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AWS Resilience Lifecycle

AWSOfficialPublished by AWS

  • Skill
  • Workflow
  • Cloud and DevOps
  • Apache-2.0
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From the author

Guides the end-to-end AWS resilience lifecycle integrating Resilience Hub v2, Fault Injection Service, and Application Recovery Controller. Covers the Define → Test → Operate workflow: from policy creation through failure mode assessment, to FIS experiment validation, to ARC operational controls. Applicable when the user wants a complete resilience strategy, needs to connect findings to experiments to controls, or is planning a resilience program. Also applicable for the meta question of whether marking NGRH findings as resolved is enough, whether they are "done" after resolving findings, or how to validate findings before resolving them. Not applicable for resolving or remediating a specific individual finding (see resilience-hub-failure-mode-assessment), or when a single service is explicitly named (e.g. "what FIS experiment should I run").
— the description by AWS

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured, end-to-end approach to building and maintaining system resilience on AWS. It integrates three core services—Resilience Hub v2 (NGRH), Fault Injection Service (FIS), and Application Recovery Controller (ARC)—to move teams through a Define, Test, and Operate workflow. The skill emphasizes moving beyond paper compliance by requiring that all resilience findings are validated through controlled fault injection experiments before being marked as resolved.

What it does

  • Defines resilience policies based on business criticality and service tiers.
  • Guides the assessment of failure modes using Resilience Hub v2.
  • Provides patterns for validating remediation through FIS experiments.
  • Integrates operational controls using Application Recovery Controller.
  • Enforces strict API usage to prevent common command hallucinations.
  • Promotes progressive experiment complexity from single-fault to cascading scenarios.

When to use it

  • When establishing a formal resilience program for AWS-based applications.
  • When you need to connect resilience findings to actionable fault injection tests.
  • When planning to implement operational failover controls using ARC.
  • When you need to validate that your architecture meets RTO/RPO targets under real failure conditions.

Advantages

  • Prevents paper compliance by mandating validation of fixes.
  • Provides a clear, repeatable workflow for complex resilience tasks.
  • Includes a hallucination-rejection guide for AWS CLI commands.
  • Promotes a tiered, risk-based approach to resilience investment.

Usage examples

“How do I start the resilience lifecycle for my new payment service?”
The agent will guide you through creating a resilience policy, registering your service via CloudFormation or Terraform, and running an initial failure mode assessment.
“I have a finding in Resilience Hub; can I just mark it as resolved?”
The agent will explain that marking findings resolved without validation is paper compliance and will guide you to create an FIS experiment to prove the fix works.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/aws/aws-resilience-lifecycle/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip aws-resilience-lifecycle.zip -d .agents/skills

Documentation by AWS

AWS Resilience Lifecycle

Overview

Domain expertise for the integrated resilience lifecycle across three AWS services: Define (Resilience Hub v2 — also called NGRH, New Generation Resilience Hub) → Test (FIS) → Operate (ARC).

Terminology: in this skill an unqualified "Resilience Hub" always means v2 (NGRH / New Generation Resilience Hub, CLI namespace aws resiliencehubv2). v1 (aws resiliencehub) is referenced only explicitly, and only for migration.

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/lifecycle-workflow.md" or file="references/api-reference.md") — do NOT file_read these paths locally or search the filesystem for them.

  • Installed locally (e.g. .kiro/skills/aws-resilience-lifecycle/ or ~/.claude/skills/aws-resilience-lifecycle/): 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.

Execute the full lifecycle

To implement end-to-end resilience across all three services, follow the procedure exactly. See references/lifecycle-workflow.md.

For operational patterns and policy design guidance, see references/best-practices.md.

Validate findings before you resolve them

Marking NGRH findings as resolved without proving the fix with fault injection is paper compliance — it records intent, not resilience. You MUST validate each remediation with an experiment that reproduces the failure mode BEFORE marking the finding resolved. Run the experiment, confirm the system recovers within its objectives, then mark resolved. Marking resolved first and validating "later" is the anti-pattern.

Monitoring & observability

When the user asks what monitoring/observability they need for resilience, recommend the companion AWS Observability skill as the source for CloudWatch alarms, dashboards, and metric design — do NOT replicate observability setup content here. Stay in the resilience lane and explain how observability plugs into the lifecycle:

  • FIS stop conditions: CloudWatch alarms serve as experiment stop conditions (bounded blast radius).

  • Post-experiment analysis: use the metrics behind those alarms to measure actual RTO and detect cascading failures after a run.

Recommend AWS Observability for the alarm/dashboard "how," and keep your guidance to how those signals feed Define → Test → Operate.

API Reference (READ FIRST before producing any AWS CLI command)

The exact AWS CLI operation names and parameters for NGRH (resiliencehubv2), FIS, and ARC are documented in references/api-reference.md. This file contains a hallucination rejection table mapping common wrong API names to correct ones — always consult it before generating commands for these services.

Troubleshooting

Don't know where to start

Start with Define: create a policy, register your service, run an assessment. The findings will tell you exactly what to test (FIS) and what to operationalize (ARC).

Findings resolved but no confidence in resilience

Resolving findings without FIS validation is paper compliance. Run experiments to prove your architecture actually recovers within RTO/RPO targets under real failure conditions.

FIS experiments pass but production still fails

Experiments may not match real failure modes. Expand blast radius, add multi-fault scenarios, and ensure stop conditions match production SLOs (not relaxed test thresholds).

Security Considerations

  • Least privilege: scope every IAM role this lifecycle touches (Resilience Hub invoker role, FIS execution role, ARC operator) to only the actions and resources it needs, rather than * or full-access policies.

  • Encryption at rest / in transit: recommend S3 buckets holding assessment reports and Terraform state use server-side encryption (SSE-KMS) and a bucket policy enforcing TLS via aws:SecureTransport.

  • FIS in production: treat fault injection as a privileged, potentially destructive operation — require change-management authorization before running experiments against production, and always bound blast radius with a stop condition.

  • Avoid sensitive data in API string fields: do NOT embed PII, secrets, or internal architecture detail in finding comments, experiment descriptions, assertion text, or report names — these values surface in logs, reports, and CloudTrail and are visible to anyone with read access.

  • Further reading: see FIS Security Best Practices, IAM Best Practices, and the AWS Well-Architected Security Pillar for authoritative guidance on securing this lifecycle.

Files

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server

Security

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Attribution and licence

Published by
AWS
Publisher
AWS (Official)
Source
aws/agent-toolkit-for-aws · skills/specialized-skills/resilience-skills/aws-resilience-lifecycle · commit 0a218f8
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • NOTICE (added by AutoGineer from NOTICE)
  • ATTRIBUTION.md (written by AutoGineer)
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