How failure mode assessments work
When you run a failure mode assessment, Next generation Resilience Hub performs the following steps:
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Reads current resource state – Refreshes your service's resource configuration from your AWS account.
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Analyzes the topology – A multi-agent AI system examines how your resources connect and interact.
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Evaluates against policies using the resilience analysis framework – Compares your architecture against your resilience policies. It first performs an assessment to determine if policy components are achievable or not.
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Applies AWS Well-Architected best practices – Checks for common resilience anti-patterns.
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Generates findings – Identifies failure modes with severity, reasoning, and recommendations, and maps results to your resilience policies.
The assessment engine uses specialized AI agents that apply AWS Well-Architected Framework reliability best practices and the AWS Resilience Analysis Framework to your specific architecture. Agents analyze different aspects of resilience:
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Availability – Single points of failure, AZ distribution, and redundancy.
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Disaster recovery – Cross-region capabilities, replication, and failover readiness.
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Dependency resilience – Impact of dependency failures on your service.
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Observability – Monitoring gaps that could delay failure detection.
The failure mode assessment does not consume all available resources. Instead it evaluates a subset of resources known as assessed resources.
Assessed resource: A top-level infrastructure or service component that is directly evaluated during a resilience assessment. A resource is assessed if its configuration has a meaningful impact on availability, recoverability, or fault tolerance of the service. Resources outside of this scope will not have any impact on assessment and will not be surfaced in list-resources.
