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Architecture · Version 1.5.0 · Reviewed 2026-08-02

AWS Architecture Advisor

Make a defensible decision about service selection and Multi-AZ design with evidence, explicit trade-offs, and a verification plan.

4 method steps 4 documented failure modes 4 diagnostic checks 7 quality gates

Reviews AWS designs for availability, cost, security posture, and the managed-service choices that fit the workload.

₹99 one-time

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What this skill helps you do

  • Service selection
  • Multi-AZ design
  • Cost-aware architecture

How AWS Architecture Advisor works

You provide

Requirements, constraints, and the current topology

It inspects

Critical path and failure boundaries for service selection

It decides

A Multi-AZ design decision with consequences recorded

You verify

Rollout stages with the signal that gates each one

What it checks first

AWS Architecture Advisor reviews AWS designs for availability, cost, security posture, and the managed-service choices that fit the workload. Use it when the work involves Service selection, Multi-AZ design, Cost-aware architecture.

  1. The quality attribute that actually constrains the design: latency, consistency, availability, cost, or compliance.
  2. The critical path and the number of network hops on it.
  3. Where state lives and who owns it, since ownership ambiguity becomes a correctness problem.
  4. The failure behavior of every dependency: fail open, fail closed, or degrade.

Failure modes it recognizes

  • Synchronous coupling making availability the product of all dependency availabilities.
  • A shared database creating hidden coupling between nominally independent services.
  • A component with no clear owner, so its failure has no defined response.
  • Distributed transactions attempted across services without a saga or compensation model.

Answers it will reject

  • Selecting a technology before establishing the constraint it is meant to satisfy.
  • Presenting a diagram as a design without the failure and data-consistency model.
  • Optimizing for a hypothetical future scale at the cost of present operability.

Decision rules it applies

  • Make the consistency requirement explicit per operation, not per system.
  • Prefer designs whose failure modes are understood over designs whose peak performance is higher.
  • Record the decision, the rejected alternatives, and the conditions that would reverse it.

Evidence it asks for

  • Quantify load, growth, and latency budget with arithmetic and stated assumptions.
  • Define the rollout stages and the signal that gates each one.
  • Name the reversal path for the decision.

The method inside

  1. Map the artifact, actors, boundaries, and invariants relevant to service selection.
  2. Trace concrete failure or abuse paths for Multi-AZ design; do not report checklist items without a mechanism.
  3. Prioritize cost-aware architecture findings by impact, likelihood, confidence, and cost of correction.
  4. Recommend the smallest defensible change, then define how an independent reviewer can verify it.

Deliverables

  • Service selection assessment
  • Multi-AZ design decision and action plan
  • Cost-aware architecture verification checklist

Evidence requirements

  • Functional and quality requirements
  • Scale, latency, consistency, cost, and compliance constraints
  • Current topology and alternatives considered

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

Should this workload run on ECS Fargate, EKS, or Lambda? It is a spiky internal API.

Expected output

Spiky and internal favors Lambda unless you have long-running or high-memory work. Compare on cold-start tolerance, concurrency limits, and operational overhead...

Boundaries and compatibility

Ideal for

  • Service selection: produce a decision or artifact grounded in supplied evidence.
  • Multi-AZ design: produce a decision or artifact grounded in supplied evidence.
  • Cost-aware architecture: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Producing a generic reference architecture without requirements
  • Hiding material trade-offs behind best-practice language

Agent compatibility

  • GitHub Copilot custom agents
  • Claude Agent Skills / SKILL.md
  • Any instruction-following chat model

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.