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Disaster recovery

As explained in AI for Everyday IT

The process of preparing documented procedures for restoring systems and operations after a disruptive event.

Disaster recovery (DR) restores services after major failures through documented steps that return systems to working order. Continuity of operations planning (COOP) keeps critical business functions running during and after the disruption. section 14.2.2

Generative AI makes DR documentation easier to start and organize. Provide infrastructure details and requirements, then review and adapt the resulting plan to the real environment. The goal is preparedness, not automatic execution during an emergency. section 1.1 section 14.2.2

Prepare the information an AI assistant needs:

  • Inventory servers, roles such as primary or replica, configurations, and hardware or cloud details. section 14.2.2
  • Describe backups, including full, incremental, and binary-log methods, schedules, storage locations, and supporting services. section 14.2.2
  • State Recovery Time Objectives and Recovery Point Objectives for each server or application. section 14.2.2
  • Ask the assistant to identify missing information before drafting comprehensive DR documentation. section 14.2.2

A practical planning prompt

“I’m a MySQL DBA at an organization with about 100 servers. I need DR documentation. What information do you need from me?” A useful response requests the server inventory, backup strategy, and recovery objectives before producing the plan. section 14.2.2

Protect operational data while preparing the documentation. Enterprise services such as Amazon Bedrock, Azure OpenAI Service, and Google Vertex are described as security-focused for company data; with consumer tools, use templates or placeholders and insert real details later. Validate every plan with human expertise. section 14.2.2 section 1.9

How AI for Everyday IT covers it

How deep it goes
Explains DR, distinguishes COOP, supplies planning inputs, and stops short of real-time plan generation or unattended recovery.
Examples
Uses a MySQL environment with about 100 servers and requests for inventory, backup strategy, and recovery objectives.
What it assumes
Assumes knowledge of the organization’s systems, backups, and recovery targets while teaching the documentation process from the beginning.
What you can do after
Build it from scratch by supplying infrastructure and recovery requirements to an AI service, then reviewing its documentation.
How it connects
Connects disaster recovery with continuity of operations, backups, recovery objectives, crisis management, and systems administration.

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Related concepts

This explainer was generated by Manning's knowledge graph from the text of AI for Everyday IT. The section links point to the parts of the book it draws on.