Modern Incident Response Guide for Cloud-Native and AI Systems
A cross-functional operating handbook for SRE, Security, Platform, and ML teams. Built on NIST guidance, public postmortem evidence, and real-world cloud-native patterns.
What You'll Learn
Oxford Economics analysis found that service degradation eats about 9% of profits across the world's largest companies - and the visible outage is only part of the damage. Recovery drag, regulatory exposure, and diverted engineering effort carry the longer tail.
Uptime Institute analysis shows that nearly 40% of organizations experienced a major outage caused by human error in the past 3 years - and within those, 85% were tied to failure to follow procedures or process flaws. The problem is the collision of complexity with speed and partial understanding.
Gartner forecast signals that response workflows are becoming AI-shaped. Prompt injection, model denial of service, tool abuse, retrieval poisoning - these are production problems now. Organizations need governance to match the acceleration.
The guide defines the executive model around Time-to-Understanding, Blast-Radius Control, Decision Auditability, Recovery Confidence, and Learning Velocity. Most companies track MTTR. The guide shows why that is the wrong starting metric.
Seven post-2020 incidents distilled into structural patterns and response design lessons. From Fastly's global propagation event to Okta's support-system compromise to LaunchDarkly's dependency cascade. No vendor spin - just what actually happened and what it teaches.
From assistive summarization through supervised remediation to constrained autonomy - each level defines what AI does, the primary risk it introduces, and the governance required. Includes why 95% of organizations are getting zero return from GenAI pilots (MIT Project NANDA, 2025) and how to avoid that trap.
