TERC Puppet Databucket Library

Initially an intellectual exercise to try to bring myself back up to speed on puppet internals(having last messed with them in 2.7), this module adds the databucket type and associated functions. Note that because all of this is set up to run on the master, ou would have to be very careful with ordering in order to get consistent results.

Types

databucket

A databucket is a resource primitive that functions as a lightweight exportable data container. It can be used to import and export arbitrary data in a controllable manner between classes or nodes.

The get_bucketed function(see below) can be used to collect all buckets that are real or have been realized of a given type, collecting their data into an array.

Functions

create_databuckets

This function is similar to the create_resources function now included in puppet except:

• the resource is known to be a databucket
• the first argument(type) is actually setting a parameter used for filtering on the resource
• the name is automatically assigned and follows the format #{type}::#{md5sum(data)}
• the third argument sets metaparameters(tags, expiration, virtual, export)

Examples:

create_databuckets('bucket', { 'data' => { 'foo' => 'bar' } })

Is functionally equivalent to:

databucket { 'bucket::fb44f36ae92ff8464cb0efa8ee4bab74': type => 'bucket', data => { 'foo' => 'bar' } }

databucket_md5sum

The databucket_md5sum function uses the standard ruby Digest library to perform a Digest::MD5.hexdigest on a string.

Examples:

databucket_md5sum("a=>bbc=>dec=>d=>e")

Should return the value "3096339ef6bdad8974cd042511404353"

• Type: rvalue

flatten_databucket

The flatten_databucket function flattens and orders arbitrary data and returns a string.

Examples:

flatten_databucket({ 'c' => { 'd' => 'e' }, 'bc' => 'de', 'a' => 'b' })
flatten_databucket({ 'a' => 'b', 'c' => {'d' => 'e' }, 'bc' => 'de' })

Should both return the string "a=>bbc=>dec=>d=>e"

• Type: rvalue

get_bucketed

This function queries the compiler for all resources of type databucket. It then retrieves those resource's parameters(this should set off alarm bells about caution) and filters them matches by the passed 'bucket' parameter - ultimately returning an array composed of the data payload that exists within the specified databuckets.

Examples:

class setup_buckets {
  databucket{ 'foo': type => 'bucket', data => "value" }
  databucket{ 'bar': type => 'bucket', data => "another value" }
}
class collect_buckets {
  require setup_buckets 
  $buckets = get_bucketed('bucket')
}

In this example the buckets variable can be expected to contain [ 'value', 'another value' ]

• Type: rvalue