible_sudo
to true
.
Learn more at the Ansible documentation page for the Inventory
In case the available Ansible modules don’t cover your
needs, it is possible to write your own. Modules belong to the
validations/library
directory.
Here is a sample module that will always fail:
#!/usr/bin/env python
from ansible.module_utils.basic import AnsibleModule
if __name__ == '__main__':
module = AnsibleModule(argument_spec={})
module.fail_json(msg="This module always fails.")
Save it as validations/library/my_module.py
and use it in a validation like
so:
tasks:
... # some tasks
- name: Running my custom module
my_module:
... # some other tasks
The name of the module in the validation my_module
must match the file name
(without extension): my_module.py
.
The custom modules can accept parameters and do more complex reporting. Please refer to the guide on writing modules in the Ansible documentation.
Learn more at the Ansible documentation page about writing custom modules.
Running the validations require ansible and a set of nodes to run them against. These nodes need to be reachable from the operator’s machine and need to have an account it can ssh to and perform passwordless sudo.
The nodes need to be present in the static inventory file or available from the dynamic inventory script depending on which one the operator chooses to use. Check which nodes are available with:
$ source stackrc
$ tripleo-ansible-inventory --list
In general, Ansible and the validations will be located on the undercloud, because it should have connectivity to all the overcloud nodes is already set up to SSH to them.
$ source ~/stackrc
$ ansible-playbook -i /usr/bin/tripleo-ansible-inventory path/to/validation.yaml
The Undercloud has a requirement of 16GB RAM. Let’s write a validation that verifies this is indeed the case before deploying anything.
Let’s create validations/undercloud-ram.yaml
and put some metadata
in there:
---
- hosts: undercloud
vars:
metadata:
name: Minimum RAM required on the undercloud
description: >
Make sure the undercloud has enough RAM.
groups:
- prep
- pre-introspection
The hosts
key will tell which server should the validation run on. The
common values are undercloud
, overcloud
(i.e. all overcloud nodes),
controller
and compute
(i.e. just the controller or the compute nodes).
The name
and description
metadata will show up in the API and the
TripleO UI so make sure to put something meaningful there. The groups
metadata applies a tag to the validation and allows to group them together in
order to perform group operations, such are running them all in one call.
Now let’s add an Ansible task to test that it’s all set up properly. Add
this under the same indentation as hosts
and vars
:
tasks:
- name: Test Output
debug: msg="Hello World!"
When running it, it should output something like this:
$ ansible-playbook -i /usr/bin/tripleo-ansible-inventory validations/undercloud-ram.yaml
PLAY [undercloud] *************************************************************
GATHERING FACTS ***************************************************************
ok: [localhost]
TASK: [Test Output] ***********************************************************
ok: [localhost] => {
"msg": "Hello World!"
}
PLAY RECAP ********************************************************************
localhost : ok=2 changed=0 unreachable=0 failed=0
Writing the full validation code is quite easy in this case because Ansible has
done all the hard work for us already. We can use the ansible_memtotal_mb
fact to get the amount of RAM (in megabytes) the tested server currently has.
For other useful values, run ansible -i /usr/bin/tripleo-ansible-inventory
undercloud -m setup
.
So, let’s replace the hello world task with a real one:
tasks:
- name: Verify the RAM requirements
fail: msg="The RAM on the undercloud node is {{ ansible_memtotal_mb }} MB, the minimal recommended value is 16 GB."
failed_when: "({{ ansible_memtotal_mb }}) < 16000"
Running this, we see:
TASK: [Verify the RAM requirements] *******************************************
failed: [localhost] => {"failed": true, "failed_when_result": true}
msg: The RAM on the undercloud node is 8778 MB, the minimal recommended value is 16 GB.
Because our Undercloud node really does not have enough RAM. Your mileage may vary.
Either way, the validation works and reports the lack of RAM properly!
failed_when
is the real hero here: it evaluates an Ansible expression (e.g.
does the node have more than 16 GB of RAM) and fails when it’s evaluated as
true.
The fail
line right above it lets us print a custom error in case of
a failure. If the task succeeds (because we do have enough RAM), nothing will
be printed out.
Now, we’re almost done, but there are a few things we can do to make this nicer on everybody.
First, let’s hoist the minimum RAM requirement into a variable. That way we’ll have one place where to change it if we need to and we’ll be able to test the validation better as well!
So, let’s call the variable minimum_ram_gb
and set it to 16
. Do this in
the vars
section:
vars:
metadata:
name: ...
description: ...
groups: ...
minimum_ram_gb: 16
Make sure it’s on the same indentation level as metadata
.
Then, update failed_when
like this:
failed_when: "({{ ansible_memtotal_mb }}) < {{ minimum_ram_gb|int * 1024 }}"
And fail
like so:
fail: msg="The RAM on the undercloud node is {{ ansible_memtotal_mb }} MB, the minimal recommended value is {{ minimum_ram_gb|int * 1024 }} MB."
And re-run it again to be sure it’s still working.
One benefit of using a variable instead of a hardcoded value is that we can now change the value without editing the yaml file!
Let’s do that to test both success and failure cases.
This should succeed but saying the RAM requirement is 1 GB:
ansible-playbook -i /usr/bin/tripleo-ansible-inventory validations/undercloud-ram.yaml -e minimum_ram_gb=1
And this should fail by requiring much more RAM than is necessary:
ansible-playbook -i /usr/bin/tripleo-ansible-inventory validations/undercloud-ram.yaml -e minimum_ram_gb=128
(the actual values may be different in your configuration – just make sure one is low enough and the other too high)
And that’s it! The validation is now finished and you can start using it in earnest.
For reference, here’s the full validation:
---
- hosts: undercloud
vars:
metadata:
name: Minimum RAM required on the undercloud
description: Make sure the undercloud has enough RAM.
groups:
- prep
- pre-introspection
minimum_ram_gb: 16
tasks:
- name: Verify the RAM requirements
fail: msg="The RAM on the undercloud node is {{ ansible_memtotal_mb }} MB, the minimal recommended value is {{ minimum_ram_gb|int * 1024 }} MB."
failed_when: "({{ ansible_memtotal_mb }}) < {{ minimum_ram_gb|int * 1024 }}"
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