📄️ How Archiving Works
This topic provides information about how all completed and aborted releases are archived in Digital.ai Release. These releases are removed from the main repository and stored in a separate internal database called the archive database. This process improves performance and allows for the creation of custom hooks to export release information to external databases or reporting tools.
📄️ Create an Export Hook
You can use the export hook feature to configure Release to run a Jython script for every release that is about to be archived.
📄️ Create a JDBC Export Hook
This topic explains how to create a JDBC export hook in Release, allowing you to export data from the release system to a JDBC-compliant database. For more information, see Release export hooks.
📄️ Archive Database
Release stores completed releases in a database that is separate from the repository: the archived database. Besides the completed releases, metadata for reporting is stored in this database.
📄️ Clean up Stale Releases
You can automate the cleanup of old releases by setting up a template with a cleanup script that will be periodically triggered by the criteria that you provide. You can use this procedure in cases where many releases are in a failed state that are older than the specified period of time.
📄️ Purging Archived Releases
You can clean up the archived releases in the archive database by purging the archived releases.
📄️ Set up PostgreSQL Streaming Replication
This topic covers the setup of a production environment in Digital.ai Release using an external clustered database for operational and archived data. It also includes configuring PostgreSQL in a hot-standby setup for high availability with standby servers ready to take over if the primary server fails.