Aws SQS case study(what, how, why, who)

What is SQS?

• Amazon SQS is a highly available distributed queue system
• A queue is a temporary repository for messages awaiting for processing and acts as a buffer between the component producer and the consumer
• SQS is a message queue service used by distributed applications to exchange messages through a polling model, and can be used to decouple sending and receiving components.
• Amazon SQS
• fully managed and requires no administrative overhead and little configuration
• offers a reliable, highly-scalable, hosted queue for storing messages in transit between applications
• provides fault tolerant, loosely coupled, the flexibility of distributed components of applications to send & receive without requiring each component to be concurrently available
• helps build distributed application with decoupled components
• supports the HTTP over SSL (HTTPS) and Transport Layer Security (TLS) protocols for security
• SQS provides two types of Queues — Standard & FIFO

How SQS work?

SQS provides an API endpoint to submit messages and another endpoint to read messages from a queue. Each message can only be retrieved once, and you can have many clients submitting messages to and reading messages from a queue at the same time.

The messages that SQS handles can be unformatted strings, XML or JSON. Because SQS guarantees “exactly once” delivery, and because you can concurrently submit messages to and read messages from a given queue, SQS is a good option for integrating multiple independent systems.

You might well be asking: why use SQS if you can have an internal HTTP API for each service? While HTTP APIs are an accessible way to expose software systems to external users, it’s not the most efficient mechanism when it comes to integrating purely internal systems. A messaging queue is more lightweight. In particular, SQS also handles things like automated retries, preserving queue state across multiple availability zones in AWS, and keeping track of expiration timeouts on all messages.

Why use SQS(benefits)?

For Serverless developers, using SQS generally provides a wealth of benefits, which you can read about below.

Scalability Your SQS queues scale to the volume of messages you’re writing and reading. You don’t need to scale the queues; all the scaling and performance-at-scale aspects are taken care of by AWS.

Pay for what you use When using SQS, you only get charged for the messages you read and write (see the details in the Pricing section). There aren’t any recurring or base fees.

Ease of setup Since SQS is a managed service, so you don’t need to set up any infrastructure to start using SQS. You can simply use the API to read and write messages, or use the SQS <-> Lambda integration.

Options for Standard and FIFO queues When creating an SQS queue, you can choose between a standard queue and a FIFO queue out of the box. Both of these queue types can be useful for different purposes.

Automatic deduplication for FIFO queues Deduplication is important when using queues, and for FIFO queues SQS will do the work to remove any duplicate messages for you. This makes FIFO queues on SQS suitable for tasks where it’s critical to have each task done exactly once.

A separate queue for unprocessed messages This feature of SQS is useful for debugging. All messages that couldn’t be processed are sent into a “dead-letter” queue where you can inspect them. This queue has all the usual integrations enabled, so you can subscribe to it using an AWS Lambda event, for example, to send a notification when an item can’t be processed.

Who?

SQS Use Cases

Work Queues

• Decouple components of a distributed application that may not all process the same amount of work simultaneously.

Buffer and Batch Operations

• Add scalability and reliability to the architecture and smooth out temporary volume spikes without losing messages or increasing latency

Request Offloading

• Move slow operations off of interactive request paths by enqueueing the request.

Fan-out

• Combine SQS with SNS to send identical copies of a message to multiple queues in parallel for simultaneous processing.

Auto Scaling

• SQS queues can be used to determine the load on an application, and combined with Auto Scaling, the EC2 instances can be scaled in or out, depending on the volume of traffic

CASE STUDY(Red bus):

Red bus logo

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. To date, the company says they have sold over 30 million bus tickets and has more than 1750 bus operators using the software to manage their operations.

The Challenge

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. Over time, redBus realized that a better solution was imperative — a solution that offered scalability to handle the company’s processing fluctuations. redBus looked to Amazon Web Services (AWS) for a solution.

Why Amazon Web Services

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. These features included the ability to easily manage access to servers through security groups, the easy-to-use, self-service management console, the concept of Elastic IPs, and superior support.

The company has incorporated many of the AWS products into its solution, including Amazon Elastic Compute Cloud (Amazon EC2), Elastic Load Balancing, Amazon Relational Database Service (Amazon RDS), Amazon Simple Storage Service (Amazon S3), Amazon Elastic Block Store (Amazon EBS), and Amazon CloudWatch. Charan Padmaraju, Chief Technology Officer believes that “with features like Elastic Load Balancing and multiple availability zones, AWS provides the required infrastructure to build for redundancy and auto-failover. When you incorporate these in your system/application design, you can achieve high reliability and scale.”

The Benefits

Since migrating to AWS, redBus has seen measurable improvements in the bottom line. Padmaraju says, “By scaling up and down dynamically based on the load, we maintain performance as well as minimize cost. With the time savings that the IT and development staffs obtain from the AWS solution, AWS gives us an overall cost benefit of about 30–40%.” He adds, “By hosting at [the AWS Asia Pacific (Singapore) region], redBus.in gained significantly in terms of website performance by way of reduced latency (about 4x). This is a great advantage when the customers are from India.”

Of the many excellent characteristics of AWS, perhaps the most significant to redBus is the ability to “instantly replicate the whole setup on demand for testing by creating and destroying instances on demand for experimentation, thereby reducing the time to market.” Less time to market translates to increased profitability and success.

The travel agency anticipates expanding the AWS solution to include Amazon Simple Notification Service (Amazon SNS) and Amazon Simple Queue Service (Amazon SQS) for monitoring, alerts, and intercommunication. “Amazon SQS is an especially good solution for enabling messaging between external applications and our applications,” says Padmaraju.

Since joining forces with AWS, redBus has gained the freedom to experiment on new solutions and applications at minimal cost, increased the efficiency of its operations, and improved its profitability.