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AWS Launches Generative AI-Enhanced Resilience Hub

AWS Launches Generative AI-Enhanced Resilience Hub

AWS AI Blog
Monday, June 1, 2026
  • •AWS launched an upgraded Resilience Hub featuring generative AI-powered failure mode assessments and standardized policy management.
  • •The new platform supports multi-Region disaster recovery with configurations for 99.95% availability SLOs and specific RTO/RPO targets.
  • •Organizations can now assess resilience at scale using integrated AWS Organizations support and automated cross-account dependency discovery.
  • •AWS launched an upgraded Resilience Hub featuring generative AI-powered failure mode assessments and standardized policy management.
  • •The new platform supports multi-Region disaster recovery with configurations for 99.95% availability SLOs and specific RTO/RPO targets.
  • •Organizations can now assess resilience at scale using integrated AWS Organizations support and automated cross-account dependency discovery.

Amazon Web Services (AWS) announced the next generation of AWS Resilience Hub on May 28, 2026, introducing a series of generative AI-powered tools designed to assist Site Reliability Engineers (SREs) in managing application availability. This update aims to standardize resilience goals, measure progress, and prove compliance across large enterprise application portfolios. The service now integrates with AWS Organizations, allowing for centralized management of resilience postures across multiple accounts through a single delegated administrator.

The updated platform features modular resilience policies, allowing teams to construct requirements based on specific needs such as service level objectives (SLOs), multi-Availability Zone (multi-AZ) configurations, and multi-Region disaster recovery standards. A new application model maps critical business paths to deployable units, while an automated dependency discovery assessment uses DNS query log analysis to identify internal and third-party dependencies. Generative AI-powered failure mode assessments analyze service architectures against defined policies and best practices, identifying potential vulnerabilities and providing actionable remediation recommendations.

Users begin by configuring a resilience policy and establishing an invoker AWS IAM role, which provides the necessary permissions for the hub to read resources. The platform enables users to define specific targets, such as a 99.95% availability SLO, a 15-minute recovery time objective (RTO), and a 5-minute recovery point objective (RPO) for disaster recovery. Once a system is defined, the tool automatically maps the application topology, visualizing data flow and resource connections. During failure mode assessments, the system identifies parent-child relationships and presents findings that detail why a potential failure matters and how to resolve it.

For existing customers, AWS provides migration APIs to transition legacy applications and policies to the new model. The platform is now generally available across all AWS commercial Regions where Resilience Hub is supported. The service operates under a new pricing model that includes two monthly failure mode assessments per service, with additional options for automated dependency tracking. Users can manage these configurations directly through the AWS Resilience Hub console and review findings or mark them as resolved to maintain ongoing compliance and operational health.

Amazon Web Services (AWS) announced the next generation of AWS Resilience Hub on May 28, 2026, introducing a series of generative AI-powered tools designed to assist Site Reliability Engineers (SREs) in managing application availability. This update aims to standardize resilience goals, measure progress, and prove compliance across large enterprise application portfolios. The service now integrates with AWS Organizations, allowing for centralized management of resilience postures across multiple accounts through a single delegated administrator.

The updated platform features modular resilience policies, allowing teams to construct requirements based on specific needs such as service level objectives (SLOs), multi-Availability Zone (multi-AZ) configurations, and multi-Region disaster recovery standards. A new application model maps critical business paths to deployable units, while an automated dependency discovery assessment uses DNS query log analysis to identify internal and third-party dependencies. Generative AI-powered failure mode assessments analyze service architectures against defined policies and best practices, identifying potential vulnerabilities and providing actionable remediation recommendations.

Users begin by configuring a resilience policy and establishing an invoker AWS IAM role, which provides the necessary permissions for the hub to read resources. The platform enables users to define specific targets, such as a 99.95% availability SLO, a 15-minute recovery time objective (RTO), and a 5-minute recovery point objective (RPO) for disaster recovery. Once a system is defined, the tool automatically maps the application topology, visualizing data flow and resource connections. During failure mode assessments, the system identifies parent-child relationships and presents findings that detail why a potential failure matters and how to resolve it.

For existing customers, AWS provides migration APIs to transition legacy applications and policies to the new model. The platform is now generally available across all AWS commercial Regions where Resilience Hub is supported. The service operates under a new pricing model that includes two monthly failure mode assessments per service, with additional options for automated dependency tracking. Users can manage these configurations directly through the AWS Resilience Hub console and review findings or mark them as resolved to maintain ongoing compliance and operational health.

Read original (English)·May 28, 2026
#aws#resilience hub#sre#generative ai#disaster recovery#cloud management