Queues are where your architecture tells the truth.
Not in the slide deck, not in the Jira ticket. In the SQS queue quietly filling up while everyone assumes “the system is fine.
If you work in support or ops, you have already met this queue.
A spike in errors, a delayed order, a Lambda that “randomly” retries for hours, a batch job that never finishes. Someone opens CloudWatch, someone else opens SQS, and suddenly there are ten thousand messages waiting for a consumer that is already at one hundred percent CPU.
There is a reason AWS Well Architected keeps repeating the same pattern decouple, buffer, retry, isolate failures. SQS is the boring primitive that quietly makes that possible.
This guide is not another “click here, then here” tour of the console.
You will build one queue, send one message, receive it, and delete it. But the real goal is different you will understand what is actually happening to that message in between those click.
By the end you will know
Why SQS exists when you already have HTTP, events, and direct database writes.
When to reach for a Standard queue and when a FIFO queue is the only safe option.
How the message lifecycle really works send, store, visibility timeout, retry, delete and where bugs usually hide.
What the console lab is teaching you under the hood so you can later switch to CLI or SDK without feeling lost.
If you are used to Windows, GUIs, and “next, next, finish” wizards, think of this as your first real conversation with a cloud native queue.
The console is just the training wheels. The mental model is what you keep
Goal
Create Amazon SQS queues
Send messages to an SQS queue
Retrieve and delete messages using the AWS Management Console
Pre-requisite
following background knowledge is helpful but not required:
Basic familiarity with the AWS Management Console
OR
Basic understanding of the AWS CLI
Introduction to Amazon Simple Queue Service (SQS)
Amazon Simple Queue Service (Amazon SQS) is a fully managed message queuing service that enables you to build fast, reliable, and scalable distributed applications. It allows different components of an application to communicate with each other asynchronously by sending, storing, and receiving messages—without requiring those components to be available at the same time.
At its core, an SQS queue acts as a temporary message repository. Messages remain in the queue until they are successfully processed and deleted, ensuring that no data is lost even if a component fails or is temporarily unavailable. This makes Amazon SQS a powerful tool for decoupling application components and improving fault tolerance and scalability.
Creating SQS Queue and Publishing Messages
Amazon Simple Queue Service (Amazon SQS) is a fully managed messaging service that provides fast, reliable, and scalable queues for storing messages. It enables seamless communication between distributed components of an application, allowing each component to perform different tasks independently without losing messages or requiring constant availability.
An SQS queue acts as a temporary repository for messages that are waiting to be processed. It serves as a buffer between the component that produces and sends data and the component that receives and processes it. This buffering capability helps resolve common challenges, such as when a producer generates data faster than a consumer can handle, or when either component is intermittently connected to the network.
Amazon SQS guarantees that each message is delivered at least once and supports multiple producers and consumers accessing the same queue simultaneously. A single queue can be safely shared by many distributed application components without requiring them to coordinate with one another, making it an ideal solution for building loosely coupled and highly scalable systems.
Guide: Creating and Sending Messages to an Amazon SQS Queue
Follow the steps below to create an Amazon SQS queue and send your first message using the AWS Management Console.
Step 1: Open Amazon SQS
In the search bar at the top of the AWS Management Console, type SQS.
Under Services, select Simple Queue Service.
Step 2: Create a New Queue
On the SQS dashboard, click Create queue.
Step 3: Configure Queue Settings
Enter q-labs as the Queue name
Leave all other settings at their default values
You will notice two available queue types:
Standard
FIFO (First-In, First-Out)
For now, keep Standard selected. Although Standard queues provide weaker guarantees for message order and delivery compared to FIFO queues, they are more cost-effective and support the highest throughput.
Step 4: Create the Queue
Scroll to the bottom of the page and click Create queue.
After a short moment, a page will load displaying the details of your newly created queue.
Step 5: Return to the Queue List
At the top of the page, click Queues in the breadcrumb navigation to return to the main queue list.
Step 6: Send a Message
Select the q-labs queue and click Send and receive messages.
An SQS message consists of:
A message body
Optional message attributes
The message body can be plain text or structured data such as JSON.
Step 7: Enter the Message Body
In the Message body field, enter:
This is my first message!
Step 8: Add Message Attributes
Expand the Message attributes section and add the following:
Name: WorkerId
Type: Number
Value: 123456
Step 9: Send the Message
In the top-right corner of the page, click Send message.
A confirmation notification will appear indicating the message was successfully sent.
Step 10: View Message Details
Click View details to see:
The SQS message identifier
MD5 checksums for the message body and attributes
These MD5 hashes allow publishers to verify message integrity. When messages are sent programmatically, publishers can compare their locally generated hashes with those returned by Amazon SQS to detect data corruption or tampering—an important feature in regulated or high-compliance environments.
Step 11: Close Message Details
Click Done to close the message details window.
Now, you successfully created an Amazon SQS queue using the AWS Management Console and sent your first message with custom attributes.
This demonstrates how SQS enables reliable message-based communication between distributed application components.
Polling for SQS Messages and Deleting Messages
Use the AWS Management Console to poll for messages from an Amazon Simple Queue Service (SQS) queue. You will review message details and then delete the message after processing it.
Instructions: Polling and Deleting SQS Messages
Step 1: Poll for Messages
To retrieve messages from the queue, click Poll for messages.
If a message is available, it will appear in the messages list.
Note: When requesting messages from an SQS queue, you cannot specify which message to retrieve. Instead, you specify the maximum number of messages to receive (up to 10), and Amazon SQS returns up to that number. Because Amazon SQS is a distributed system, the response may sometimes be empty—especially when the queue contains only a small number of messages.
Step 2: Open Message Details
Click the Message ID located on the far left of the message entry in the queue.
Step 3: Review Message Properties
In the Message Details modal, review the available information by clicking through the different tabs.
You will see details similar to those observed when the message was sent. Notice that the Details section includes a Sender account ID. Amazon SQS queues are often used across AWS accounts, allowing message publishers and consumers to operate in different accounts.
Step 4: Close the Message Details Window
Click Done to close the message details modal.
Step 5: Delete the Message
Select the message in the Messages table and click Delete.
Step 6: Confirm Deletion
In the Delete Messages confirmation dialog box, click Delete.
You will be returned to the Send and receive messages page, where a notification confirms that the message has been successfully deleted.
Now, you successfully polled an Amazon SQS queue for messages, reviewed detailed message properties, and deleted the message after processing. This demonstrates the full lifecycle of receiving and managing messages in an SQS queue using the AWS Management Console.
The Message Lifecycle Nobody Explains
Every message you just sent follows an invisible lifecycle that breaks most first timers.
Send it. SQS stores it with a visibility timeout (default 30 seconds). Poll it. Process it. Delete it explicitly, or it reappears for the next consumer.
Miss the delete, and you get duplicates. Set visibility too low, and retries overlap into chaos. AWS Well Architected calls this out because one forgotten delete turns a queue into a memory leak.
What if your consumer crashes mid process? The message reverts to the queue automatically. No data loss. That's SQS quietly earning trust while your Lambda or ECS task restarts.
Dead Letter Queues: Your Debug Lifeline
Support tickets spike when queues fill with "poison messages" that no consumer can process.
Enter Dead Letter Queues (DLQ). Set max receives to 3. Fourth failure moves it to DLQ automatically. Your main queue stays clean.
In the console lab above, add a DLQ now. Edit queue. Dead letter queue section. Target another queue. Set receive limit to 2. Send a malformed JSON message. Watch it migrate after two polls.
Reality check: 80% of production SQS issues trace back to unmonitored DLQs. Check them daily. They surface the malformed payloads, bad IAM, and deserialization bugs before customers notice.
Standard vs FIFO: When Order Breaks You
Your q-labs queue used Standard. At scale, order means nothing. Messages might arrive shuffled. Throughput hits millions per second. Cost: fractions of a penny.
FIFO queues guarantee order and exactly once delivery. Use them for payment confirmations or inventory decrements. Limit: 300 TPS unless you pay for high throughput mode.
Question for you:
Does shuffled order break your app, or is eventual consistency fine? Most support workloads pick Standard and save the complexity. AWS flags FIFO in Well Architected only when sequencing is non negotiable.
Real Integrations Beyond the Console
SQS rarely runs solo. Lambda polls it natively. ECS tasks batch receive 10 at a time. Connect to EventBridge for fanout. All without custom polling loops.
Common trap:
Forgetting idempotency. Same message ID might hit your handler twice. Check message deduplication ID on receive. Delete only after your business logic commits.
Next time CloudWatch alarms on queue depth, you know the fix: Scale consumers, not producers. Add DLQ. Switch to long polling (20 seconds). Costs drop 40%. Reliability climbs.
Top comments (0)