resilience-hub-failure-mode-assessment

Original：🇺🇸 English

Translated

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 assessment, review findings, or understand failure modes, or has a specific finding and asks how to resolve, remediate, or fix it. Does not apply to initial setup (use resilience-hub-getting-started) or FIS experiments.

62installs

Sourceaws/agent-toolkit-for-aws

Added on2026-07-25

NPX Install

npx skill4agent add aws/agent-toolkit-for-aws resilience-hub-failure-mode-assessment

SKILL.md Content

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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.

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 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 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 and the AWS Well-Architected Security Pillar for securing assessment outputs and IAM configurations.