Ansible and Ansible Tower special variables

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Ansible and Ansible Tower provide a powerful variable system. At the same time, there are some variables reserved to one or the other, which cannot be used by others, but can be helpful. This post lists all reserved and magic variables and also important keywords.

Ansible Variables

Variables in Ansible are a powerful tool to influence and control your automation execution. In fact, I’ve dedicated a fare share of posts to the topic over the years:

The official documentation of Ansible variables is also quite comprehensive.

The variable system is in fact so powerful that Ansible uses it itself. There are certain variables which are reserved, the so called magic variables.

The given documentation lists many of them – but is missing the Tower ones. For that reason this post list all magic variables in Ansible and Ansible Tower with references to more information.

Note that the variables and keywords might be different for different Ansible versions. The lists provided here are for Ansible 2.8 which is the current release and als shipped in Fedora – and Tower 3.4/3.5.

Reserved & Magic Variables

Magic Variables

The following list shows true magic variables. They are reserved internally and are overwritten by Ansible if needed. A “(D)” highlights that the variable is deprecated.

ansible_check_mode
ansible_dependent_role_names
ansible_diff_mode
ansible_forks
ansible_inventory_sources
ansible_limit
ansible_loop
ansible_loop_var
ansible_play_batch (D)
ansible_play_hosts (D)
ansible_play_hosts_all
ansible_play_role_names
ansible_playbook_python
ansible_role_names
ansible_run_tags
ansible_search_path
ansible_skip_tags
ansible_verbosity
ansible_version
group_names
groups
hostvars
inventory_hostname
inventory_hostname_short
inventory_dir
inventory_file
omit
play_hosts (D)
ansible_play_name
playbook_dir
role_name
role_names
role_path

Source: docs.ansible.com/ansible/latest/reference_appendices/special_variables.html

Facts

Facts are not magic variables because they are not internal. But they are collected during facts gathering or execution of the setup module, so it helps to keep them in mind. There are two “main” variables related to facts, and a lot of other variables depending on what the managed node has to offer. Since those are different from system to system, it is tricky to list them all. But they can be easily identified by the leading ansible_.

ansible_facts
ansible_local
ansible_*

Sources: docs.ansible.com/ansible/latest/reference_appendices/special_variables.html & docs.ansible.com/ansible/latest/user_guide/playbooks_variables.html

Connection Variables

Connection variables control the way Ansible connects to target machines: what connection plugin to use, etc.

ansible_become_user
ansible_connection
ansible_host
ansible_python_interpreter
ansible_user

Soource: docs.ansible.com/ansible/latest/reference_appendices/special_variables.html

Ansible Tower

Tower has its own set of magic variables which are used internally to control the execution of the automation. Note that those variables can optionally start with awx_ instead of tower_.

tower_job_id
tower_job_launch_type
tower_job_template_id
tower_job_template_name
tower_user_id
tower_user_name
tower_schedule_id
tower_schedule_name
tower_workflow_job_id
tower_workflow_job_name

Source: docs.ansible.com/ansible-tower/latest/html/userguide/job_templates.html

Keywords

Keywords are strictly speaking not variables. In fact, you can even set a variable named as a key word. Instead, they are the parts of a playbook that make a playbook work: think of the keys hosts, tasks, name or even the parameters of a module.

It is just important to keep those keywords in mind – and it certainly helps when you name your variables in a way that they are not mixed up with keywords by chance.

The following lists shows all keywords by where they can appear. Note that some keywords are listed multiple times because they can be used at different places.

Play

any_errors_fatal
become
become_flags
become_method
become_user
check_mode
collections
connection
debugger
diff
environment
fact_path
force_handlers
gather_facts
gather_subset
gather_timeout
handlers
hosts
ignore_errors
ignore_unreachable
max_fail_percentage
module_defaults
name
no_log
order
port
post_tasks
pre_tasks
remote_user
roles
run_once
serial
strategy
tags
tasks
vars
vars_files
vars_prompt

Source: docs.ansible.com/ansible/latest/reference_appendices/playbooks_keywords.html

Role

any_errors_fatal
become
become_flags
become_method
become_user
check_mode
collections
connection
debugger
delegate_facts
delegate_to
diff
environment
ignore_errors
ignore_unreachable
module_defaults
name
no_log
port
remote_user
run_once
tags
vars
when

Source: docs.ansible.com/ansible/latest/reference_appendices/playbooks_keywords.html

Block

always
any_errors_fatal
become
become_flags
become_method
become_user
block
check_mode
collections
connection
debugger
delegate_facts
delegate_to
diff
environment
ignore_errors
ignore_unreachable
module_defaults
name
no_log
port
remote_user
rescue
run_once
tags
vars
when

Source: docs.ansible.com/ansible/latest/reference_appendices/playbooks_keywords.html

Task

action
any_errors_fatal
args
async
become
become_flags
become_method
become_user
changed_when
check_mode
collections
connection
debugger
delay
delegate_facts
delegate_to
diff
environment
failed_when
ignore_errors
ignore_unreachable
local_action
loop
loop_control
module_defaults
name
no_log
notify
poll
port
register
remote_user
retries
run_once
tags
until
vars
when
with_<lookup_plugin>

Source: docs.ansible.com/ansible/latest/reference_appendices/playbooks_keywords.html

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Of debugging Ansible Tower and underlying cloud images

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Recently I was experimenting with Tower’s isolated nodes feature – but somehow it did not work in my environment. Debugging told me a lot about Ansible Tower – and also why you should not trust arbitrary cloud images.

Background – Isolated Nodes

Ansible Tower has a nice feature called “isolated nodes”. Those are dedicated Tower instances which can manage nodes in separated environments – basically an Ansible Tower Proxy.

An Isolated Node is an Ansible Tower node that contains a small piece of software for running playbooks locally to manage a set of infrastructure. It can be deployed behind a firewall/VPC or in a remote datacenter, with only SSH access available. When a job is run that targets things managed by the isolated node, the job and its environment will be pushed to the isolated node over SSH, where it will run as normal.

Ansible Tower Feature Spotlight: Instance Groups and Isolated Nodes

Isolated nodes are especially handy when you setup your automation in security sensitive environments. Think of DMZs here, of network separation and so on.

I was fooling around with a clustered Tower installation on RHEL 7 VMs in a cloud environment when I run into trouble though.

My problem – Isolated node unavailable

Isolated nodes – like instance groups – have a status inside Tower: if things are problematic, they are marked as unavailable. And this is what happened with my instance isonode.remote.example.com running in my lab environment:

Ansible Tower showing an instance node as unavailable

I tried to turn it “off” and “on” again with the button in the control interface. It made the node available, it was even able to executed jobs – but it became quickly unavailable soon after.

Analysis

So what happened? The Tower logs showed a Python error:

# tail -f /var/log/tower/tower.log
fatal: [isonode.remote.example.com]: FAILED! => {"changed": false,
"module_stderr": "Shared connection to isonode.remote.example.com
closed.\r\n", "module_stdout": "Traceback (most recent call last):\r\n
File \"/var/lib/awx/.ansible/tmp/ansible-tmp-1552400585.04
-60203645751230/AnsiballZ_awx_capacity.py\", line 113, in <module>\r\n
_ansiballz_main()\r\n  File \"/var/lib/awx/.ansible/tmp/ansible-tmp
-1552400585.04-60203645751230/AnsiballZ_awx_capacity.py\", line 105, in
_ansiballz_main\r\n    invoke_module(zipped_mod, temp_path,
ANSIBALLZ_PARAMS)\r\n  File \"/var/lib/awx/.ansible/tmp/ansible-tmp
-1552400585.04-60203645751230/AnsiballZ_awx_capacity.py\", line 48, in
invoke_module\r\n    imp.load_module('__main__', mod, module, MOD_DESC)\r\n
File \"/tmp/ansible_awx_capacity_payload_6p5kHp/__main__.py\", line 74, in
<module>\r\n  File \"/tmp/ansible_awx_capacity_payload_6p5kHp/__main__.py\",
line 60, in main\r\n  File
\"/tmp/ansible_awx_capacity_payload_6p5kHp/__main__.py\", line 27, in
get_cpu_capacity\r\nAttributeError: 'module' object has no attribute
'cpu_count'\r\n", "msg": "MODULE FAILURE\nSee stdout/stderr for the exact
error", "rc": 1}

PLAY RECAP *********************************************************************
isonode.remote.example.com : ok=0    changed=0    unreachable=0    failed=1  

Apparently a Python function was missing. If we check the code we see that indeed in line 27 of file awx_capacity.py the function psutil.cpu_count() is called:

def get_cpu_capacity():
    env_forkcpu = os.getenv('SYSTEM_TASK_FORKS_CPU', None)
    cpu = psutil.cpu_count()

Support for this function was added in version 2.0 of psutil:

2014-03-10
Enhancements
424: [Windows] installer for Python 3.X 64 bit.
427: number of logical and physical CPUs (psutil.cpu_count()).

psutil history

Note the date here: 2014-03-10 – pretty old! I check the version of the installed package, and indeed the version was pre-2.0:

$ rpm -q --queryformat '%{VERSION}\n' python-psutil
1.2.1

To be really sure and also to ensure that there was no weird function backporting, I checked the function call directly on the Tower machine:

# python
Python 2.7.5 (default, Sep 12 2018, 05:31:16) 
[GCC 4.8.5 20150623 (Red Hat 4.8.5-36)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import inspect
>>> import psutil as module
>>> functions = inspect.getmembers(module, inspect.isfunction)
>>> functions
[('_assert_pid_not_reused', <function _assert_pid_not_reused at
0x7f9eb10a8d70>), ('_deprecated', <function deprecated at 0x7f9eb38ec320>),
('_wraps', <function wraps at 0x7f9eb414f848>), ('avail_phymem', <function
avail_phymem at 0x7f9eb0c32ed8>), ('avail_virtmem', <function avail_virtmem at
0x7f9eb0c36398>), ('cached_phymem', <function cached_phymem at
0x7f9eb10a86e0>), ('cpu_percent', <function cpu_percent at 0x7f9eb0c32320>),
('cpu_times', <function cpu_times at 0x7f9eb0c322a8>), ('cpu_times_percent',
<function cpu_times_percent at 0x7f9eb0c326e0>), ('disk_io_counters',
<function disk_io_counters at 0x7f9eb0c32938>), ('disk_partitions', <function
disk_partitions at 0x7f9eb0c328c0>), ('disk_usage', <function disk_usage at
0x7f9eb0c32848>), ('get_boot_time', <function get_boot_time at
0x7f9eb0c32a28>), ('get_pid_list', <function get_pid_list at 0x7f9eb0c4b410>),
('get_process_list', <function get_process_list at 0x7f9eb0c32c08>),
('get_users', <function get_users at 0x7f9eb0c32aa0>), ('namedtuple',
<function namedtuple at 0x7f9ebc84df50>), ('net_io_counters', <function
net_io_counters at 0x7f9eb0c329b0>), ('network_io_counters', <function
network_io_counters at 0x7f9eb0c36500>), ('phymem_buffers', <function
phymem_buffers at 0x7f9eb10a8848>), ('phymem_usage', <function phymem_usage at
0x7f9eb0c32cf8>), ('pid_exists', <function pid_exists at 0x7f9eb0c32140>),
('process_iter', <function process_iter at 0x7f9eb0c321b8>), ('swap_memory',
<function swap_memory at 0x7f9eb0c327d0>), ('test', <function test at
0x7f9eb0c32b18>), ('total_virtmem', <function total_virtmem at
0x7f9eb0c361b8>), ('used_phymem', <function used_phymem at 0x7f9eb0c36050>),
('used_virtmem', <function used_virtmem at 0x7f9eb0c362a8>), ('virtmem_usage',
<function virtmem_usage at 0x7f9eb0c32de8>), ('virtual_memory', <function
virtual_memory at 0x7f9eb0c32758>), ('wait_procs', <function wait_procs at
0x7f9eb0c32230>)]

Searching for a package origin

So how to solve this issue? My first idea was to get this working by updating the entire code part to the multiprocessor lib:

# python
Python 2.7.5 (default, Sep 12 2018, 05:31:16) 
[GCC 4.8.5 20150623 (Red Hat 4.8.5-36)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import multiprocessing
>>> cpu = multiprocessing.cpu_count()
>>> cpu
4

But while I was filling a bug report I wondered why RHEL shipped such an ancient library. After all, RHEL 7 was released in June 2014, and psutil had cpu_count available since early 2014! And indeed, a quick search for the package via the Red Hat package search showed a weird result: python-psutil was never part of base RHEL 7! It was only shipped as part of some very, very old OpenStack channels:

access.redhat.com package search, results for python-psutil

Newer OpenStack channels in fact come along with newer versions of python-psutil.

So how did this outdated package end up on this RHEL 7 image? Why was it never updated?

The cloud image is to blame! The package was installed on it – most likely during the creation of the image: python-psutil is needed for OpenStack Heat, so I assume that these RHEL 7 images where once created via OpenStack and then used as the default image in this demo environment.

And after the initial creation of the image the Heat packages were forgotten. In the meantime the image was updated to newer RHEL versions, snapshots were created as new defaults and so on. But since the package in question was never part of the main RHEL repos, it was never changed or removed. It just stayed there. Waiting, apparently, for me 😉

Conclusion

This issue showed me how tricky cloud images can be. Think about your own cloud images: have you really checked all all of them and verified that no package, no start up script, no configuration was changed from the Linux distribution vendor’s base setup?

With RPMs this is still manageable, you can track if packages are installed which are not present in the existing channels. But did someone install something with pip? Or any other way?

Take my case: an outdated version of a library was called instead of a much, much more recent one. If there would have been a serious security issue with the library in the meantime, I would have been exposed although my update management did not report any library to be updated.

I learned my lesson to be more critical with cloud images, checking them in more detail in the future to avoid having nasty surprises during production. And I can just recommend that you do that as well.

Flatpak – a solution to the Linux desktop packaging problem [Update]

Linux packaging was a nightmare for years. But recently serious contenders came up claiming to solve the challenge: first containers changed how code is deployed on servers for good. And now a solution for the desktops is within reach. Meet Flatpak!

Preface

In the beginning I probably should admit that over the years I identified packaging within the Linux ecosystem as a fundamental problem. It prevented wider adoption of Linux in general, but especially on the desktop. I was kind of obsessed with the topic.

The general arguments were/are:

  • Due to a missing standard it was not easy enough for developers to package software. If they used one of the formats out there they could only target a sub-set of distributions. This lead to lower adoption of the software on Linux, making it a less attractive platform.
  • Since Linux was less attractive for developers, less applications were created on/ported to Linux. This lead to a smaller ecosystem. Thus it was less attractive to users since they could not find appealing or helpful applications.
  • Due to missing packages in an easy-accessible format, installing software was a challenge as soon as it was not packaged for the distribution in use. So Linux was a lot less attractive for users because few software was available.

History, server side

In hindsight I must say the situation was not as bad as I thought on the server level: Linux in the data center grew and grew. Packaging simply did not matter that much because admins were used to problems deploying applications on servers anyway and they had the proper knowledge (and time) to tackle challenges.

Additionally, the recent rise of container technologies like Docker had a massive impact: it made deploying of apps much easier and added other benefits like sandboxing, detailed access permissions, clearer responsibilities especially with dev and ops teams involved, and less dependency hell problems. Together with Kubernetes it seems as there is an actual standard evolving of how software is deployed on Linux servers.

To summarize, in the server ecosystem things never were as bad, and are quite good these days. Given that Azure serves more Linux servers than Windows servers there are reasons to believe that Linux is these days the dominant server platform and that Windows is more and more becoming a niche platform.

History, client side

On the desktop side things were bad right from the start. Distribution specific packaging made compatibility a serious problem, incompatible packaging formats with RPMs and DEBs made it worse. One reason why no package format ever won was probably that no solution offered real benefits above the other. Given today’s solutions for packaging software out there RPM and DEB are missing major advantages like sandboxing and permission systems. They are helplessly outdated, I question if they are suited for software packaging at all today.

There were attempts to solve the problem. There were attempts at standardization – for example via the LSB – but that did not gather enough attraction. There were platform agnostic packaging solutions. Most notably is Klik which started already 15 years ago and got later renamed to AppImage. But despite the good intentions and the ease of use it never gained serious attention over the years.

But with the approach of Docker things changed: people saw the benefits of container formats and the technology technology for such approaches was widely available. So people gave the idea another try: Flatpak.

Flatpak

Flatpak is a “technology for building and distributing desktop applications on Linux”. It is an attempt to establish an application container format for Linux based desktops and make them easy consumable.

According to the history of Flatpak the initial idea goes way back. Real work started in 2014, and the first release was in 2015. It was developed initially in the ecosystem of Fedora and Red Hat, but soon got attention from other distributions as well.

Many features look somewhat similar to the typical features associated with container tools like Docker:

  • Build for every distro
  • Consistent environments
  • Full control over dependencies
  • Easy to use  build tools
  • Future-proof builds
  • Distribution of packages made easy

Additionally it features a sandboxing environment and a permissions system.

The most appealing feature for end users is that it makes it simple to install packages and that there are many packages available because developers only have to built them once to support a huge range of distributions.

By using Flatpak the software version is also not tied to the distribution update cycle. Flatpak can update all installed packages centrally as well.

Flathub

One thing I like about Flatpak is that it was built with repositories (“shops”) baked right in. There is a large repository called flathub.org where developers can submit their applications to be found and consumed by users:

The interface is simple but has a somewhat proper design. Each application features screenshots and a summary. The apps themselves are grouped by categories. The ever changing list of new & updated apps shows that the list of apps is ever growing. A list of the two dozen most popular apps is available as well.

I am a total fan of Open Source but I do like the fact that there are multiple closed source apps listed in the store. It shows that the format can be used for such use cases. That is a sign of a healthy ecosystem. Also, there are quite a few games which is always good 😉

Of course there is lots of room for improvement: at the time of writing there is no way to change or filter the sorting order of the lists. There is no popularity rating visible and no way to rate applications or leave comments.

Last but not least, there is currently little support from external vendors. While you find many closed source applications in Flathub, hardly any of them were provided by the software vendor. They were created by the community but are not affiliated with the vendors. To have a broader acceptance of Flatpak the support of software vendors is crucial, and this needs to be highlighted in the web page as well (“verified vendor” or similar).

Hosting your own hub

As mentioned Flatpak has repositories baked in, and it is well documented. It is easy to generate your own repository for your own flatpaks. This is especially appealing to projects or vendors who do not want to host their applications themselves.

While today it is more or less common to use a central market (Android, iOS, etc.) some still prefer to keep their code in there hands. It sometimes makes it easier to provide testing and development versions. Other use cases are software which is just developed and used in-house, or the mirroring of existing repositories for security or offline reasons: such use cases require local hubs, and it is no problem at all to bring them up with Flatpak.

Flatpak, distribution support

Flatpak is currently supported on most distributions. Many of them have the support built in right from the start, others, most notably Ubuntu, need to install some software first. But in general it is quite easy to get started – and once you did, there are hundreds of applications you can use.

What about the other solutions?

Of course Flatpak is not the only solution out there. After all, this is the open source world we are talking about, so there must be other solutions 😉

Snap & Snapcraft

Snapcraft is a way to “deliver and update your app on any Linux distribution – for desktop, cloud, and Internet of Things.” The concept and idea behind it is somewhat similar to Flatpak, with a few notable differences:

  • Snapcraft also target servers, while Flatpak only targets desktops
  • Among the servers, Snapcraft additionally has iot devices as a specific target group
  • Snapcraft does not support additional repositories; there is only one central market place everyone needs to use, and there is no real way to change that

Some more technical differences are in the way packages are built, how the sandbox work and so on, but we will noch focus on those in this post.

The Snapcraft market place called snapcraft.io provides lists of applications, but is much more mature than Flathub: it has vendor testimonials, features verified accounts, multiple versions like beta or development can be picked from within the market, there are case stories, for each app additional blog posts are listed, there is integration with social accounts, you can even see the distribution by countries and Linux flavors.

And as you can see, Snapcraft is endorsed and supported by multiple companies today which are listed on the web page and which maintain their applications in the market.

Flathub has a lot to learn until it reaches the same level of maturity. However, while I’d say that snapcraft.io is much more mature than Flathub it also misses the possibility to rate packages, or just list them by popularity. Am I the only one who wants that?

The main disadvantage I see is the monopoly. snapcraft.io is tightly controlled by a single company (not a foundation or similar). It is of course Canonical’s full right to do so, and the company and many others argue that this is not different from what Apple does with iOS. However, the Linux ecosystem is not the Apple ecosystem, and in the Linux ecosystem there are often strong opinions about monopolies, closed source solutions and related topics which might lead to acceptance problems in the long term.

Also, technically it is not possible to launch your own central server for example for in-house development, or for hosting a local mirror, or to support offline environments or for other reasons. To me this is particularly surprising given that Snapcraft targets specifically iot devices, and I would run iot devices in an closed network wherever I can – thus being unable to connect to snapcraft.io. The only solution I was able to identify was running a http proxy, which is far from the optimal solution.

Another a little bit unusual feature of Snapcraft is that updates are installed automatically, thanks to theo.9dor for the hint:

The good news is that snaps are updated automatically in the background every day! 

https://tutorials.ubuntu.com/tutorial/basic-snap-usage#2

While in the end a development model with auto deployments, even dozens per day, is a worthwhile goal I am not sure if everyone is there yet.

So while Snapcraft has a mature market place, targets much more use cases and provides more packages to this date, I do wonder how it will turn out in the long run given that we are talking about the Linux ecosystem here. And while Canonical has quite some experience to develop their own solutions outside the “rest” of the community, those attempts seldom worked out.

AppImage

I’ve already mentioned AppImage above and I’ve written about it in the past when it was still called Klik. AppImage is “way for upstream developers to provide native binaries for Linux”. The result is basically a file that contains your entire application and which you can copy everywhere. It exists for more than a dozen years now.

The thing that is probably most worth mentioning about it is that it never caught on. After all, already long time ago it provided many impressive features, and made it possible to install software cross distribution. Many applications where also available as AppImage – and yet I never saw wider adoption. It seems to me that it only got traction recently because Snapcraft and Flatpak entered the market and kind of dragged it with them.

I’d love to understand why that is the case, or have an answer to the “why”. I only have few ideas but those are just ideas, and not explanations why AppImage, in all the years, never managed to become the Docker of the Linux desktop.

Maybe one problem was that it never featured a proper store: today we know from multiple examples on multiple platforms that a store can mean the difference. A central place for the users to browse, get a first idea of the app, leave comments and rate the application. Docker has a central “store”, Android and iOS have one, Flatpak and Snapcraft have one. However, AppImage never put a focus on that, and I do wonder if this was a missed opportunity. And no, appimage.github.io/apps is not a store.

Another difference to the other tools is that AppImage always focused on the Open Source tools. Don’t get me wrong, I appreciate it – but open source tools like Digikam were available on every distribution anyway. If AppImage would have focused to reach out to closed source software vendors as well, together with marketing this aggressively, maybe things would have turned out differently. You do not only need to make software easily available to users, you also need to make software available the people want.

Last but not least, AppImage always tried to provide as many features as possible, while it might have benefited from focusing on some and marketing them stronger. As an example, AppImage advertises that it can run with and without sandboxing. However, sandboxing is a large benefit of using such a solution to begin with. Another thing is integrated updates: there is a way to automatically update all appimages on a system, but it is not built in. If both would have been default and not optional, things maybe would have been different.

But again, these are just ideas, attempts to find explanations. I’d be happy if someone has better ideas.

Disadvantages of the Flatpak approach

There are some disadvantages with the Flatpak approach – or the Snapcraft one, or in general with any container approach. Most notably: libraries and dependencies.

The basic argument here is: all dependencies are kept in each package. This means:

  • Multiple copies of the same libraries on the system, leading to larger disk consumption
  • Multiple copies of the same library in the RAM during execution, leading to larger memory consumption
  • And probably most important: if a library has a security problem, each and every package has to be updated

Especially the last part is crucial: in case of a serious library security problem the user has to rely on each and every package vendor that they update the library in the package and release an updated version. With a dependency based system this is usually not the case.

People often compare this problem to the Windows or Java world were a similar situation exists. However, while the underlying problem is existent and serious, with Flatpak at least there is a sandbox and a permission system something which was not the case in former Windows versions.

There needs to be made a trade off between the advanced security through permissions and sandboxing vs the risk of having not-updated libraries in those packages. That trade off is not easily done.

But do we even need something like Flatpak?

This question might be strange, given the needs I identified in the past and my obvious enthusiasm for it. However, these days more and more apps are created as web applications – the importance of the desktop is shrinking. The dominant platform for users these days are mobile phones and tablets anyway. I would even go so far to say that in the future desktops will still be there but mainly to launch a web browser

But we are not there yet and today there is still the need for easy consumption of software on Linux desktops. I would have hoped though to see this technology and this much traction and distribution and vendor support 10 years ago.

Conclusion

Well – as I mentioned early on, I can get somewhat obsessed with the topic. And this much too long blog post shows this for sure 😉

But as a conclusion I say that the days of difficult-to-install-software on Linux desktops are gone. I am not sure if Snapcraft or Flatpak will “win” the race, we have to see that.

At the same time we have to face that desktops in general are just not that important anymore.  But until then, I am very happy that it became so much easier for me to install certain pieces of software in up2date versions on my machine.

Ansible community modules for Oracle DB & ASM

Ansible LogoBesides the almost thousand modules shipped with Ansible, there are many more community modules out there developed independently. A remarkable example is a set of modules to manage Oracle DBs.

The Ansible module system is a great way to improve data center automation: automation tasks do not have to be programmed “manually” in shell code, but can be simply executed by calling the appropriate module with the necessary parameters. Besides the fact that an automation user does not have to remember the shell code the modules are usually also idempotent, thus a module can be called multiple times and only changes something when it is needed.

This only works when a module for the given task exists. The list of Ansible modules is huge, but does not cover all tasks out there. For example quite some middleware products are not covered by Ansible modules (yet?). But there are also community modules out there, not part of the Ansible package, but nevertheless of high quality and developed actively.

A good example of such 3rd party modules are the Oracle DB & ASM modules developed by oravirt aka Mikael Sandström, in a community fashion. Oracle DBs are quite common in the daily enterprise IT business. And since automation is not about configuring single servers, but about integrating all parts of a business process, Oracle DBs should also be part of the automation. Here the extensive set of Ansible modules comes in handy. According to the README (shortened):

  • oracle_user
    • Creates & drops a user.
    • Grants privileges only
  • oracle_tablespace
    • Manages normal(permanent), temp & undo tablespaces (create, drop, make read only/read write, offline/online)
    • Tablespaces can be created as bigfile, autoextended
  • oracle_grants
    • Manages privileges for a user
    • Grants/revokes privileges
    • Handles roles/sys privileges properly.
    • The grants can be added as a string (dba,’select any dictionary’,’create any table’), or in a list (ie.g for use with with_items)
  • oracle_role
    • Manages roles in the database
  • oracle_parameter
    • Manages init parameters in the database (i.e alter system set parameter…)
    • Also handles underscore parameters. That will require using mode=sysdba, to be able to read the X$ tables needed to verify the existence of the parameter.
  • oracle_services
    • Manages services in an Oracle database (RAC/Single instance)
  • oracle_pdb
    • Manages pluggable databases in an Oracle container database
    • Creates/deletes/opens/closes the pdb
    • saves the state if you want it to. Default is yes
    • Can place the datafiles in a separate location
  • oracle_sql
    • 2 modes: sql or script
    • Executes arbitrary sql or runs a script
  • oracle_asmdg
    • Manages ASM diskgroup state. (absent/present)
    • Takes a list of disks and makes sure those disks are part of the DG. If the disk is removed from the disk it will be removed from the DG.
  • oracle_asmvol
    • Manages ASM volumes. (absent/present)
  • oracle_ldapuser
    • Syncronises users/role grants from LDAP/Active Directory to the database
  • oracle_privs
    • Manages system and object level grants
    • Object level grant support wildcards, so now it is possible to grant access to all tables in a schema and maintain it automatically!

I have not yet had the change to test the modules, but I think they are worth a look. The amount of quality code, the existing documentation and also the ongoing development shows an active and healthy project, development important and certainly relevant modules. Please note: these modules are not part of the Ansible community, nor part of any offering from Oracle or anyone else. So use them at your own risk, they probably will eat your data. And kittens!

So, if you are dealing with Oracle DBs these modules might be worth to take a look. And I hope they will be pushed upstream soon.

[Short Tip] Fix mount problems in RHV during GlusterFS mounts

Gluster Logo

When using Red Hat Virtualization or oVirt together with GLusterFS, there might be a strange error during the first creation of a storage domain:

Failed to add Storage Domain xyz.

One of the rather easy to fix reasons might be a permission problem: an initial Gluster exported file system belongs to the user root. However, the virtualization manager (ovirt-m bzw. RHV-M) does not have root rights and such needs another ownership.

In such cases, the fix is to mount the exported volume & set the user rights to the rhv-m user.

$ sudo mount -t glusterfs 192.168.122.241:my-vol /mnt
# cd /mnt/
# chown -R 36.36 .

Afterwarsd, the volume can be mounted properly. Some more general details can be found at RH KB 78503.

[Howto] Writing an Ansible module for a REST API

Ansible LogoAnsible comes along with a great set of modules. But maybe your favorite tool is not covered yet and you need to develop your own module. This guide shows you how to write an Ansible module – when you have a REST API to speak to.

Background: Ansible modules

Ansible is a great tool to automate almost everything in an IT environment. One of the huge benefits of Ansible are the so called modules: they provide a way to address automation tasks in the native language of the problem. For example, given a user needs to be created: this is usually done by calling certain commandos on the shell. In that case the automation developer has to think about which command line tool needs to be used, which parameters and options need to be provided, and the result is most likely not idempotent. And its hard t run tests (“checks”) with such an approach.

Enter Ansible user modules: with them the automation developer only has to provide the data needed for the actual problem like the user name, group name, etc. There is no need to remember the user management tool of the target platform or to look up parameters:

$ ansible server -m user -a "name=abc group=wheel" -b

Ansible comes along with hundreds of modules. But what is if your favorite task or tool is not supported by any module? You have to write your own Ansible module. If your tools support REST API, there are a few things to know which makes it much easier to get your module running fine with Ansible. These few things are outlined below.

REST APIs and Python libraries in Ansible modules

According to Wikipedia, REST is:

… the software architectural style of the World Wide Web.

In short, its a way to write, provide and access an API via usual HTTP tools and libraries (Apache web server, Curl, you name it), and it is very common in everything related to the WWW.

To access a REST API via an Ansible module, there are a few things to note. Ansible modules are usually written in Python. The library of choice to access URLs and thus REST APIs in Python is usually urllib. However, the library is not the easiest to use and there are some security topics to keep in mind when these are used. Out of these reasons alternative libraries like Python requests came up in the past and are pretty common.

However, using an external library in an Ansible module would add an extra dependency, thus the Ansible developers added their own library inside Ansible to access URLs: ansible.module_utils.urls. This one is already shipped with Ansible – the code can be found at lib/ansible/module_utils/urls.py – and it covers the shortcomings and security concerns of urllib. If you submit a module to Ansible calling REST APIs the Ansible developers usually require that you use the inbuilt library.

Unfortunately, currently the documentation on the Ansible url library is sparse at best. If you need information about it, look at other modules like the Github, Kubernetes or a10 modules. To cover that documentation gap I will try to cover the most important basics in the following lines – at least as far as I know.

Creating REST calls in an Ansible module

To access the Ansible urls library right in your modules, it needs to be imported in the same way as the basic library is imported in the module:

from ansible.module_utils.basic import *
from ansible.module_utils.urls import *

The main function call to access a URL via this library is open_url. It can take multiple parameters:

def open_url(url, data=None, headers=None, method=None, use_proxy=True,
        force=False, last_mod_time=None, timeout=10, validate_certs=True,
        url_username=None, url_password=None, http_agent=None,
force_basic_auth=False, follow_redirects='urllib2'):

The parameters in detail are:

  • url: the actual URL, the communication endpoint of your REST API
  • data: the payload for the URL request, for example a JSON structure
  • headers: additional headers, often this includes the content-type of the data stream
  • method: a URL call can be of various methods: GET, DELETE, PUT, etc.
  • use_proxy: if a proxy is to be used or not
  • force: force an update even if a 304 indicates that nothing has changed (I think…)
  • last_mod_time: the time stamp to add to the header in case we get a 304
  • timeout: set a timeout
  • validate_certs: if certificates should be validated or not; important for test setups where you have self signed certificates
  • url_username: the user name to authenticate
  • url_password: the password for the above listed username
  • http_agent: if you wnat to set the http agent
  • force_basic_auth: for ce the usage of the basic authentication
  • follow_redirects: determine how redirects are handled

For example, to fire a simple GET to a given source like Google most parameters are not needed and it would look like:

open_url('https://www.google.com',method="GET")

A more sophisticated example is to push actual information to a REST API. For example, if you want to search for the domain example on a Satellite server you need to change the method to PUT, add a data structure to set the actual search string ({"search":"example"}) and add a corresponding content type as header information ({'Content-Type':'application/json'}). Also, a username and password must be provided. Given we access a test system here the certification validation needs to be turned off also. The resulting string looks like this:

open_url('https://satellite-server.example.com/api/v2/domains',method="PUT",url_username="admin",url_password="abcd",data=json.dumps({"search":"example"}),force_basic_auth=True,validate_certs=False,headers={'Content-Type':'application/json'})

Beware that the data json structure needs to be processed by json.dumps. The result of the query can be formatted as json and further used as a json structure:

resp = open_url(...)
resp_json = json.loads(resp.read())

Full example

In the following example, we query a Satellite server to find a so called environment ID for two given parameters, an organization ID and an environment name. To create a REST call for this task in a module multiple, separate steps have to be done: first, create the actual URL endpoint. This usually consists of the server name as a variable and the API endpoint as the flexible part which is different in each REST call.

server_name = 'https://satellite.example.com'
api_endpoint = '/katello/api/v2/environments/'
my_url = server_name + api_endpoint

Besides the actual URL, the payload must be pieced together and the headers need to be set according to the content type of the payload – here json:

headers = {'Content-Type':'application/json'}
payload = {"organization_id":orga_id,"name":env_name}

Other content types depends on the REST API itself and on what the developer prefers. JSON is widely accepted as a good way to go for REST calls.

Next, we set the user and password and launch the call. The return data from the call are saved in a variable to analyze later on.

user = 'abc'
pwd = 'def'
resp = open_url(url_action,method="GET",headers=headers,url_username=module.params.get('user'),url_password=module.params.get('pwd'),force_basic_auth=True,data=json.dumps(payload))

Last but not least we transform the return value into a json construct, and analyze it: if the return value does not contain any data – that means the value for the key total is zero – we want the module to exit with an error. Something went wrong, and the automation administrator needs to know that. The module calls the built-in error functionmodule.fail_json. But if the total is not zero, we get out the actual environment ID we were looking for with this REST call from the beginning – it is deeply hidden in the json structure, btw.

resp_json = json.loads(resp.read())
if resp_json["total"] == 0:
    module.fail_json(msg="Environment %s not found." % env_name)
env_id = resp_json["results"][0]["id"]

Summary

It is fairly easy to write Ansible modules to access REST APIs. The most important part to know is that an internal, Ansible provided library should be used, instead of the better known urllib or requests library. Also, the actual library documentation is still pretty limited, but that gap is partially filled by the above post.

Impressions from #AnsibleFest London 2016 [Update]

Ansible LogoThe #AnsibleFest was taking place in London, and I was luckily able to attend. This post shares some impressions from the event, together with interesting announcements and stories.

Update: The slides of the various presentations are now available.

Preface

The #AnsibleFest London 2016 took place near the O2 Arena and lasted the entire day. The main highlight of the conference was the network automation coming along with Ansible now. Other very interesting talks covered very helpful tips about managing Windows Servers, the 101 on modules, how to implement continuous deployment, the journey of a french bank towards DevOps, how Cisco devices can be managed and how to handle immutable infrastructure. All focused on Ansible, of course.

But while the conference took place during Thursday, the #AnsibleFest started already the evening before: at the social event Ansible Social.
Ansible Social
And it was a wonderful evening: many people from Ansible, partners, coworkers from Red Hat and others were there to enjoy drinks, food and chatting through the evening. Getting to know many of the people there went pretty well, it was a friendly bunch meeting at a pretty nice place.
Ansible Social

Keynote

Upon arrival at the conference area one of the sponsor desks immediately caught the eye: Cisco!
20160218_084833-01
For everyone following Ansible news closely it was obvious that networking would be a big topic, especially since it was about to be featured twice during the day, once by Peter Sprygada from Ansible and later on by Fabrizio Maccioni from Cisco.

And this impression was confirmed when Todd Barr came to the stage and talked about the current state of Ansible and what to expect in the near future: networking is a big topic for Ansible right now, they are pushing resources into the topic and already hinted that there would be a larger announcement during the #AnsibleFest. During the presentation the strengths of Ansible were of course emphasized again: that it is simple to setup, to understand and to deploy. And that it does not require agents. While I do have my past with Puppet and still like it as a tool in certain circumstances, I must admit that I had to smile at the slide about agents.
Todd Barr at AnsibleFest
I have to admit, for many customers and many setups this is in fact true: they do not want agents for various reasons. And Ansible can deliver actual results without any need for a client.

The future of Ansible

Next up was Bill Nottingham talking setting the road for the future of Ansible. A focus is certainly better integration of Windows (no beta tag anymore!), better testing – and Python 3 support! It was acknowledged that there are more and more distributions out there not providing any Python 2 anymore and that they need to be catered.
Future of Ansible by Bill Nottingham
Ansible Tower was also covered, of course, and has very promising improvements coming up as well: the interface will be streamlined, the credentials and rights system will be improved, and there will be (virtual) appliances to get Ansible Tower out of the box in an instant. But the really exciting part is more large-scale, enterprise focused: Ansible Tower will be able to cater federated setups, meaning distributed replication of Ansible Tower commands via proxy Towers.
Federated Ansible Tower
Don’t expect this all in the next weeks, but we might see many of these features already in Ansible Tower 3.0. And it was mentioned that there might be a release in early fall.

Scaling abilities are indeed needed – many data centers these days have more than one location, or are spread over several departments and thus need partially independent setups to manage the infrastructure. At the same time, there are Ansible customers who are using Ansible with 50k nodes and more out there, and they have a demand for fine grained, federated infrastructure setups as well.

Networking with Ansible

While the upcoming Ansible Tower had some exciting news, the talk about networking support by Peter Sprygada really blew everyone away. Right at the moment of presentation Red Hat issued a press release that they bring DevOps to the network via Ansible:

[Red Hat] is bringing DevOps to networking by extending Ansible – its powerful IT automation and DevOps platform – to include native agentless support for automating heterogeneous network infrastructure devices using the same simple human and machine readable automation language that Ansible provides to IT teams.

Peter picked that up and presented a whole lot of technical details. The most important one was that there are now several networking core modules for commands, configuration and templates.
Ansible networking automation support
They cover a huge load of devices:

  • Arista EOS
  • Cisco NXOS
  • Cisco IOS
  • Cisco IOSXR
  • Cumulus Linux
  • Juniper Junos
  • OpenSwitch

While some of these devices were already supported by the raw module or some libraries out there, but fully integrated modules supported by Ansible and the network device manufacturers themselves takes networking automation to another new level. If you are interested, get the latest Ansible networking right away.

Ansible in a visual effects studio

The next talk was by the customer “Industrial Light and Magic”, a visual effects studio using Ansible to handle there massive setup via Ansible. It showed in particular how many obstacles you face in your daily routine running data centers and deploying software all the time – and how to tackle them using Ansible and Ansible’s features. I forgot to take a photo, though…

Ansible & Windows

John Hawkesworth from M*Modal came up to the stage next and delivered a brilliant speech about all the things needed to know when managing Windows with Ansible. Talking about the differences of Ansible 1.9 vs 2.0 briefly, he went over lessons learned like why the backslash should be escaped every time just to be sure (\t …) but also gave his favourite development and modules quite some attention. Turns out the registration module can come in very handy!
Ansible and Windows

Writing modules, 101

Next up James Cammarata introduced how to write modules for Ansible. And impressively, this was live demonstrated by a module he had written the days before to control his Philips Hue lights. They could be controlled via Ansible live on stage.
Ansible Modules 101
Besides the great live demo the major points of the presentation were:

  • It is quite easy to develop modules.
  • Start of simply, get more complex the further you go down the road.
  • Write a module when your Playbook for a single task exceeds ten lines of code.
  • Write in Python/Powershell when you want it to be integrated with Ansible Core.
  • Write in any language you want if you won’t share it anyway.

While I am sure that other module developers might see some of these points different, it gives a rather good idea what to keep in mind when the topic is approached.

Of course, the the code for the Philips Hue Ansible module is available on Github.

Continuous deployment

Continuous integration is a huge topic in DevOps, and thus especially with Ansible. Steve Smith of Atlassian picked up the topic and discussed what needs to be taken into account when Ansible is used to enable continuous integration.
Continous Integration with Ansible
And there were many memorable quotes during the talk which made it simply fun to watch. I particularly like this one:

Release features, not dumps.

It means: do release when you have something worth releasing – not at arbitrary dates. It is a strong statement against release or maintenance windows and does make sense: after all, why should you release when its not worth? And you certainly will not wait if it is important!

Also, since many maintenance windows are implemented because doing maintenance is hard:

Everything which is hard should be done more often, not less.

Combined with the fact that very complex, but successful enterprises do 300 releases an hour it is clear that continuous deployment is possible – but what often is needed is the right culture and probably at some point a great, simple to use tool able to cater the needs of complex infrastructure.

Ansible accelerates deployment

The next talk focused on a vertical which might usually say that they are too regulated and “special” to integrate DevOps: financial. Fabrice Bernhard presented the journey of the Bank Société Générale introducing DevOps principles with the help of Ansible to become more agile, more flexible and to be able to respond quicker to changes. The reason for that was summarized in a very good quote:

It’s not the big that eat the small. It’s the fast that eat the slow.

This is true for all the enterprises out there: software enabled companies have attacked almost any given business out there (Amazon vs Walmart, Uber vs cabs, Airbnb vs hotels and hostels, etc.). And there are enough analysts right now who see the banking market as the next big thing which might be seriously disrupted due to mobile payment, blockchain technology and other IT based developments.
Ansible and the challenges for businesses

But that also shows what the actual change must be about: the new companies do not take over because they have the better technology. They take over because they have a different culture, and approach problems totally different. And thus, to keep up with the development, change your culture. Or, as said on stage:

Automation is about cultural change. Move fast and break things!

DevOps discussion

After these two powerful talks the audience had a chance to catch some breath during the interactive DevOps discussion. It mainly picked up the topics from the previous talks, and it showed that everyone in the room is pretty sure that DevOps as such is more or less a name on the underlying situation that enterprises need to adopt – or they will fail in the long term, no matter how big they are.

Managing your Cisco data center – with Ansible

As already mentioned, Fabrizio Maccioni from Cisco had the second talk about managing networks with Ansible.
Ansible and Cisco
Interestingly enough, he mentioned that the interest to support Ansible was brought to them by customers who were already managing part of their infrastructure with Ansible. A key point is that Ansible does not require an agent. While Cisco does support some configuration management agents on their hardware, it seems that most of the customers would not do that.
Ansible is good becaue agentless

Immutable infrastructure

The last presentation was held by Vik Bhatti from Beamly. Their problem is that sometimes they have to massively scale in seconds. Literally, in seconds. That requires them to have images of machines up and running in no time. They do this with Ansible, having the playbooks right on the images on one hand, and using Ansible to control their image build process on the other. Actually, the image builder is Packer and it uses Ansible to partially build the image.

As a result, down the line they have images ready to deploy and can extend their environment very, very, very quickly. Since they are able to respond that fast, they were able to cut down hardware costs massively.

Final discussions, happy hour

The final panel dealt mainly with questions about Open Source Tower (it will be there eventually, but no fixed date) and similar questions. After that, everyone went to enjoy drinks and a beautiful skyline.
AnsibleFest skyline and happy hour

Conclusion

In conclusion the #AnsibleFest was a great success, in terms of the people I met as well as in terms of the technical discussions. I can’t wait to get my hand on the networking modules. I’d like to thank the people from Ansible making this event possible, and of course my employer Red Hat for making it possible to visit this event.