Creating the Production Cutover Runbook
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This content applies to On-premises, Client-managed cloud and Pega Cloud environments
It is important to minimize the impact on your users during the final phase of the migration process. To ensure this, the Pega migration team works with you to create a Production Cutover Runbook. This is separate from the overall Migration Project Plan, and focuses specifically on the final cutover process.
Pega works with your team to conduct one or more dry runs for the production data migration, and uses the dry runs to create the Runbook, as well as to validate connectivity for the data migration.
The Runbook includes a start date and time for each step of the migration process, and includes a calculation of the total time from start to finish for the entire migration, along with an estimate of potential downtime for your end users.
The Production Cutover Runbook ensures alignment between all parties heading into the final migration and Go Live.
The Production Cutover Runbook also includes a "backout plan" detailing any steps necessary to re-enable the source system for production use.
The Production Cutover Runbook includes the following information and steps:
- Listing of all people involved in this migration, their roles, and contact information
- Listing of database schemas and tables that require migration to Pega Cloud
- Proposed date and time of migration
- Amount of time required to move the data
- Exact duration of the production outage
- Notifications to users
- Disabling rule changes
- Disabling creation of new items
- Backing up rules
- Backing up data
- Cutover process for integrations and endpoints
- References to any Cloud Change (CC) tickets required for the cutover
- QA testing criteria to achieve before making the Go Live decision
- Any manual post-migration steps to be performed
- Backout Plan to Re-Enable Source Environment
The project team and key stakeholders (both at your company and at Pega) must review the Production Cutover Runbook and provide final sign-off.
Previous topic Phase 4: Data Migration and Production Go Live Next topic Stage 1: Production Environment: Preparation and Dry Run