Extending Database Recovery Point via Automated Archive Log Incorporation
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Solution Overview
Problem
Current disaster recovery procedures for databases, particularly those using DB2 systems, often recover databases to an older state due to pre-generated recovery jobs that do not account for subsequent archive logs, requiring manual and time-consuming processes to update the database to a more current state, especially during critical events.
Innovation Solution
An automated method is introduced to generate and execute database recovery jobs at a disaster recovery site, incorporating additional archive logs generated after the initial job creation, allowing the database to be recovered to a more current state, thereby extending the recovery point beyond the pre-generated time without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If pre-generated recovery jobs are used to recover the database, then the recovery process is automated and faster, but the database can only be recovered to an older state without including subsequent archive logs
Solution Approach 1:
The recovery job is pre-generated at the local site before a disaster occurs, capturing the database state and recovery instructions at that time. This preliminary action enables fast automated recovery at the disaster site while the system continues to operate and generate new archive logs, resolving the contradiction between quick recovery and current data state.
Solution Approach 2:
The system maintains continuous operation at the local site, generating new archive logs that capture transactions occurring after the pre-generated recovery job. These continuous actions ensure that the database can be recovered to the most current state by incorporating subsequent archive logs into the recovery process.
2Loss of information
If manual steps are taken to add archive log information to the recovered database, then the database can be updated to a more current state, but the process takes long amounts of time and carries significant risks of errors
Solution Approach 1:
The system automatically incorporates subsequent archive logs into the recovery process without requiring manual intervention. The recovery job self-updates by reading and applying new archive logs generated after the pre-generated job, eliminating manual steps and their associated time costs and error risks.
Solution Approach 2:
The recovery system continuously monitors and incorporates new archive logs into the recovery process. This feedback mechanism ensures that the recovered database automatically reflects the most current state by integrating subsequent transactions, eliminating the need for manual updates.
3Reliability
If disaster recovery sites are established at a distance from the original site, then the risk of total area failure is reduced, but the complexity of the disaster recovery system increases
Solution Approach 1:
The disaster recovery system is segmented into modular components: pre-generated recovery jobs, archive log storage, and automated recovery execution. This segmentation allows the system to achieve high reliability through geographic separation while managing complexity through modular, independent components that can be deployed and executed automatically.
Data Source
AI summary
A DBA may pre-generate database recovery jobs on a convenient schedule at a local site, then recover a database at a disaster recovery site. Archive log files for the database that are generated in the interim between recovery job generation and recovery job execution are automatically incorporated into the recovery job when it executes, extending the recovery point closer to the time of the disruption that triggered the need or desire for recovery.