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A Puppet Module for Backing Up / Maintaining / Tuning Your Puppet Enterprise Databases


190 latest version

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Version information

  • 2.3.0 (latest)
  • 2.2.0
  • 2.1.1
  • 2.1.0
  • 2.0.0
  • 1.2.0
  • 1.1.0
  • 1.0.1
  • 1.0.0
released Jul 21st 2022
This version is compatible with:
  • Puppet Enterprise 2021.6.x, 2021.5.x, 2021.4.x, 2021.3.x, 2021.2.x, 2021.1.x, 2021.0.x, 2019.8.x
  • Puppet >= 6.16.0 < 8.0.0
  • , , , , ,
  • reset_pgrepack_schema

Start using this module

  • r10k or Code Manager
  • Bolt
  • Manual installation
  • Direct download

Add this module to your Puppetfile:

mod 'puppetlabs-pe_databases', '2.3.0'
Learn more about managing modules with a Puppetfile

Add this module to your Bolt project:

bolt module add puppetlabs-pe_databases
Learn more about using this module with an existing project

Manually install this module globally with Puppet module tool:

puppet module install puppetlabs-pe_databases --version 2.3.0

Direct download is not typically how you would use a Puppet module to manage your infrastructure, but you may want to download the module in order to inspect the code.



puppetlabs/pe_databases — version 2.3.0 Jul 21st 2022

Table of Contents


This module provides tuning, and maintenance for PE PostgreSQL.

What does this module provide?

This module provides the following functionaility

  1. Customized settings for PE PostgreSQL
  2. Maintenance to keep the pe-puppetdb database lean and fast


In order to use this module, classify the node running PE PostgreSQL with the pe_databases class. The Primary Server and Replica run PE PostgreSQL in most instances, but there may be one or more servers with this role in an XL deployment

To classify via the PE Console, create a new node group called "PE Database Maintenance". Then pin the node(s) running pe-postgresql to that node group. It is not recommended to classify using a pre-existing node group in the PE Console.

Items you may want to configure

WARNING: The backup functionality in this module has been removed. Please refer to the PE Backup and Restore documentation for details on how to backup. You should ensure the parameter pe_databases::manage_database_backups and any parameters from the pe_databases::backup class are removed from classification or hiera. You should also clean up associated crontab entries.

Disable Maintenance

The maintenance systemd timers will perform a pg_repack on various pe-puppetdb tables to keep them lean and fast. pg_repack is a non blocking operation and should have no impact on the operations of Puppet Enterprise, however, if for some reason you experience issues you can disable the maintenance systemd timers. You can do so by setting pe_databases::disable_maintenance: true in your hieradata.

General PostgreSQL Recommendations


Under normal operating conditions, there is very little tuning needed for PE PostgreSQL.

If you are using a Monolithic installation of Puppet Enterprise then the default settings are well-tuned. If you are using a dedicated node for PE PostgreSQL, then some of the settings can be tuned upwards, but likely with little difference in performance.

This module attempts to provide default settings that accommodate both a Monolithic install and a dedicated PE PostgreSQL instance. Those defaults change based on the $all_in_one_pe parameter.


This module provides systemd timers to pg_repack tables in the pe-puppetdb database:

  • facts tables are pg_repack'd Tuesdays and Saturdays at 4:30AM
  • catalogs tables are pg_repack'd Sundays and Thursdays at 4:30AM
  • reports table is pg_repack'd on the 10th of the month at 05:30AM on systems with PE 2019.7.0 or less
  • resource_events table is pg_repack'd on the 15th of the month at 05:30AM on systems with PE 2019.3.0 or less
  • other tables are pg_repack'd on the 20th of the month at 5:30AM

Note: You may be able to improve the performance (reduce time to completion) of maintenance tasks by increasing the maintenance_work_mem setting.

Please note that when using pg_repack as part of the pe_databases module, unclean exits can leave behind the schema when otherwise it should have been cleaned up. This can result in the messages similar to the following:

INFO: repacking table "public.fact_paths"
WARNING: the table "public.fact_paths" already has a trigger called "repack_trigger"
DETAIL: The trigger was probably installed during a previous attempt to run pg_repack on the table which was interrupted and for some reason failed to clean up the temporary objects. Please drop the trigger or drop and recreate the pg_repack extension altogether to remove all the temporary objects left over.

The module now contains a task reset_pgrepack_schema to mitigate this issue. This needs to be run against your Primary or PE-postgreSQL server to resolve this and it will drop and recreate the extension, removing the temporary objects.

PostgreSQL Settings


You can improve the speed of vacuuming, reindexing, and backups by increasing this setting. Consider a table that is 1GB. If maintenance_work_mem is 256MB, then to perform operations on the table a quarter of it will be read into memory, operated on, then written out to disk, and then that will repeat three more times. If maintenance_work_mem is 1GB then the entire table can be read into memory, operated on, then written out to disk.

Note: that each autovacuum worker can use up to this much memory, if you do not set autovacuum_work_mem as well.


Puppet Enterprise ships with a default work_mem of 4MB. For most installations, this is all that is needed, however, at a larger scale you may need to increase to 8MB or 16MB. One way to know if you need more work_mem is to change the log_temp_files setting to 0 which will log all temporary files created by PostgreSQL. When you see a lot of temporary files being logged over the work_mem threshold then it’s time to consider increasing work_mem, however, you should first run a REINDEX and VACUUM ANALYZE to see if that reduces the number of temporary files being logged.

Another way to determine the need for an increase in work_mem is to get the query plan from a slow running query (accomplished by adding EXPLAIN ANALYZE to the beginning of the query). Query plans that have something like Sort Method: external merge Disk in them indicate a possible need for for more work_mem.

This is discussed on the Tuning Your PostgreSQL Server Wiki


This setting is essentially maintenance_work_mem but for autovacuum processes only. Usually you will set maintenance_work_mem higher and this lower, since autovacuum_work_mem is used by autovacuum_max_workers number of autovacuum processes.


The larger your database the more autovacuum workers you may need. The default of 3 is reasonable for most small or medium installations of Puppet Enterprise. When you’re tracking the size of your database tables and indexes and you notice some of them seem to keep getting larger then you might need more autovacuum workers.

If you’ve installed PE PostgreSQL on its own node, then we recommend CPU / 2 as a default for this setting (with a maximum of 8). For a Monolithic installation, increasing this setting means you likely need to compensate by reducing other settings that may cause your CPU to be over-subscribed during a peak. Those settings would be PuppetDB Command Processing Threads and Puppet Server JRuby Instances.

checkpoint_segments and checkpoint_completion_target

We suggest a middle ground of 128 for checkpoint_segments and .9 for checkpoint_completion_target. As mentioned in the PostgreSQL Wiki, the larger value you use for checkpoint_segments affords you better performance but you sacrifice in potential recovery time.

If you see messages like “LOG: checkpoints are occurring too frequently (xx seconds apart)” then you definitely want to increase your checkpoint_segments.

How to Report an issue or contribute to the module

If you are a PE user and need support using this module or are encountering issues, our Support team would be happy to help you resolve your issue and help reproduce any bugs. Just raise a ticket on the support portal. If you have a reproducible bug or are a community user you can raise it directly on the Github issues page of the module puppetlabs/puppetlabs-pe_databases. We also welcome PR contributions to improve the module. Please see further details about contributing here