How Do I Use Salt States?¶

Simplicity, Simplicity, Simplicity

Many of the most powerful and useful engineering solutions are founded on simple principles. Salt States strive to do just that: K.I.S.S. (Keep It Stupidly Simple)

The core of the Salt State system is the SLS, or Structured Layered State. The SLS is a representation of the state in which a system should be in, and is set up to contain this data in a simple format. This is often called configuration management.

Note

This is just the beginning of using states, make sure to read up on pillar Pillar next.

It is All Just Data¶

Before delving into the particulars, it will help to understand that the SLS file is just a data structure under the hood. While understanding that the SLS is just a data structure isn't critical for understanding and making use of Salt States, it should help bolster knowledge of where the real power is.

SLS files are therefore, in reality, just dictionaries, lists, strings, and numbers. By using this approach Salt can be much more flexible. As one writes more state files, it becomes clearer exactly what is being written. The result is a system that is easy to understand, yet grows with the needs of the admin or developer.

The Top File¶

The example SLS files in the below sections can be assigned to hosts using a file called top.sls. This file is described in-depth here.

Default Data - YAML¶

By default Salt represents the SLS data in what is one of the simplest serialization formats available - YAML.

A typical SLS file will often look like this in YAML:

Note

These demos use some generic service and package names, different distributions often use different names for packages and services. For instance apache should be replaced with httpd on a Red Hat system. Salt uses the name of the init script, systemd name, upstart name etc. based on what the underlying service management for the platform. To get a list of the available service names on a platform execute the service.get_all salt function.

Information on how to make states work with multiple distributions is later in the tutorial.

apache:
  pkg.installed: []
  service.running:
    - require:
      - pkg: apache

This SLS data will ensure that the package named apache is installed, and that the apache service is running. The components can be explained in a simple way.

The first line is the ID for a set of data, and it is called the ID Declaration. This ID sets the name of the thing that needs to be manipulated.

The second and third lines contain the state module function to be run, in the format <state_module>.<function>. The pkg.installed state module function ensures that a software package is installed via the system's native package manager. The service.running state module function ensures that a given system daemon is running.

Finally, on line four, is the word require. This is called a Requisite Statement, and it makes sure that the Apache service is only started after a successful installation of the apache package.

Adding Configs and Users¶

When setting up a service like an Apache web server, many more components may need to be added. The Apache configuration file will most likely be managed, and a user and group may need to be set up.

apache:
  pkg.installed: []
  service.running:
    - watch:
      - pkg: apache
      - file: /etc/httpd/conf/httpd.conf
      - user: apache
  user.present:
    - uid: 87
    - gid: 87
    - home: /var/www/html
    - shell: /bin/nologin
    - require:
      - group: apache
  group.present:
    - gid: 87
    - require:
      - pkg: apache

/etc/httpd/conf/httpd.conf:
  file.managed:
    - source: salt://apache/httpd.conf
    - user: root
    - group: root
    - mode: 644

This SLS data greatly extends the first example, and includes a config file, a user, a group and new requisite statement: watch.

Adding more states is easy, since the new user and group states are under the Apache ID, the user and group will be the Apache user and group. The require statements will make sure that the user will only be made after the group, and that the group will be made only after the Apache package is installed.

Next, the require statement under service was changed to watch, and is now watching 3 states instead of just one. The watch statement does the same thing as require, making sure that the other states run before running the state with a watch, but it adds an extra component. The watch statement will run the state's watcher function for any changes to the watched states. So if the package was updated, the config file changed, or the user uid modified, then the service state's watcher will be run. The service state's watcher just restarts the service, so in this case, a change in the config file will also trigger a restart of the respective service.

Moving Beyond a Single SLS¶

When setting up Salt States in a scalable manner, more than one SLS will need to be used. The above examples were in a single SLS file, but two or more SLS files can be combined to build out a State Tree. The above example also references a file with a strange source - salt://apache/httpd.conf. That file will need to be available as well.

The SLS files are laid out in a directory structure on the Salt master; an SLS is just a file and files to download are just files.

The Apache example would be laid out in the root of the Salt file server like this:

apache/init.sls
apache/httpd.conf

So the httpd.conf is just a file in the apache directory, and is referenced directly.

Do not use dots in SLS file names or their directories

The initial implementation of top.sls and Include declaration followed the python import model where a slash is represented as a period. This means that a SLS file with a period in the name ( besides the suffix period) can not be referenced. For example, webserver_1.0.sls is not referenceable because webserver_1.0 would refer to the directory/file webserver_1/0.sls

The same applies for any subdirectories, this is especially 'tricky' when git repos are created. Another command that typically can't render its output is `state.show_sls` of a file in a path that contains a dot.

But when using more than one single SLS file, more components can be added to the toolkit. Consider this SSH example:

ssh/init.sls:

openssh-client:
  pkg.installed

/etc/ssh/ssh_config:
  file.managed:
    - user: root
    - group: root
    - mode: 644
    - source: salt://ssh/ssh_config
    - require:
      - pkg: openssh-client

ssh/server.sls:

include:
  - ssh

openssh-server:
  pkg.installed

sshd:
  service.running:
    - require:
      - pkg: openssh-client
      - pkg: openssh-server
      - file: /etc/ssh/banner
      - file: /etc/ssh/sshd_config

/etc/ssh/sshd_config:
  file.managed:
    - user: root
    - group: root
    - mode: 644
    - source: salt://ssh/sshd_config
    - require:
      - pkg: openssh-server

/etc/ssh/banner:
  file:
    - managed
    - user: root
    - group: root
    - mode: 644
    - source: salt://ssh/banner
    - require:
      - pkg: openssh-server

Note

Notice that we use two similar ways of denoting that a file is managed by Salt. In the /etc/ssh/sshd_config state section above, we use the file.managed state declaration whereas with the /etc/ssh/banner state section, we use the file state declaration and add a managed attribute to that state declaration. Both ways produce an identical result; the first way -- using file.managed -- is merely a shortcut.

Now our State Tree looks like this:

apache/init.sls
apache/httpd.conf
ssh/init.sls
ssh/server.sls
ssh/banner
ssh/ssh_config
ssh/sshd_config

This example now introduces the include statement. The include statement includes another SLS file so that components found in it can be required, watched or as will soon be demonstrated - extended.

The include statement allows for states to be cross linked. When an SLS has an include statement it is literally extended to include the contents of the included SLS files.

Note that some of the SLS files are called init.sls, while others are not. More info on what this means can be found in the States Tutorial.

Extending Included SLS Data¶

Sometimes SLS data needs to be extended. Perhaps the apache service needs to watch additional resources, or under certain circumstances a different file needs to be placed.

In these examples, the first will add a custom banner to ssh and the second will add more watchers to apache to include mod_python.

ssh/custom-server.sls:

include:
  - ssh.server

extend:
  /etc/ssh/banner:
    file:
      - source: salt://ssh/custom-banner

python/mod_python.sls:

include:
  - apache

extend:
  apache:
    service:
      - watch:
        - pkg: mod_python

mod_python:
  pkg.installed

The custom-server.sls file uses the extend statement to overwrite where the banner is being downloaded from, and therefore changing what file is being used to configure the banner.

In the new mod_python SLS the mod_python package is added, but more importantly the apache service was extended to also watch the mod_python package.

Using extend with require or watch

The extend statement works differently for require or watch. It appends to, rather than replacing the requisite component.

Understanding the Render System¶

Since SLS data is simply that (data), it does not need to be represented with YAML. Salt defaults to YAML because it is very straightforward and easy to learn and use. But the SLS files can be rendered from almost any imaginable medium, so long as a renderer module is provided.

The default rendering system is the jinja|yaml renderer. The jinja|yaml renderer will first pass the template through the Jinja2 templating system, and then through the YAML parser. The benefit here is that full programming constructs are available when creating SLS files.

Other renderers available are yaml_mako and yaml_wempy which each use the Mako or Wempy templating system respectively rather than the jinja templating system, and more notably, the pure Python or py, pydsl & pyobjects renderers. The py renderer allows for SLS files to be written in pure Python, allowing for the utmost level of flexibility and power when preparing SLS data; while the pydsl renderer provides a flexible, domain-specific language for authoring SLS data in Python; and the pyobjects renderer gives you a "Pythonic" interface to building state data.

Note

The templating engines described above aren't just available in SLS files. They can also be used in file.managed states, making file management much more dynamic and flexible. Some examples for using templates in managed files can be found in the documentation for the file state, as well as the MooseFS example below.

Getting to Know the Default - jinja|yaml¶

The default renderer - jinja|yaml, allows for use of the jinja templating system. A guide to the Jinja templating system can be found here: https://jinja.palletsprojects.com/en/2.11.x/

When working with renderers a few very useful bits of data are passed in. In the case of templating engine based renderers, three critical components are available, salt, grains, and pillar. The salt object allows for any Salt function to be called from within the template, and grains allows for the Grains to be accessed from within the template. A few examples:

apache/init.sls:

apache:
  pkg.installed:
    {% if grains['os'] == 'RedHat'%}
    - name: httpd
    {% endif %}
  service.running:
    {% if grains['os'] == 'RedHat'%}
    - name: httpd
    {% endif %}
    - watch:
      - pkg: apache
      - file: /etc/httpd/conf/httpd.conf
      - user: apache
  user.present:
    - uid: 87
    - gid: 87
    - home: /var/www/html
    - shell: /bin/nologin
    - require:
      - group: apache
  group.present:
    - gid: 87
    - require:
      - pkg: apache

/etc/httpd/conf/httpd.conf:
  file.managed:
    - source: salt://apache/httpd.conf
    - user: root
    - group: root
    - mode: 644

This example is simple. If the os grain states that the operating system is Red Hat, then the name of the Apache package and service needs to be httpd.

A more aggressive way to use Jinja can be found here, in a module to set up a MooseFS distributed filesystem chunkserver:

moosefs/chunk.sls:

include:
  - moosefs

{% for mnt in salt['cmd.run']('ls /dev/data/moose*').split() %}
/mnt/moose{{ mnt[-1] }}:
  mount.mounted:
    - device: {{ mnt }}
    - fstype: xfs
    - mkmnt: True
  file.directory:
    - user: mfs
    - group: mfs
    - require:
      - user: mfs
      - group: mfs
{% endfor %}

/etc/mfshdd.cfg:
  file.managed:
    - source: salt://moosefs/mfshdd.cfg
    - user: root
    - group: root
    - mode: 644
    - template: jinja
    - require:
      - pkg: mfs-chunkserver

/etc/mfschunkserver.cfg:
  file.managed:
    - source: salt://moosefs/mfschunkserver.cfg
    - user: root
    - group: root
    - mode: 644
    - template: jinja
    - require:
      - pkg: mfs-chunkserver

mfs-chunkserver:
  pkg.installed: []
mfschunkserver:
  service.running:
    - require:
{% for mnt in salt['cmd.run']('ls /dev/data/moose*') %}
      - mount: /mnt/moose{{ mnt[-1] }}
      - file: /mnt/moose{{ mnt[-1] }}
{% endfor %}
      - file: /etc/mfschunkserver.cfg
      - file: /etc/mfshdd.cfg
      - file: /var/lib/mfs

This example shows much more of the available power of Jinja. Multiple for loops are used to dynamically detect available hard drives and set them up to be mounted, and the salt object is used multiple times to call shell commands to gather data.

Introducing the Python, PyDSL, and the Pyobjects Renderers¶

Sometimes the chosen default renderer might not have enough logical power to accomplish the needed task. When this happens, the Python renderer can be used. Normally a YAML renderer should be used for the majority of SLS files, but an SLS file set to use another renderer can be easily added to the tree.

This example shows a very basic Python SLS file:

python/django.sls:

#!py


def run():
    """
    Install the django package
    """
    return {"include": ["python"], "django": {"pkg": ["installed"]}}

This is a very simple example; the first line has an SLS shebang that tells Salt to not use the default renderer, but to use the py renderer. Then the run function is defined, the return value from the run function must be a Salt friendly data structure, or better known as a Salt HighState data structure.

Alternatively, using the pydsl renderer, the above example can be written more succinctly as:

#!pydsl

include("python", delayed=True)
state("django").pkg.installed()

The pyobjects renderer provides an "Pythonic" object based approach for building the state data. The above example could be written as:

#!pyobjects

include("python")
Pkg.installed("django")

These Python examples would look like this if they were written in YAML:

include:
  - python

django:
  pkg.installed

This example clearly illustrates that; one, using the YAML renderer by default is a wise decision and two, unbridled power can be obtained where needed by using a pure Python SLS.

Running and Debugging Salt States¶

Once the rules in an SLS are ready, they should be tested to ensure they work properly. To invoke these rules, simply execute salt '*' state.apply on the command line. If you get back only hostnames with a : after, but no return, chances are there is a problem with one or more of the sls files. On the minion, use the salt-call command to examine the output for errors:

salt-call state.apply -l debug

This should help troubleshoot the issue. The minion can also be started in the foreground in debug mode by running salt-minion -l debug.

Next Reading¶

With an understanding of states, the next recommendation is to become familiar with Salt's pillar interface:

Pillar Walkthrough

Generated on October 23, 2024 at 09:02:06 UTC.

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