Hiera looks up data with a hierarchy, which is an ordered list of data sources.
Hierarchies are configured in a hiera.yaml config file. A hierarchy usually looks something like this:
---
version: 5
defaults: # Used for any hierarchy level that omits these keys.
datadir: data # This path is relative to hiera.yaml's directory.
data_hash: yaml_data # Use the built-in YAML backend.
hierarchy:
- name: "Per-node data" # Human-readable name.
path: "nodes/%{trusted.certname}.yaml" # File path, relative to datadir.
# ^^^ IMPORTANT: include the file extension!
- name: "Per-datacenter business group data" # Uses custom facts.
path: "location/%{facts.whereami}/%{facts.group}.yaml"
- name: "Global business group data"
path: "groups/%{facts.group}.yaml"
- name: "Per-datacenter secret data (encrypted)"
lookup_key: eyaml_lookup_key # Uses non-default backend.
path: "secrets/%{facts.whereami}.eyaml"
options:
pkcs7_private_key: /etc/puppetlabs/puppet/eyaml/private_key.pkcs7.pem
pkcs7_public_key: /etc/puppetlabs/puppet/eyaml/public_key.pkcs7.pem
- name: "Per-OS defaults"
path: "os/%{facts.os.family}.yaml"
- name: "Common data"
path: "common.yaml"
Each level of the hierarchy tells Hiera how to access some kind of data source. In this example, every level configures the path to a YAML file on disk.
Most hierarchies interpolate variables
Notice that most levels of this hierarchy interpolate variables into their configuration:
path: "os/%{facts.os.family}.yaml"
- The percent-and-braces
%{variable}syntax is a Hiera interpolation token. It’s similar to the Puppet language’s${expression}interpolation tokens. facts.os.familyuses Hiera’s special key.subkey notation for accessing elements of hashes and arrays. It’s equivalent to$facts['os']['family']in the Puppet language.- This example, like most real-life hierarchies, uses facts and trusted data.
- You can only interpolate values into certain parts of the config file. For more info, see the hiera.yaml format reference.
This is the core of Hiera’s power: with node-specific variables, each node gets its own customized version of the hierarchy.
Consider two example machines that both belong to the operations team: an Ubuntu server named Thrush (in the Belfast datacenter), and a Red Hat server named Crane (in Portland). These machines use the same hierarchy, but it resolves to a different list of data sources for each.
| Thrush’s hierarchy | Crane’s hierarchy |
|---|---|
|
|
Note that they both use data/groups/ops.yaml (since they belong to the same group) and they both use data/common.yaml (since that level of the hierarchy doesn’t use any variables). But other than that, they use completely different data sources.
It’s normal for some of these files to not exist, and Hiera handles that just fine. Most Hiera users have several optional levels in their hierarchy, which are important for some machines and irrelevant for others. (For example, maybe the ops team uses a lot of location-specific data, but the release engineering team is datacenter-agnostic.)
Hiera searches the hierarchy in order
Once Hiera replaces the variables to make a list of concrete data sources, it checks those data sources in the order they’re written. If a data source doesn’t exist, or doesn’t specify a value for the current key, Hiera skips it and moves on to the next source.
This means earlier data sources have priority over later ones. In the example above, the node-specific data has the highest priority, and can override data from any other level. Business group data is separated into local and global sources, with the local one overriding the global one. And the common data used by all nodes always goes last.
That’s how Hiera’s “defaults, with overrides” approach to data works: you specify shared data at lower levels of the hierarchy, and override it at higher levels for groups of nodes with special needs.
Optionally, Hiera can merge data
Hiera has two main modes of operation:
- Return the first value found.
- Find multiple values and merge them together. (There are a few merge behaviors to choose from; for more details, see Merging data from multiple sources.)
In a first-found lookup, higher-priority data sources completely override values from the data sources below them. In a merging lookup, every level of the hierarchy can contribute to the final value, although higher-priority sources win in the case of a conflict.
Three layer hierarchies → one combined hierarchy
Hiera uses three layers of data. (For more info, see The three config layers.)
Each layer can configure its own independent hierarchy. When it’s time to do a lookup, Hiera combines them into a single super-hierarchy. The order for this is global → environment → module.
Assume the example above is an environment hierarchy (in the production environment). If we also had the following global hierarchy:
---
version: 5
hierarchy:
- name: "Data exported from our old self-service config tool"
path: "selfserve/%{trusted.certname}.json"
data_hash: json_data
datadir: data
…and the NTP module had the following hierarchy for default data:
---
version: 5
hierarchy:
- name: "OS values"
path: "os/%{facts.os.name}.yaml"
- name: "Common values"
path: "common.yaml"
defaults:
data_hash: yaml_data
datadir: data
…then in a lookup for the the ntp::servers key, thrush.example.com would use the following combined hierarchy:
<CONFDIR>/data/selfserve/thrush.example.com.json<CODEDIR>/environments/production/data/nodes/thrush.example.com.yaml<CODEDIR>/environments/production/data/location/belfast/ops.yaml<CODEDIR>/environments/production/data/groups/ops.yaml<CODEDIR>/environments/production/data/os/Debian.yaml<CODEDIR>/environments/production/data/common.yaml<CODEDIR>/environments/production/modules/ntp/data/os/Ubuntu.yaml<CODEDIR>/environments/production/modules/ntp/data/common.yaml
(See the codedir and confdir documentation for the locations of these directories on different platforms.)
The combined hierarchy works the same way as a layer hierarchy: Hiera skips empty data sources, and either returns the first found value or merges all found values.
What makes a good hierarchy?
That’s very subjective. But here are some things to think about as you design your data:
- A shorter hierarchy is easier to reason about, and makes your data files easier to work with.
- Use the roles and profiles method to manage less data in Hiera. Sorting thousands of fiddly class parameters is a nightmare; sorting hundreds of conscious decisions is quite a bit easier.
- A hierarchy is a way of acknowledging the differences in your infrastructure. Think hard about the differences that are most important to you! If the built-in facts don’t give you an easy way to represent those differences, consider making custom facts — for example, a
datacenterfact that distils institutional knowledge about your network layout into a simple geographical signal. - Don’t get ahead of yourself! In the days of Hiera 3, when changing a hierarchy was incredibly expensive and “dead” layers hung around forever, people made really large hierarchies in an effort to guess their future needs. But now that you can change hierarchies on an environment-by-environment basis, you can be a lot more agile about it. Start small, and iterate.