Talking querying with AWS SQS

Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables the user to decouple and scale microservices, distributed systems, and serverless applications. SQS eliminates the complexity and overhead associated with managing and operating message oriented middleware, and empowers developers to focus on differentiating work. Using SQS, you can send, store, and receive messages between software components at any volume, without losing messages or requiring other services to be available.

Amazon SQS allows us to store messages that are in transit from one computer to the other.

One might wonder that why we would be using such a service.

For example, let’s say you have a service where people upload photos from their mobile devices. Once the photos are uploaded your service needs to do a bunch of processing of the photos, e.g. scaling them to different sizes, applying different filters, extracting metadata, etc.

One way to accomplish this would be to post a message to an SQS queue (or perhaps multiple messages to multiple queues, depending on how you architect it). The message describe work that needs to be performed on the newly uploaded image file. Once the message has been written to SQS, your application can return a success to the user because you know that you have the image file and you have scheduled the processing.

In the background, you can have servers reading messages from SQS and performing the work specified in the messages. If one of those servers dies another one will pick up the message and perform the work. SQS guarantees that a message will be delivered eventually so you can be confident that the work will eventually get done.


AWS manages all in progress operations and underlying infrastructure required to produce an extremely accessible and scalable message queuing service. With AWS SQS, there’s no direct value, no ought to acquire, install, and assemble messaging package, and no long build-out and maintenance of supporting infrastructure.

Use AWS SQS to transmit any volume of data, at any level of output, while not losing messages or requiring alternative services to be accessible. Amazon SQS helps you to decouple application parts in order that they run and fail severally, increasing the fault tolerance of the system.

You can use Amazon SQS to exchange sensitive data between applications using server-side secret writing (SSE) to inscribe every message body. The AWS SQS compass point integration with KMS permits you to centrally manage the keys that defend SQS messages together with keys that defend your alternative AWS resources.

AWS SQS leverages the AWS cloud to dynamically scale supported demand. Amazon SQS scales elastically together with your application. Therefore, you don’t have to worry regarding capability designing and pre-provisioning.

Let’s take a case study now.

The Redbus Story

Redbus is an Indian travel agency that specializes in bus travel throughout India by selling bus tickets throughout the country. Tickets are purchased through the company’s Website or through the Web services of its agents and partners.

The company also offers software, on a Software as a Service (SaaS) basis, which gives bus operators the option of handling their own ticketing and managing their own inventories.

The company previously ran its operations from a traditional data center by purchasing and renting its systems and infrastructure. In addition to the expense, several logistical problems evolved from this arrangement. The biggest problem was that the infrastructure could not effectively handle processing fluctuations, which had a negative impact on productivity. Additionally, the procurement of servers or upgrading the server configuration was an extremely time-consuming endeavor.

After testing the AWS solution on a small application for several months, the travel agency determined that it was very workable and convenient. Although redBus was quite enthusiastic about the on-demand instances and variety of instance types, several other features cemented the company’s decision to migrate completely to AWS.

Benefits of AWS

  • Reduced costs by up to 40%
  • Reduced website latency by 4x
  • Able to instantly replicate test environments, which in turn reduces time to market

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