In this article I am going to tell What is Amazon SQS and its usecases So, let’s get Started
Amazon Simple Queue Service
Fully managed message queues for microservices, distributed systems, and serverless applications
Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you 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. Get started with SQS in minutes using the AWS console, Command Line Interface or SDK of your choice, and three simple commands.
SQS offers two types of message queues. Standard queues offer maximum throughput, best-effort ordering, and at-least-once delivery. SQS FIFO queues are designed to guarantee that messages are processed exactly once, in the exact order that they are sent.
Case studies of Companies which are using AWS SQS
redBus Case Study
2014
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.
How AWS resolves the challenge
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.”
BMW Case Study
2015
The BMW Group is using AWS for its new connected-car application that collects sensor data from BMW 7 Series cars to give drivers dynamically updated map information. BMW Group is one of the leading manufacturers of premium cars and mobility services in the world, with brands such as Rolls Royce, BMW, and Mini. BMW built its new car-as-a-sensor (CARASSO) service in only six months leveraging Amazon Simple Storage Service (Amazon S3), Amazon Simple Queue Service (Amazon SQS), Amazon DynamoDB, Amazon Relational Database Service (Amazon RDS), and AWS Elastic Beanstalk. By running on AWS, CARASSO can adapt to rapidly changing load requirements that can scale up and down by two orders of magnitude within 24 hours. By 2018 CARASSO is expected to process data collected by a fleet of 100,000 vehicles traveling more than eight billion kilometers.
That’s all from my side . Signing off …. 😊😊😊
