Architecting AI-powered resilience framework on AWS

This article presents a five-layer AI-powered resilience framework that automates infrastructure dependency discovery, generates targeted chaos experiments, and integrates resilience testing into CI/CD pipelines using AWS services.

• Discovery layer automatically maps infrastructure dependencies using AWS Resilience Hub and Bedrock agents in 2-4 hours
• Test generation layer creates targeted chaos experiments tailored to specific architecture and business impact
• Experimentation layer executes tests with progressive scope expansion (1% → 5% → 10% → 25%) and automated stop conditions
• Gap analysis layer identifies weaknesses and prioritizes remediation by severity, likelihood, and business impact
• Continuous validation layer integrates lightweight policy checks and resilience regression tests into CI/CD pipelines
• Phased rollout approach: pilot (1-2 weeks), expansion (4-6 weeks), enterprise scale (8-12 weeks)
• Multi-account architecture and tiered resilience policies optimize testing across large organizations

The framework removes expertise barriers to chaos engineering, reduces infrastructure discovery from weeks to hours, and enables proactive resilience validation before production failures occur.