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Data · Version 1.1.0 · Reviewed 2026-08-02

RabbitMQ Topology Advisor

Make data systems more correct and operable for exchange and routing design and consumer throughput tuning with evidence, explicit trade-offs, and a verification plan.

4 method steps 6 documented failure modes 5 diagnostic checks 7 quality gates

Designs exchanges, queues, bindings, acknowledgements, dead-lettering, quorum queues, and consumer prefetch for reliable messaging.

₹99 one-time

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What this skill helps you do

  • Exchange and routing design
  • Consumer throughput tuning
  • Dead-letter strategy

How RabbitMQ Topology Advisor works

You provide

Topic config, consumer settings, and lag history

It inspects

Per-partition lag and processing time for exchange and routing design

It decides

A consumer throughput tuning decision with ordering guarantees stated

You verify

Lag flattens and dead-letter volume stays bounded

What it checks first

RabbitMQ Topology Advisor designs exchanges, queues, bindings, acknowledgements, dead-lettering, quorum queues, and consumer prefetch for reliable messaging. Use it when the work involves Exchange and routing design, Consumer throughput tuning, Dead-letter strategy.

  1. Consumer lag trend rather than absolute value: flat lag at any level is healthy, rising lag is not.
  2. Partition count versus consumer count, since consumers beyond the partition count are idle by definition.
  3. Whether the partition key produces even distribution, or a few keys dominate one partition.
  4. Rebalance frequency, which converts into repeated processing pauses.
  5. Whether offsets commit before or after processing, which decides between at-most-once and at-least-once.

Failure modes it recognizes

  • A poison message blocking a partition indefinitely because the consumer retries in place without dead-lettering.
  • Processing time exceeding the poll interval, causing the broker to evict the consumer and trigger a rebalance loop.
  • Committing offsets before processing, silently dropping messages on crash.
  • Producer key set to null or a timestamp, destroying ordering guarantees the consumer assumed.
  • Consumer group rebalance storms from short session timeouts on a slow consumer.
  • Unbounded retention plus a compaction misconfiguration filling disk and stopping the broker.

Answers it will reject

  • Adding consumers to reduce lag when partitions are already saturated — throughput is bounded by partitions.
  • Increasing partitions to fix lag without checking whether processing is CPU-bound downstream.
  • Treating the queue as a database by retaining everything and querying it by scan.
  • Requeueing a failed message to the tail forever, converting a bug into an infinite loop.

Decision rules it applies

  • Order is guaranteed only within a partition, so any ordering requirement must map to a partition key.
  • Choose at-least-once with idempotent consumers over attempting exactly-once across systems.
  • Dead-letter after a bounded retry count with the failure reason attached; never retry indefinitely in place.
  • Size partitions for peak throughput plus headroom, because increasing partitions later breaks key-to-partition mapping.

Evidence it asks for

  • Track consumer lag per partition, not aggregated, so a single stuck partition is visible.
  • Measure processing time per message against `max.poll.interval.ms`.
  • Alert on rebalance rate and on dead-letter volume as separate signals.

The method inside

  1. Map the artifact, actors, boundaries, and invariants relevant to exchange and routing design.
  2. Trace concrete failure or abuse paths for consumer throughput tuning; do not report checklist items without a mechanism.
  3. Prioritize dead-letter strategy 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

  • Exchange and routing design assessment
  • Consumer throughput tuning decision and action plan
  • Dead-letter strategy verification checklist

Evidence requirements

  • Schema, access patterns, query plans, or event contracts
  • Volume, cardinality, retention, and freshness
  • Consistency, latency, and migration constraints

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

Design RabbitMQ topology for order events consumed independently by billing, fulfillment, and analytics.

Expected output

Use one durable topic exchange with a dedicated quorum queue per consumer domain. Independent queues prevent a slow analytics consumer from blocking billing; set bounded retries and dead-letter poison messages instead of requeueing forever...

Boundaries and compatibility

Ideal for

  • Exchange and routing design: produce a decision or artifact grounded in supplied evidence.
  • Consumer throughput tuning: produce a decision or artifact grounded in supplied evidence.
  • Dead-letter strategy: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Recommending indexes without a workload
  • Treating eventual consistency as universally acceptable

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.