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CodeTracked since May 19, 2026

Add AI-DLC optional resiliency extension with WAR-aligned reliability enforcement

This PR introduces a new AI-DLC resiliency extension that adds a 15-rule reliability baseline mapped to 11 of 13 AWS Well-Architected Reliability Pillar questions, gates requirements capture via an opt-in workflow plus an RTO/RPO follow-up, and provides template-based validation so reliability controls are checked through generated CloudFormation artifacts.

AI-DLCresiliency extensionAWS Well-Architected Framework Reliability PillarRESILIENCY-02

What Happened

  • This PR introduces a new AI-DLC resiliency extension that adds a 15-rule reliability baseline mapped to 11 of 13 AWS Well-Architected Reliability Pillar questions, gates requirements capture via an opt-in workflow plus an RTO/RPO follow-up, and provides template-based validation so reliability controls are checked through generated CloudFormation artifacts.
  • This PR introduces a new AI-DLC resiliency extension that adds a 15-rule reliability baseline mapped to 11 of 13 AWS Well-Architected Reliability Pillar questions, gates requirements capture via an opt-in workflow plus an RTO/RPO follow-up, and provides template-based validation so reliability controls are checked through generated CloudFormation artifacts.
  • 1 evidence item attached for review.

What is Different

Before

Scattered source updates, isolated context, and manual follow-up across multiple feeds.

Now

Introduces a concrete resiliency-by-design capability: a ruleset + opt-in flow that captures recovery objectives and DR strategy during requirements, then propagates those constraints into design/infrastructure stages and enforces them against templates via comparison and review tooling.

Why Track This

Why It Matters

Teams building applications with AI-DLC can enable the resiliency extension and receive explicit reliability requirements and safeguards (for example RTO/RPO targets, DR strategy, observability defaults, and health checks) before deployment, which reduces the operational risk of discovering resilience gaps only after production exposure. The change also brings measurable gains in reviewed templates (9/15 rules compliant vs 3/15 without it), but it should be tracked for template-review accuracy, whether the added context (~4,370 tokens) affects larger workflows, and what gaps remain from the excluded REL 2 and REL 3 areas.

Impact

Teams building applications with AI-DLC can enable the resiliency extension and receive explicit reliability requirements and safeguards (for example RTO/RPO targets, DR strategy, observability defaults, and health checks) before deployment, which reduces the operational risk of discovering resilience gaps only after production exposure. The change also brings measurable gains in reviewed templates (9/15 rules compliant vs 3/15 without it), but it should be tracked for template-review accuracy, whether the added context (~4,370 tokens) affects larger workflows, and what gaps remain from the excluded REL 2 and REL 3 areas.

What To Watch Next

  • Watch whether AI-DLC becomes a repeated pattern.
  • Track follow-up changes around LLMOps.
  • Compare future signals against this evidence trail.
  • Re-check risk flags: review_skill_false_negatives, rules_coverage_gap_rel2_rel3.
Open Topic TimelineOpen Technical EventOpen Original Sourcereview_skill_false_negatives / rules_coverage_gap_rel2_rel3 / opt_in_bypass / context_overhead_at_scale

Supporting Evidence

GITHUB PULL REQUESTHigh Trust

awslabs/aidlc-workflows PR #265: feat(resiliency-extension): add new resiliency extension

The resilient workflow path improved rule compliance from 3/15 to 9/15 in comparison tests, while adding baseline observability and DR features by default (alarms, tracing, health checks, cross-region DR resources, reserved/provisioned concurrency, versioning for point-in-time recovery).