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Event Driven Patterns Agent Skill

Message queue patterns with BullMQ, Kafka, RabbitMQ - saga, outbox, dead letter queue, exactly-once semantics.

2k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
521
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/vibeeval/vibecosystem --skill event-driven-patterns

The instruction itself

9 sections, as written by the author

Event-Driven Patterns

Message queue and event bus patterns for decoupled, reliable async processing.

BullMQ Setup (Producer + Consumer)

import { Queue, Worker, QueueEvents } from 'bullmq'
import Redis from 'ioredis'

const connection = new Redis(process.env.REDIS_URL!, { maxRetriesPerRequest: null })

// Producer: define queue
const emailQueue = new Queue('email', { connection })
const marketQueue = new Queue('market-resolution', { connection })

// Add job with options
await emailQueue.add(
  'send-welcome',
  { userId: 'abc', email: '[email protected]' },
  {
    attempts: 3,
    backoff: { type: 'exponential', delay: 1000 },
    removeOnComplete: { count: 1000 },
    removeOnFail: { count: 5000 }
  }
)

// Delayed job (send after 1 hour)
await emailQueue.add('send-reminder', { userId: 'abc' }, { delay: 3_600_000 })

// Consumer: named processor
const emailWorker = new Worker(
  'email',
  async (job) => {
    if (job.name === 'send-welcome') {
      await sendWelcomeEmail(job.data.email)
    } else if (job.name === 'send-reminder') {
      await sendReminderEmail(job.data.userId)
    }
    // Return value stored in job.returnvalue
    return { sent: true, at: new Date().toISOString() }
  },
  {
    connection,
    concurrency: 10
  }
)

emailWorker.on('completed', (job, result) => {
  console.log(`Job ${job.id} completed:`, result)
})

emailWorker.on('failed', (job, err) => {
  console.error(`Job ${job?.id} failed after ${job?.attemptsMade} attempts:`, err.message)
})

Retry Policies and Dead Letter Queue

import { Queue, Worker, QueueEvents } from 'bullmq'

const dlqQueue = new Queue('dead-letter', { connection })

const processingWorker = new Worker(
  'orders',
  async (job) => {
    // Attempt processing
    await processOrder(job.data)
  },
  {
    connection,
    concurrency: 5
  }
)

// Move failed jobs to DLQ after all retries exhausted
processingWorker.on('failed', async (job, err) => {
  if (!job) return
  const isExhausted = job.attemptsMade >= (job.opts.attempts || 1)

  if (isExhausted) {
    await dlqQueue.add('order-failed', {
      originalJob: job.name,
      data: job.data,
      error: err.message,
      failedAt: new Date().toISOString(),
      attempts: job.attemptsMade
    })
    console.error(`Job moved to DLQ: ${job.id}`)
  }
})

// DLQ consumer: alert + manual review
const dlqWorker = new Worker('dead-letter', async (job) => {
  await alertOpsTeam({
    message: `Job failed permanently: ${job.data.originalJob}`,
    data: job.data
  })
}, { connection })

Transactional Outbox Pattern

// Problem: write to DB and publish event atomically (no lost messages)
// Solution: write event to outbox table in same transaction, relay worker reads and publishes

// DB schema
// CREATE TABLE outbox (
//   id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
//   aggregate_type TEXT NOT NULL,
//   aggregate_id TEXT NOT NULL,
//   event_type TEXT NOT NULL,
//   payload JSONB NOT NULL,
//   published_at TIMESTAMPTZ,
//   created_at TIMESTAMPTZ DEFAULT now()
// );

async function createMarketWithOutbox(data: CreateMarketDto): Promise<Market> {
  return db.$transaction(async (tx) => {
    // 1. Write domain entity
    const market = await tx.market.create({ data })

    // 2. Write outbox event in SAME transaction
    await tx.outbox.create({
      data: {
        aggregateType: 'Market',
        aggregateId: market.id,
        eventType: 'MarketCreated',
        payload: { marketId: market.id, name: market.name, createdAt: market.createdAt }
      }
    })

    return market
  })
}

// Relay worker: poll outbox and publish (runs separately)
async function outboxRelay(): Promise<void> {
  const unpublished = await db.outbox.findMany({
    where: { publishedAt: null },
    orderBy: { createdAt: 'asc' },
    take: 100
  })

  for (const event of unpublished) {
    try {
      await publishToQueue(event.eventType, event.payload)
      await db.outbox.update({
        where: { id: event.id },
        data: { publishedAt: new Date() }
      })
    } catch (err) {
      console.error(`Outbox relay failed for ${event.id}:`, err)
    }
  }
}

// Poll every second
setInterval(outboxRelay, 1000)

Saga Pattern (Orchestration)

// Orchestrator drives the saga steps and handles compensation

interface SagaStep<T> {
  name: string
  execute: (ctx: T) => Promise<Partial<T>>
  compensate: (ctx: T) => Promise<void>
}

class SagaOrchestrator<T extends Record<string, unknown>> {
  constructor(private steps: SagaStep<T>[]) {}

  async run(initialContext: T): Promise<T> {
    const ctx = { ...initialContext }
    const completed: SagaStep<T>[] = []

    for (const step of this.steps) {
      try {
        const result = await step.execute(ctx)
        Object.assign(ctx, result)
        completed.push(step)
        console.log(`Saga step '${step.name}' succeeded`)
      } catch (err) {
        console.error(`Saga step '${step.name}' failed, compensating...`)

        // Compensate in reverse order
        for (const done of completed.reverse()) {
          try {
            await done.compensate(ctx)
            console.log(`Compensated '${done.name}'`)
          } catch (compensateErr) {
            console.error(`Compensation '${done.name}' failed:`, compensateErr)
            // Log to manual intervention queue
          }
        }
        throw err
      }
    }

    return ctx
  }
}

// Order fulfillment saga
interface OrderContext {
  orderId: string
  userId: string
  amount: number
  paymentId?: string
  reservationId?: string
}

const orderSaga = new SagaOrchestrator<OrderContext>([
  {
    name: 'reserve-inventory',
    execute: async (ctx) => {
      const reservationId = await inventory.reserve(ctx.orderId)
      return { reservationId }
    },
    compensate: async (ctx) => {
      if (ctx.reservationId) await inventory.release(ctx.reservationId)
    }
  },
  {
    name: 'charge-payment',
    execute: async (ctx) => {
      const paymentId = await payments.charge(ctx.userId, ctx.amount)
      return { paymentId }
    },
    compensate: async (ctx) => {
      if (ctx.paymentId) await payments.refund(ctx.paymentId)
    }
  },
  {
    name: 'confirm-order',
    execute: async (ctx) => {
      await orders.confirm(ctx.orderId)
      return {}
    },
    compensate: async (ctx) => {
      await orders.cancel(ctx.orderId)
    }
  }
])

Idempotent Consumers (Exactly-Once Semantics)

// Even if a message is delivered twice, process it only once
async function processEventIdempotent(
  eventId: string,
  handler: () => Promise<void>
): Promise<void> {
  const key = `processed:${eventId}`

  // SET NX: only set if not exists (atomic)
  const isNew = await redis.set(key, '1', 'EX', 86_400, 'NX')
  if (!isNew) {
    console.log(`Event ${eventId} already processed, skipping`)
    return
  }

  try {
    await handler()
  } catch (err) {
    // Release lock so it can be retried
    await redis.del(key)
    throw err
  }
}

// In BullMQ worker
const worker = new Worker('payments', async (job) => {
  await processEventIdempotent(job.id!, async () => {
    await processPayment(job.data)
  })
}, { connection })

Fan-Out Pattern

// One event → multiple consumers in parallel
const eventBus = new Queue('events', { connection })

async function publishMarketResolved(marketId: string, outcome: string): Promise<void> {
  const event = { marketId, outcome, resolvedAt: new Date().toISOString() }

  // Fan-out to multiple downstream queues
  await Promise.all([
    notificationQueue.add('market-resolved', event),
    payoutQueue.add('process-payouts', event),
    analyticsQueue.add('track-resolution', event),
    feedQueue.add('update-feed', event)
  ])
}

// Each queue has its own worker with appropriate concurrency and retry config

Priority Queue

// Higher priority number = processed first in BullMQ
await criticalQueue.add('urgent-payout', data, { priority: 1 })   // highest
await normalQueue.add('regular-email', data, { priority: 10 })
await batchQueue.add('report-generation', data, { priority: 100 }) // lowest

// Worker respects priority automatically when picking next job

Queue Monitoring

import { QueueEvents } from 'bullmq'

const queueEvents = new QueueEvents('email', { connection })

// Track job lifecycle
queueEvents.on('waiting', ({ jobId }) => metrics.increment('jobs.waiting'))
queueEvents.on('active', ({ jobId }) => metrics.increment('jobs.active'))
queueEvents.on('completed', ({ jobId }) => metrics.increment('jobs.completed'))
queueEvents.on('failed', ({ jobId, failedReason }) => {
  metrics.increment('jobs.failed')
  console.error(`Job ${jobId} failed: ${failedReason}`)
})
queueEvents.on('stalled', ({ jobId }) => {
  metrics.increment('jobs.stalled')
  console.warn(`Job ${jobId} stalled — worker may have crashed`)
})

// Health check: alert if queue depth grows too large
async function checkQueueHealth(queue: Queue): Promise<void> {
  const counts = await queue.getJobCounts('waiting', 'active', 'failed', 'delayed')

  if (counts.waiting > 1000) {
    await alertOpsTeam({ queue: queue.name, backlog: counts.waiting })
  }
  if (counts.failed > 100) {
    await alertOpsTeam({ queue: queue.name, failures: counts.failed })
  }
}

setInterval(() => checkQueueHealth(emailQueue), 30_000)

Remember: Use the outbox pattern whenever a DB write and an event publish must be atomic. Never publish directly inside a transaction — the broker call can fail after the DB commits, causing lost events.

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