Common signs: slow requests, timeouts and lost jobs. Usual causes: heavy work like emails, reports or AI calls done inside requests. What we do: add a message queue and background workers with retries. What you get: faster responses and reliable jobs.
Our message queue setup moves slow and heavy work, such as emails, reports, file processing, AI calls and integrations, out of your web requests and into background workers. A Codersarts engineer sets up a queue like RabbitMQ, Amazon SQS or Redis with workers, retries and monitoring, so your app responds faster and jobs don't get lost. Fixed price from $199 with 1-day delivery.
Message Queue Setup at a Glance
Item | Details |
|---|---|
Starting price | $199 for one queue and worker |
Delivery | 1 day |
Queues | RabbitMQ, Amazon SQS, Redis with BullMQ, Celery or Sidekiq, Kafka for streams |
Includes | Workers, retries, dead-letter queues and monitoring |
Stacks | Node.js, Python, Ruby, Java, .NET, PHP |
What you get | Faster requests and reliable background jobs |
Revisions | One revision round included |
What Is a Message Queue?
A message queue lets one part of your system hand off work to another without waiting. The web app puts a job on the queue and responds immediately; background workers pick jobs up and process them, with retries if something fails. It speeds up requests, smooths traffic spikes and keeps jobs from being lost.
Signs You Need a Queue
Requests time out while sending emails or generating reports
AI or third-party calls make pages slow
Jobs are lost when a server restarts
Traffic spikes overload slow operations
Cron jobs overlap or fail silently
Why Heavy Work Slows Apps
Work inside requests
Users wait while the server does slow tasks.
No retries
A failed email or API call is simply lost.
No backpressure
Spikes overwhelm downstream services.
Fragile cron
Scheduled jobs overlap or crash unnoticed.
Quick Checks You Can Try First
List operations that take more than a second inside requests.
Check whether your framework has a built-in job system.
Make jobs safe to run twice before adding retries.
Decide which jobs must never be lost.
If the problem remains, our engineers take it from there.
How We Add a Queue
Identify jobs. We find slow work that can run in the background.
Choose a queue. We pick the right tool for your stack and scale.
Set up workers. We add workers that process jobs.
Add reliability. Retries, dead-letter queues and idempotent jobs.
Monitor. Queue length, failures and alerts.
Document. How to add new jobs.
What You Get
A message queue set up and secured
Background workers for your heavy jobs
Retries and dead-letter handling
Monitoring and alerts
Docs for adding jobs
Example result (illustrative)
A coding platform ran code analysis inside each submission request, causing timeouts at peak. We added Redis with BullMQ workers for analysis and notifications. Submissions now respond instantly, and analysis results arrive within seconds even at exam-day traffic.
What Is Included and Not Included
Included | Not included |
|---|---|
One queue and its workers | Large event-streaming platforms |
Retries, dead-letter queues and monitoring | Rewriting business logic |
Up to 3 job types | Hosting costs |
Documentation | Ongoing queue management |
Pricing for Message Queue Setup
Package | Best for | Starting at | Delivery |
|---|---|---|---|
Standard | One queue, up to 3 job types | $199 | 1 day |
Full setup | Several queues, scheduling and scaling workers | $599 | 3 days |
Event streaming | Kafka or event-driven architecture | Custom quote | Agreed with you |
You get a fixed quote after we review your setup. You approve the scope before any payment.
Who This Is For
Apps with slow requests from heavy work
Platforms calling AI or third-party APIs
Teams with fragile cron jobs
Apps preparing for traffic spikes
What We Need From You
Repository access
A list of slow operations
Hosting details
Which jobs must never be lost
Code and data privacy
We sign an NDA on request, work with the least access needed, and never keep copies of your data after delivery. You own all code, configuration and notes.
Key Terms Explained
Message queue: a buffer that holds jobs until workers process them
Worker: a process that runs background jobs
Dead-letter queue: where jobs go after repeated failures
Idempotent: safe to run more than once
Common Mistakes We Avoid
Retrying jobs that aren't safe to repeat
No dead-letter queue, so failures vanish
Not monitoring queue length
Using Kafka when a simple queue is enough
Need More Than One Task?
Need an event-driven architecture? See Event-Driven Systems and Distributed Systems. Or use Prepaid Developer Hours to cover several tasks from one prepaid balance.
Related Tasks
Load Test Your App to confirm the speed-up
Redis Caching Setup if you already use Redis
Architecture Review for wider design questions
Frequently Asked Questions
RabbitMQ, SQS or Redis?
Redis with BullMQ or Celery is simplest for many apps, SQS suits AWS, and RabbitMQ offers rich routing.
When do we need Kafka?
For high-volume event streams and multiple consumers. Most apps need a simple queue instead.
Will jobs be lost if a server restarts?
Not with a durable queue and proper acknowledgments.
How do users see results?
Through polling, webhooks or real-time updates when the job finishes.
Stop Making Users Wait
Share your slow operations, and a Codersarts engineer will move them into reliable background jobs.