To ensure our database recovery plan is robust, we focus on a few key steps. First, we identify and prioritize critical data, ensuring we know what needs to be recovered first in case of a disaster. We use redundancy by setting up real-time backups and off-site storage to minimize the risk of data loss and reduce downtime. Regular testing is essential, so we conduct recovery drills at least quarterly to ensure our team is well-prepared and our processes are effective. Additionally, we continuously review and update the plan to address any new risks or changes in the system.

When designing a recovery solution for a database infrastructure facing potential disaster, key factors to consider include: - ensuring regular, reliable backups are in place and accessible; - clearly defining and gathering recovery requirements based on business needs; - proactively identifying and informing all stakeholders who may be impacted by the disruption; - evaluating possible failure scenarios to develop robust contingency plans that minimize downtime and data loss.

When designing a disaster recovery solution, consider key factors: RPO (Recovery Point Objective) to determine acceptable data loss, and RTO (Recovery Time Objective) to minimize downtime. Assess the criticality of data and prioritize mission-critical databases. Evaluate risks like cyberattacks or hardware failures and plan accordingly. Account for database size, growth, and platform-specific requirements. Balance costs against potential losses and ensure compliance with regulations. Implement scalable, geo-redundant solutions for distributed systems. Regularly test recovery plans and backups to ensure readiness. A well-thought-out strategy safeguards business continuity and minimizes disruptions.

The first thing I would look into is: moving critical data into a separate database and immediately preform a backup. Making sure critical data isn't compromised would be key. Next, I would identify secondary data (nice to have) and implement moving that to the new database. While doing this, I would be discussing with my legal department what our data retention policy is (how far back are we required by law to keep), this data would go to the primary new location and the rest would go to a data lake- unless it's been determined that we can delete this data. Lastly, the migration of all other data would be audited internally for necessity and historical criticality before any major efforts are made to salvage.

If there was an attack surface then the network might be at risk, the question is not clear on what is compromised and how bad it is. An CyberSecurity Architect comes in at the beginning and not at the end simply because it is not a bolt on system. SYSlogs, SSO, IAM, RBAC, EDR, PAM, MFA, Firewalls, routers, etc... everything needs to be analyzed documented, signed off on and implemented then audited over and over again. As for recovery plans and protection against ransomware a cloud-system always comes in handy which also require a proper setup and documentation. Automation with AI is the next big thing and I can certainly say that most of the redundancy will go away. So far we handled everything with python & SQL