Cloudflare Queues

Status: Production Ready ✅ Last Updated: 2026-01-09 Dependencies: cloudflare-worker-base (for Worker setup) Latest Versions: wrangler@4.58.0, @cloudflare/workers-types@4.20260109.0

Recent Updates (2025):

• April 2025: Pull consumers increased limits (5,000 msg/s per queue, up from 1,200 requests/5min)

• March 2025: Pause & Purge APIs (wrangler queues pause-delivery, queues purge)

• 2025: Customizable retention (60s to 14 days, previously fixed at 4 days)

• 2025: Increased queue limits (10,000 queues per account, up from 10)

Quick Start (5 Minutes)

1. Create queue

npx wrangler queues create my-queue

2. Add producer binding to wrangler.jsonc

{ "queues": { "producers": [{ "binding": "MY_QUEUE", "queue": "my-queue" }] } }

3. Send message from Worker

await env.MY_QUEUE.send({ userId: '123', action: 'process-order' });

Or publish via HTTP (May 2025+) from any service

curl -X POST "https://api.cloudflare.com/client/v4/accounts/{account_id}/queues/my-queue/messages"
-H "Authorization: Bearer YOUR_API_TOKEN"
-d '{"messages": [{"body": {"userId": "123"}}]}'

4. Add consumer binding to wrangler.jsonc

{ "queues": { "consumers": [{ "queue": "my-queue", "max_batch_size": 10 }] } }

5. Process messages

export default { async queue(batch: MessageBatch, env: Env): Promise<void> { for (const message of batch.messages) { await processMessage(message.body); message.ack(); // Explicit acknowledgement } } };

6. Deploy and test

npx wrangler deploy npx wrangler tail my-consumer

Producer API

// Send single message await env.MY_QUEUE.send({ userId: '123', action: 'send-email' });

// Send with delay (max 12 hours) await env.MY_QUEUE.send({ action: 'reminder' }, { delaySeconds: 600 });

// Send batch (max 100 messages or 256 KB) await env.MY_QUEUE.sendBatch([ { body: { userId: '1' } }, { body: { userId: '2' } }, ]);

Critical Limits:

• Message size: 128 KB max (including ~100 bytes metadata)

• Messages >128 KB will fail - store in R2 and send reference instead

• Batch size: 100 messages or 256 KB total

• Delay: 0-43200 seconds (12 hours max)

HTTP Publishing (May 2025+)

New in May 2025: Publish messages to queues via HTTP from any service or programming language.

Source: Cloudflare Changelog

Authentication: Requires Cloudflare API token with Queues Edit permissions.

Single message

curl -X POST "https://api.cloudflare.com/client/v4/accounts/{account_id}/queues/my-queue/messages"
-H "Authorization: Bearer YOUR_API_TOKEN"
-H "Content-Type: application/json"
-d '{ "messages": [ {"body": {"userId": "123", "action": "process-order"}} ] }'

Batch messages

curl -X POST "https://api.cloudflare.com/client/v4/accounts/{account_id}/queues/my-queue/messages"
-H "Authorization: Bearer YOUR_API_TOKEN"
-H "Content-Type: application/json"
-d '{ "messages": [ {"body": {"userId": "1"}}, {"body": {"userId": "2"}}, {"body": {"userId": "3"}} ] }'

Use Cases:

• Publishing from external microservices (Node.js, Python, Go, etc.)

• Cron jobs running outside Cloudflare

• Webhook receivers

• Legacy systems integration

• Services without Cloudflare Workers SDK

Event Subscriptions (August 2025+)

New in August 2025: Subscribe to events from Cloudflare services and consume via Queues.

Source: Cloudflare Changelog

Supported Event Sources:

• R2 (bucket.created, object.uploaded, object.deleted, etc.)

• Workers KV

• Workers AI

• Vectorize

• Workflows

• Super Slurper

• Workers Builds

Create Subscription:

npx wrangler queues subscription create my-queue
--source r2
--events bucket.created,object.uploaded

Event Structure:

interface CloudflareEvent { type: string; // 'r2.bucket.created', 'kv.namespace.created' source: string; // 'r2', 'kv', 'ai', etc. payload: any; // Event-specific data metadata: { accountId: string; timestamp: string; }; }

Consumer Example:

export default { async queue(batch: MessageBatch, env: Env): Promise<void> { for (const message of batch.messages) { const event = message.body as CloudflareEvent;

  switch (event.type) {
    case 'r2.bucket.created':
      console.log('New R2 bucket:', event.payload.bucketName);
      await notifyAdmin(event.payload);
      break;

    case 'r2.object.uploaded':
      console.log('File uploaded:', event.payload.key);
      await processNewFile(event.payload.key);
      break;

    case 'kv.namespace.created':
      console.log('New KV namespace:', event.payload.namespaceId);
      break;

    case 'ai.inference.completed':
      console.log('AI inference done:', event.payload.modelId);
      break;
  }

  message.ack();
}

} };

Use Cases:

• Build custom workflows triggered by R2 uploads

• Monitor infrastructure changes (new KV namespaces, buckets)

• Track AI inference jobs

• Audit account activity

• Event-driven architectures without custom webhooks

Consumer API

export default { async queue(batch: MessageBatch, env: Env, ctx: ExecutionContext): Promise<void> { for (const message of batch.messages) { // message.id - unique UUID // message.timestamp - Date when sent // message.body - your content // message.attempts - retry count (starts at 1)

  await processMessage(message.body);
  message.ack(); // Explicit ack (critical for non-idempotent ops)
}

} };

// Retry with exponential backoff message.retry({ delaySeconds: Math.min(60 * Math.pow(2, message.attempts - 1), 3600) });

// Batch methods batch.ackAll(); // Ack all messages batch.retryAll(); // Retry all messages

Critical:

• message.ack()

• Mark success, prevents retry even if handler fails later

• Use explicit ack for non-idempotent operations (DB writes, API calls, payments)

• Implicit ack - If handler returns successfully without calling ack(), all messages auto-acknowledged

• Ordering not guaranteed - Don't assume FIFO message order

Critical Consumer Patterns

Explicit Acknowledgement (Non-Idempotent Operations)

ALWAYS use explicit ack() for: Database writes, API calls, financial transactions

export default { async queue(batch: MessageBatch, env: Env): Promise<void> { for (const message of batch.messages) { try { await env.DB.prepare('INSERT INTO orders (id, amount) VALUES (?, ?)') .bind(message.body.orderId, message.body.amount).run(); message.ack(); // Only ack on success } catch (error) { console.error(Failed ${message.id}:, error); // Don't ack - will retry } } } };

Why? Prevents duplicate writes if one message in batch fails. Failed messages retry independently.

Exponential Backoff for Rate-Limited APIs

export default { async queue(batch: MessageBatch, env: Env): Promise<void> { for (const message of batch.messages) { try { await fetch('https://api.example.com/process', { method: 'POST', body: JSON.stringify(message.body), }); message.ack(); } catch (error) { if (error.status === 429) { const delaySeconds = Math.min(60 * Math.pow(2, message.attempts - 1), 3600); message.retry({ delaySeconds }); } else { message.retry(); } } } } };

Dead Letter Queue (DLQ) - CRITICAL for Production

⚠️ Without DLQ, failed messages are DELETED PERMANENTLY after max_retries

npx wrangler queues create my-dlq

wrangler.jsonc:

{ "queues": { "consumers": [{ "queue": "my-queue", "max_retries": 3, "dead_letter_queue": "my-dlq" // Messages go here after 3 failed retries }] } }

DLQ Consumer:

export default { async queue(batch: MessageBatch, env: Env): Promise<void> { for (const message of batch.messages) { console.error('PERMANENTLY FAILED:', message.id, message.body); await env.DB.prepare('INSERT INTO failed_messages (id, body) VALUES (?, ?)') .bind(message.id, JSON.stringify(message.body)).run(); message.ack(); // Remove from DLQ } } };

Known Issues Prevention

This skill prevents 13 documented issues:

Issue #1: Multiple Dev Commands - Queues Don't Flow Between Processes

Error: Queue messages sent in one wrangler dev process don't appear in another wrangler dev consumer process Source: GitHub Issue #9795

Why It Happens: The virtual queue used by wrangler is in-process memory. Separate dev processes cannot share the queue state.

Prevention:

❌ Don't run producer and consumer as separate processes

Terminal 1: wrangler dev (producer)

Terminal 2: wrangler dev (consumer) # Won't receive messages!

✅ Option 1: Run both in single dev command

wrangler dev -c producer/wrangler.jsonc -c consumer/wrangler.jsonc

✅ Option 2: Use Vite plugin with auxiliaryWorkers

vite.config.ts:

export default defineConfig({ plugins: [ cloudflare({ auxiliaryWorkers: ['./consumer/wrangler.jsonc'] }) ] })

Issue #2: Queue Producer Binding Causes 500 Errors with Remote Dev

Error: All routes return 500 Internal Server Error when using wrangler dev --remote with queue bindings Source: GitHub Issue #9642

Why It Happens: Queues are not yet supported in wrangler dev --remote mode. Even routes that don't use the queue binding fail.

Prevention:

// When using remote dev, temporarily comment out queue bindings { "queues": { // "producers": [{ "queue": "my-queue", "binding": "MY_QUEUE" }] } }

// Or use local dev instead // wrangler dev (without --remote)

Issue #3: D1 Remote Breaks When Queue Remote is Set

Error: D1 remote binding stops working when remote: true is set on queue producer binding Source: GitHub Issue #11106

Why It Happens: Binding conflict issue affecting mixed local/remote development.

Prevention:

// ❌ Don't mix D1 remote with queue remote { "d1_databases": [{ "binding": "DB", "database_id": "...", "remote": true }], "queues": { "producers": [{ "binding": "QUEUE", "queue": "my-queue", "remote": true // ❌ Breaks D1 remote }] } }

// ✅ Avoid remote on queues when using D1 remote { "d1_databases": [{ "binding": "DB", "remote": true }], "queues": { "producers": [{ "binding": "QUEUE", "queue": "my-queue" }] } }

Status: No workaround yet. Track issue for updates.

Issue #4: Mixed Local/Remote Bindings - Queue Consumer Missing

Error: Queue consumer binding does not appear when mixing local queues with remote AI/Vectorize bindings Source: GitHub Issue #9887

Why It Happens: Wrangler doesn't support mixed local/remote bindings in the same worker.

Prevention:

// ❌ Don't mix local queues with remote AI { "queues": { "consumers": [{ "queue": "my-queue" }] }, "ai": { "binding": "AI", "experimental_remote": true // ❌ Breaks queue consumer } }

// ✅ Option 1: All local (no remote bindings) wrangler dev

// ✅ Option 2: Separate workers for queues vs AI // Worker 1: Queue processing (local) // Worker 2: AI operations (remote)

Issue #5: http_pull Type Prevents Worker Consumer Execution

Error: Queue consumer with type: "http_pull" doesn't execute in production Source: GitHub Issue #6619

Why It Happens: http_pull is for external HTTP-based consumers, not Worker-based consumers.

Prevention:

// ❌ Don't use type: "http_pull" for Worker consumers { "queues": { "consumers": [{ "queue": "my-queue", "type": "http_pull", // ❌ Wrong for Workers "max_batch_size": 10 }] } }

// ✅ Omit type field for push-based Worker consumers { "queues": { "consumers": [{ "queue": "my-queue", "max_batch_size": 10 // No "type" field - defaults to Worker consumer }] } }

Breaking Changes & Deprecations

delivery_delay in Producer Config (Upcoming Removal)

Warning: The delivery_delay parameter in producer bindings will be removed in a future wrangler version.

Source: GitHub Issue #10286

// ❌ Will be removed - don't use { "queues": { "producers": [{ "binding": "MY_QUEUE", "queue": "my-queue", "delivery_delay": 300 // ❌ Don't use this }] } }

Migration: Use per-message delay instead:

// ✅ Correct approach - per-message delay await env.MY_QUEUE.send({ data }, { delaySeconds: 300 });

Why: Workers should not affect queue-level settings. With multiple producers, the setting from the last-deployed producer wins, causing unpredictable behavior.

Community Tips

Note: These tips come from community discussions and GitHub issues. Verify against your wrangler version.

Tip: max_batch_timeout May Break Local Development

Source: GitHub Issue #6619 Confidence: MEDIUM Applies to: Local development with wrangler dev

If your queue consumer doesn't execute locally, try removing max_batch_timeout :

{ "queues": { "consumers": [{ "queue": "my-queue", "max_batch_size": 10 // Remove max_batch_timeout for local dev }] } }

This appears to be version-specific and may not affect all setups.

Tip: Queue Name Not Available on Producer Bindings

Source: GitHub Issue #10131 Confidence: HIGH Applies to: Multi-environment deployments (staging, PR previews, tenant-specific queues)

Queue names are only available via batch.queue in consumer handlers, not on producer bindings. This creates issues with environment-specific queue names like email-queue-staging or email-queue-pr-123 .

Current Limitation:

// ❌ Can't access queue name from producer binding const queueName = env.MY_QUEUE.name; // Doesn't exist!

// ❌ Must hardcode or normalize in consumer switch (batch.queue) { case 'email-queue': // What about email-queue-staging? case 'email-queue-staging': // Must handle all variants case 'email-queue-pr-123': // Dynamic env names break this }

Workaround:

// In consumer: Normalize queue name function normalizeQueueName(queueName: string): string { return queueName.replace(/-staging|-pr-\d+|-dev/g, ''); }

switch (normalizeQueueName(batch.queue)) { case 'email-queue': // Handle all email-queue-* variants }

Status: Feature request tracked internally: MQ-923

Consumer Configuration

{ "queues": { "consumers": [{ "queue": "my-queue", "max_batch_size": 100, // 1-100 (default: 10) "max_batch_timeout": 30, // 0-60s (default: 5s) "max_retries": 5, // 0-100 (default: 3) "retry_delay": 300, // Seconds (default: 0) "max_concurrency": 10, // 1-250 (default: auto-scale) "dead_letter_queue": "my-dlq" // REQUIRED for production }] } }

Critical Settings:

• Batching - Consumer called when EITHER condition met (max_batch_size OR max_batch_timeout)

• max_retries - After exhausted: with DLQ → sent to DLQ, without DLQ → DELETED PERMANENTLY

• max_concurrency - Only set if upstream has rate limits or connection limits. Otherwise leave unset for auto-scaling (up to 250 concurrent invocations)

• DLQ - Create separately: npx wrangler queues create my-dlq

Wrangler Commands

Create queue

npx wrangler queues create my-queue npx wrangler queues create my-queue --message-retention-period-secs 1209600 # 14 days

Manage queues

npx wrangler queues list npx wrangler queues info my-queue npx wrangler queues delete my-queue # ⚠️ Deletes ALL messages!

Pause/Purge (March 2025 - NEW)

npx wrangler queues pause-delivery my-queue # Pause processing, keep receiving npx wrangler queues resume-delivery my-queue npx wrangler queues purge my-queue # ⚠️ Permanently deletes all messages!

Consumer management

npx wrangler queues consumer add my-queue my-consumer-worker
--batch-size 50 --batch-timeout 10 --message-retries 5 npx wrangler queues consumer remove my-queue my-consumer-worker

Limits & Quotas

Feature Limit

Queues per account 10,000

Message size 128 KB (includes ~100 bytes metadata)

Message retries 100 max

Batch size 1-100 messages

Batch timeout 0-60 seconds

Messages per sendBatch 100 (or 256 KB total)

Queue throughput 5,000 messages/second per queue

Message retention 4 days (default), 14 days (max)

Queue backlog size 25 GB per queue

Concurrent consumers 250 (push-based, auto-scale)

Consumer duration 15 minutes (wall clock)

Consumer CPU time 30 seconds (default), 5 minutes (max)

Visibility timeout 12 hours (pull consumers)

Message delay 12 hours (max)

API rate limit 1200 requests / 5 minutes

Pricing

Requires Workers Paid plan ($5/month)

Operations Pricing:

• First 1,000,000 operations/month: FREE

• After that: $0.40 per million operations

What counts as an operation:

• Each 64 KB chunk written, read, or deleted

• Messages >64 KB count as multiple operations:

• 65 KB message = 2 operations

• 127 KB message = 2 operations

• 128 KB message = 2 operations

Typical message lifecycle:

• 1 write + 1 read + 1 delete = 3 operations

Retries:

• Each retry = additional read operation

• Message retried 3 times = 1 write + 4 reads + 1 delete = 6 operations

Dead Letter Queue:

• Writing to DLQ = additional write operation

Cost examples:

• 1M messages/month (no retries): ((1M × 3) - 1M) / 1M × $0.40 = $0.80

• 10M messages/month: ((10M × 3) - 1M) / 1M × $0.40 = $11.60

• 100M messages/month: ((100M × 3) - 1M) / 1M × $0.40 = $119.60

Error Handling

Common Errors

1. Message Too Large

// ❌ Bad: Message >128 KB await env.MY_QUEUE.send({ data: largeArray, // >128 KB });

// ✅ Good: Check size before sending const message = { data: largeArray }; const size = new TextEncoder().encode(JSON.stringify(message)).length;

if (size > 128000) { // Store in R2, send reference const key = messages/${crypto.randomUUID()}.json; await env.MY_BUCKET.put(key, JSON.stringify(message)); await env.MY_QUEUE.send({ type: 'large-message', r2Key: key }); } else { await env.MY_QUEUE.send(message); }

2. Throughput Exceeded

// ❌ Bad: Exceeding 5000 msg/s per queue for (let i = 0; i < 10000; i++) { await env.MY_QUEUE.send({ id: i }); // Too fast! }

// ✅ Good: Use sendBatch const messages = Array.from({ length: 10000 }, (_, i) => ({ body: { id: i }, }));

// Send in batches of 100 for (let i = 0; i < messages.length; i += 100) { await env.MY_QUEUE.sendBatch(messages.slice(i, i + 100)); }

// ✅ Even better: Rate limit with delay for (let i = 0; i < messages.length; i += 100) { await env.MY_QUEUE.sendBatch(messages.slice(i, i + 100)); if (i + 100 < messages.length) { await new Promise(resolve => setTimeout(resolve, 100)); // 100ms delay } }

3. Consumer Timeout

// ❌ Bad: Long processing without CPU limit increase export default { async queue(batch: MessageBatch): Promise<void> { for (const message of batch.messages) { await processForMinutes(message.body); // CPU timeout! } }, };

// ✅ Good: Increase CPU limit in wrangler.jsonc

wrangler.jsonc:

{ "limits": { "cpu_ms": 300000 // 5 minutes (max allowed) } }

4. Backlog Growing

// Issue: Consumer too slow, backlog growing

// ✅ Solution 1: Increase batch size { "queues": { "consumers": [{ "queue": "my-queue", "max_batch_size": 100 // Process more per invocation }] } }

// ✅ Solution 2: Let concurrency auto-scale (don't set max_concurrency)

// ✅ Solution 3: Optimize consumer code export default { async queue(batch: MessageBatch, env: Env): Promise<void> { // Process in parallel await Promise.all( batch.messages.map(async (message) => { await process(message.body); message.ack(); }) ); }, };

Critical Rules

Always:

• ✅ Configure DLQ for production (dead_letter_queue in consumer config)

• ✅ Use explicit message.ack() for non-idempotent ops (DB writes, API calls)

• ✅ Validate message size <128 KB before sending

• ✅ Use sendBatch() for multiple messages (more efficient)

• ✅ Implement exponential backoff: 60 * Math.pow(2, message.attempts - 1)

• ✅ Let concurrency auto-scale (don't set max_concurrency unless upstream has rate limits)

Never:

• ❌ Never assume FIFO ordering - not guaranteed

• ❌ Never rely on implicit ack for non-idempotent ops - use explicit ack()

• ❌ Never send messages >128 KB - will fail (store in R2 instead)

• ❌ Never skip DLQ in production - failed messages DELETED PERMANENTLY without DLQ

• ❌ Never exceed 5,000 msg/s per queue (push consumers) or rate limits apply

• ❌ Never process messages synchronously - use Promise.all() for parallelism

Troubleshooting

Issue: Messages not being delivered to consumer

Possible causes:

• Consumer not deployed

• Wrong queue name in wrangler.jsonc

• Delivery paused

• Consumer throwing errors

Solution:

Check queue info

npx wrangler queues info my-queue

Check if delivery paused

npx wrangler queues resume-delivery my-queue

Check consumer logs

npx wrangler tail my-consumer

Issue: Entire batch retried when one message fails

Cause: Using implicit acknowledgement with non-idempotent operations

Solution: Use explicit ack()

// ✅ Explicit ack for (const message of batch.messages) { try { await dbWrite(message.body); message.ack(); // Only ack on success } catch (error) { console.error(Failed: ${message.id}); // Don't ack - will retry } }

Issue: Messages deleted without processing

Cause: No Dead Letter Queue configured

Solution:

Create DLQ

npx wrangler queues create my-dlq

Add to consumer config

{ "queues": { "consumers": [{ "queue": "my-queue", "dead_letter_queue": "my-dlq" }] } }

Issue: Consumer not auto-scaling

Possible causes:

• max_concurrency set to 1

• Consumer returning errors (not processing)

• Batch processing too fast (no backlog)

Solution:

{ "queues": { "consumers": [{ "queue": "my-queue", // Don't set max_concurrency - let it auto-scale "max_batch_size": 50 // Increase batch size instead }] } }

Related Documentation

• Cloudflare Queues Docs

• How Queues Works

• JavaScript APIs

• Batching & Retries

• Consumer Concurrency

• Dead Letter Queues

• Wrangler Commands

• Limits

• Pricing

Last Updated: 2026-01-21 Version: 2.0.0 Changes: Added HTTP Publishing (May 2025), Event Subscriptions (Aug 2025), Known Issues Prevention (13 issues), Breaking Changes section, Community Tips. Error count: 0 → 13. Major feature additions and comprehensive issue documentation. Maintainer: Jeremy Dawes | jeremy@jezweb.net