Name: resilience-hub-failure-mode-assessment
Author: aws

Runs and interprets AWS Resilience Hub v2 failure mode assessments. Covers starting assessments, understanding findings (severity, categories, recommendations), triaging by achievability, working with AI-generated service functions, and resolving findings. Applies when the user wants to run an asses

Failure Mode Assessment Overview Domain expertise for running Resilience Hub v2 failure mode assessments, interpreting findings, triaging by severity and achievability, and driving remediation. The AWS MCP server is recommended for executing this skill's AWS API calls, but it is not required — all operations also work with the AWS CLI directly. Guardrail — where this skill's own files live (MCP vs local install) Before reading a reference file, determine how this skill was loaded: Loaded via the AWS MCP retrieve skill tool: the skill's reference files are not on the local filesystem. Fetch each one through retrieve skill with the file parameter (e.g. file="references/assessment workflow.md" ) — do NOT file read these paths locally or search the filesystem for them. Installed locally (e.g. .kiro/skills/resilience hub failure mode assessment/ or ~/.claude/skills/resilience hub failure mode assessment/ ): read reference files from the local skill directory using the relative paths shown here. This applies only to the skill's own reference files; always read and write user or session data in the working directory, never through retrieve skill . Run and interpret assessments To run assessments and triage findings, follow the procedure exactly. See [references/assessment workflow.md](references/assessment workflow.md). Troubleshooting Assessment fails with INVALID PERMISSIONS The service's permission model (invokerRoleName / crossAccountRoles) doesn't have access to the resources. Verify the invoker role (and any cross account roles) can describe resources in all configured regions. Too many findings — where to start? Prioritize by finding severity, highest first (HIGH, then MEDIUM, then LOW). For HIGH severity findings, check the service's achievability for the relevant policy component (from get service / list failure mode assessments ): NOT ACHIEVABLE means the architecture must change before testing; ACHIEVABLE means validate the fix with an FIS experiment. MEDIUM findings: plan remediation this sprint; LOW findings: track but don't block (see the priority matrix in [references/assessment workflow.md](references/assessment workflow.md) Step 5). AI generated service functions are wrong Update them: aws resiliencehubv2 update service function to rename or change criticality (there is no service function "type" parameter). Reassign resources by calling create service function resources with the desired resource set (see [references/assessment workflow.md](references/assessment workflow.md) for the service function operations). Security Considerations Least privilege: the invoker role should be scoped to read only discovery of only the resource types in the service's input sources; avoid granting access beyond what assessment needs. Encryption & access control: recommend that S3 buckets used for report output have server side encryption (SSE S3 or SSE KMS) and block public access — assessment reports can contain sensitive architectural detail. If a bucket policy grants the Resilience Hub service principal write access, scope it with aws:SourceArn / aws:SourceAccount condition keys to prevent confused deputy writes. Further reading: see [Security in AWS Resilience Hub](https://docs.aws.amazon.com/resilience hub/latest/userguide/security.html) and the [AWS Well Architected Security Pillar](https://docs.aws.amazon.com/wellarchitected/latest/security pillar/welcome.html) for securing assessment outputs and IAM configurations.