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Case archiving and purging overview

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Use case archiving to archive and purge cases to improve the performance of your cloud-based instance of Pega Platform and reduce storage costs. Permanently delete data from Pega Cloud File Storage to meet your business data retention policy with Pega Platform expunge functionality. Understand how case archiving works so that you can effectively plan and perform case archiving policy within Pega Platform.

How is the term "archival process" used in this documentation?
An archival process is a set of jobs that includes copying, indexing, purging, moving data to PCFS, and permanent deletion using an expunge job.
How is the term "expunge" used in this documentation?
Expunge means permanent deletion of archived data from PCFS. Expunge jobs are used to implement your data retention policy.

Case archiving and data retention

Case hierarchy requirements for case archiving and purging

Case hierarchy requirements can be categorized by the following case structures:
Stand-alone case
A case unit that contains a single case. This type of case contains neither a child nor a parent with a corresponding case type that uses an archival policy. You must set an archival policy on the singular case type to define a stand-alone case policy. Pega Platform can archive or expunge stand-alone cases if the case has been resolved for at least as long as the archival policy.
Case hierarchy
A case unit that contains parent cases, child cases, or both. Pega Platform performs a case archival policy on the entire hierarchy. You must set an archival policy for the top-level case. The case type of the top-level case of the hierarchy determines the archival policy of the entire hierarchy. Pega Platform can archive all cases in the hierarchy if they meet the following conditions:
  • The top-level case has been resolved for at least as long as its archival policy specifies.
  • All sub-level parent and child cases are resolved. Note the following sub-conditions:
    • Sub-level parent and child cases do not need to have an archival policy defined.
    • Sub-level parent and child cases can be resolved any time before the archival job.

If the case structure does not meet these conditions, the archival job cannot process that case structure.

In the following examples, all cases are archived if they meet the specified conditions:
Case hierarchy with sub-level parent and child cases
Case hierarchy with sub-level child cases
Stand-alone case
Top-level case type Archival policy
ServiceRequest (S prefix) 1 year
Job (J prefix) 6 months
TASKS (Task prefix) 3 months

Case hierarchy requirements for expunging

Stand-alone case and case hierarchy
Both stand-alone cases and case hierarchies that Pega Platform previously archived are permanently deleted from Pega Cloud File Storage after you set the permanent deletion policy for that case. Expunge jobs do not process cases that were not archived.

Artifacts that are archived during an archival process

The archival process can also archives certain artifacts within a case. The following table shows the artifacts that Pega Platform can archive:

Artifacts that are archived in Pega Platform

Archived artifacts Non-archived artifacts
  • Child cases
  • Declarative indexes
  • Work history
  • Pulse replies, including link attachments
  • Attachments
    If an attachment is shared between two cases and both cases are not archived, the shared attachment will not be archived.
  • Ad hoc subcases
  • Bookmarked messages
  • Custom associations
  • Documents
  • Followed users
  • Liked messages
  • Links to folders
  • Links to top cases
  • Social reference
  • Tags
  • Workbaskets
  • Worklists

Case archiving process

To archive cases, Pega Platform uses different jobs that you set up through Job Schedulers to copy, index, and purge specific artifacts in stand-alone cases and case hierarchies.

Case archiving pipeline
Pega Platform uses the following jobs during the archive process:

Archive and purge jobs and processes

Job Scheduler Implementation and description
pyPegaArchiver

The pyPegaArchiver Job Scheduler (default short description: Archival_Copier) copies files to Pega Cloud File Storage by using the following steps:

  1. The job uses a crawler to identify, in bulk, cases that are eligible for archiving.
  2. The crawler adds the cases to the archiving pipeline.
  3. The crawler validates the resolution of all subcases.
  4. The job copies the cases and their artifacts to Pega Cloud File Storage.
pyPegaIndexer The pyPegaIndexer Job Scheduler (default short description: Archival_Indexer) indexes the copied files into Elasticsearch. The index keeps the association between an archived case and its archived file in Pega Cloud File Storage.
pyPegaPurger The pyPegaPurger Job Scheduler (default short description: Archival_Purger) deletes cases and their associated data from the primary database. The job also integrates a SQL VACUUM command to process deleted space and reclaim the irrelevant empty database tables.
pyPegaExpunger The pyPegaExpunger (default short description: Archival_Expunger) Job Scheduler permanently deletes archived files from Pega Cloud File Storage and removes the data for the corresponding cases from the Elasticsearch index.
Optional: pyArchival_ReIndexer The pyArchival_ReIndexer (default short description: Archival_ReIndexer) Job Scheduler fixes corrupted Elasticsearch indexes. This job follows a case archival and purge job when trying to fix case archives.
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