Step-by-Step Tutorial: Integrate AWS IoT Core with SQS.

Introduction.

In today’s rapidly evolving digital landscape, IoT (Internet of Things) is playing a pivotal role in transforming industries. From smart homes to industrial automation, connected devices are generating massive amounts of data in real time. As this data flows in, the challenge lies not only in collecting it efficiently but also in routing it to the right systems for processing, analytics, or triggering actions. That’s where AWS IoT Core comes in—a fully managed cloud service that lets connected devices interact securely and reliably with cloud applications and other devices.

However, collecting data is only half the battle. Once your devices publish messages to AWS IoT Core via MQTT or other supported protocols, you need a scalable and reliable way to process or forward that data. One of the simplest and most robust solutions for this is Amazon SQS (Simple Queue Service). SQS allows decoupling between systems, reliable message queuing, and easy scaling for downstream processing.

This blog post dives into how you can seamlessly integrate AWS IoT Core with Amazon SQS, allowing real-time messages from your IoT devices to be sent directly into an SQS queue for further processing. This integration is incredibly useful for scenarios like buffering telemetry data, queuing sensor alerts for processing by a serverless application, or managing workloads across distributed services.

Whether you’re working on a smart agriculture solution, a connected vehicle platform, or a home automation system, this architecture enables resilience and flexibility. With this setup, if your processing backend slows down or becomes temporarily unavailable, SQS ensures that no data is lost—everything gets queued safely and can be processed when resources are available again.

AWS provides the tools to do this with minimal friction. AWS IoT Core allows you to define rules that trigger actions when messages are received. One such action is “Send a message to an SQS queue”, which forms the backbone of our integration. With a few clicks and the right IAM permissions, you can wire up this system to send every MQTT message from your devices into a resilient message queue.

In this tutorial, we’ll walk through the entire process from scratch. You’ll learn how to create an SQS queue, configure the necessary IAM roles and permissions, set up an IoT rule that targets SQS, and test the entire pipeline using the AWS MQTT test client. We’ll break everything down into manageable, beginner-friendly steps, so even if you’re new to AWS or IoT development, you’ll be able to follow along.

Beyond the technical steps, we’ll also touch on real-world use cases, security best practices, and scaling considerations so you understand not just how to implement the solution, but why it’s designed this way and how it fits into broader cloud architecture patterns.

By the end of this post, you’ll have a working prototype where an MQTT message from an IoT device is automatically pushed into an Amazon SQS queue. You’ll also gain a deeper understanding of AWS services, how they interconnect, and how to build reliable, decoupled systems using AWS-managed infrastructure.

Let’s dive in and get your IoT data flowing smoothly into your cloud applications—securely, efficiently, and scalably.

Step 1: Create an Amazon SQS Queue

1. Go to the Amazon SQS console: https://console.aws.amazon.com/sqs/
2. Click Create queue.
3. Choose Standard Queue (or FIFO if needed).
4. Enter a name, e.g., MyIoTQueue.
5. Leave default settings or customize as needed.
6. Click Create Queue.
7. Copy the Queue ARN and Queue URL (you’ll need this later).

Step 2: Create an IAM Role for AWS IoT Core

1. Go to the IAM console: https://console.aws.amazon.com/iam/
2. Click Roles > Create role.
3. Choose AWS Service > IoT as the trusted entity.
4. Click Next.
5. Attach the following inline policy or use an existing one:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": "sqs:SendMessage",
      "Resource": "arn:aws:sqs:your-region:your-account-id:MyIoTQueue"
    }
  ]
}

1. Name the role something like IoT_SQSSendRole.
2. Click Create role.

Step 3: Create an AWS IoT Rule

1. Go to the AWS IoT Core Console: https://console.aws.amazon.com/iot/
2. In the left menu, click Act > Rules.
3. Click Create Rule.
4. Give the rule a name, e.g., SendToSQSRule.

Fill in:

• SQL version: 2016-03-23
• Rule query statement: sqlCopyEdit

SELECT * FROM 'iot/topic'

Under Set one or more actions:

1. Choose Send a message to an SQS queue.
2. Select your SQS Queue.
3. Choose the IAM role you created (IoT_SQSSendRole).
4. (Optional) You can add a custom message format using JSON if needed.
5. Click Create rule.

Step 4: Test the Integration

1. Use MQTT test client in AWS IoT:
   • Go to Test > MQTT test client.
   • Publish a message to the topic iot/topic:

{
  "temperature": 22.5,
  "deviceId": "sensor001"
}

Go to Amazon SQS console and check if the message appears in the queue.

Conclusion.

Integrating AWS IoT Core with Amazon SQS opens up a powerful pattern for building scalable, decoupled, and event-driven IoT applications. With just a few steps, you’ve learned how to capture device data in real time, route it through AWS IoT Core, and securely send it to an SQS queue for downstream processing. This architecture not only improves system resilience but also simplifies workload management, especially when dealing with bursts of data or asynchronous processing requirements.

By leveraging IoT Rules, IAM roles, and SQS queue actions, AWS allows you to build a robust messaging pipeline with minimal overhead. Whether you’re buffering telemetry, triggering downstream Lambda functions, or integrating with legacy systems, SQS acts as a reliable broker between your IoT data and backend systems.

What makes this integration even more valuable is its scalability and flexibility. You can expand on this foundation by connecting SQS to AWS Lambda, Amazon Kinesis, or custom microservices, creating a comprehensive and responsive IoT data pipeline.

As you continue to build and optimize your solution, remember to monitor queue depths, handle message retries gracefully, and apply the principle of least privilege in your IAM roles. These best practices will ensure your IoT applications remain secure, reliable, and cost-efficient over time.

With this setup in place, you’re well on your way to building a production-grade IoT system that can handle real-world demands. Keep experimenting, iterate based on feedback, and explore how AWS’s broader ecosystem can help you scale from prototype to production with confidence.