Case Study and Industries Use-cases of Amazon SQS!
Harshita Kumari
DevOps Engineer | Terraform/RHCSA/AWS/Azure Certified | AWS,Docker, Ansible, Kubernetes ,Terraform ,Python ,Jenkins,
In this Blog we’re going to discuss about the SQS Service of AWS with its use cases
What is Amazon SQS?
Amazon Simple Queue Service (SQS) is a managed message queue service offered by Amazon Web Services (AWS). It provides an HTTP API over which applications can submit items into and read items out of a queue. The queue itself is fully managed by AWS, which makes SQS an easy solution for passing messages between different parts of software systems that run in the cloud.
How does 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.
How does SQS integrate with other AWS services?
Most interesting for Serverless developers is SQS‘s integration with Amazon Lambda: SQS can act as an AWS Lambda event source. When configured, every SQS message triggers a Lambda function run that processes a batch of SQS messages.
Another useful integration is with SNS. SQS also provides standard integrations for monitoring and debugging SQS queues using Amazon CloudWatch and AWS X-Ray.
Serverless developers can manually integrate an SQS queue with any other AWS service (or a third-party service) by writing code that uses the AWS SDK to submit messages to SQS and read them from there, or by using the SQS API directly.
Benefits of using SQS:
For Serverless developers, using SQS generally provides a wealth of benefits, which are given 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.
Key features of SQS:
SQS is a cloud service and can be used by any type of software, application, or other service. SQS works at its own independent service in the cloud. A software connects with SQS using a connection by passing the credentials and queue names. SQL also allows applications to create and delete custom queues.
- At-Least-Once Delivery :A message in the queue is delivered at least once. Message delivery is guaranteed, no message is lost.[Text Wrapping Break]
- Multiple components can work on a single queue: SQS uses a lock mechanism, if one component is using a message, it is made hidden to other components. Upon successful processing, message is deleted from the queue. If the message processing fails, it stays in the queue and is made visible to all the components. This feature is called Visibility Timeout.
- There are two types of queues: Standard and FIFO. In standard queue the messages are picked up randomly. It might not be in the order it entered the queue while FIFO queue uses first-in-first-out, it ensures the order.
- For the messages that cannot be processed are kept in dead-letter queue.
- Billing is done based on the number of requests to the queue. SQS is a good service to be used for applications to increase efficiency, reliability and performance.
Use cases of SQS :
The most common ways to use SQS, and of course other messaging systems, in cloud applications are:
- Decoupling microservices: In a microservice architecture, messages represent one of the easiest ways to set up communication between different parts of the system. If your microservices run in AWS, and especially if those are Serverless services, SQS is a great choice for that aspect of the communication.
- Sending tasks between different parts of your system: You don’t have to be running a microservices-oriented application to take advantage of SQS. You can also use it in any kind of application that needs to communicate tasks to other systems.
- Distributing workloads from a central node to worker nodes: You can frequently find messaging systems in the flows of distributed large workloads like map-reduce operations. For these kinds of operations, it’s essential to be able to maintain a queue of all the tasks that need to be processed, efficiently distribute the tasks between the machines or functions doing the work, and guarantee that every part of the work is only done once.
- Scheduling batch jobs: SQS is a great option for scheduling batch jobs for two reasons. First, it maintains a durable queue of all the scheduled jobs, which means you don’t need to keep track of the job status — you can rely on SQS to pass the jobs through and to handle any retries, should an execution fail and your batch system returns the message to the queue. Second, it integrates with AWS Lambda; if you’re using AWS Lambda to process the batch jobs, SQS automatically launches your Lambda functions once the data is available for them to process.
Case study of Amazon SQS Service :
EMS Delivers 500% ROI through IoT Capabilities Using AWS
- Environmental Monitoring Solutions (EMS) is based in Victoria, Australia. Launched 25 years ago, the company specializes in solutions that help petrol retailers gather and analyze data on the performance of their petrol stations. Its solutions provide remote monitoring and 24/7 support services — helping customers boost sales, reduce maintenance expense, and decrease the risk of accidents. Today, EMS operates with a team of 30 personnel.
Challenge : -
- EMS customers such as Viva Energy (Shell), PUMA Energy, BP, and 7-Eleven typically own and operate hundreds of petrol stations across Australia. The stations need to operate highly efficiently because profit margins are small. Yet, at the same time, they have to offer great customer experiences, ensure employee safety, and minimize their environmental impact.
- Sometimes accidents do occur, and a typical EMS customer is likely to incur annual costs of AU$15 million (US$12.13 million) for cleaning up underground petrol tank leaks or vehicle fuel tank contamination. To help customers maximize efficiencies while addressing the need for service excellence, safety, and environmental protection, EMS developed Fuelsuite, which enables customers to switch from legacy technologies that are largely manual and unify station management — significantly reducing costs. With Fuelsuite, customers can monitor inventories, deliveries, and prices. The solution also raises alarms in event of possible environmental incidents, such as underground tank overfills. After the successful launch of Fuelsuite, EMS focused on product development. It looked to connect sensors in the stations’ underground tanks and pumps and, regardless of the configurations of those sensors, collect all their data at 30-second intervals. The data would then be aggregated on a cloud-computing infrastructure and displayed via a web-enabled interface in Fuelsuite in near-real time.
Russell Dupuy, founder and managing director of EMS, says,
“Our job was to find an IT partner and cloud-computing provider that could help us re-engineer our Fuelsuite technology and deliver an innovative off-the-shelf product that was user-friendly and easily customizable.”
Why Amazon Web Services : -
EMS researched the market for cloud-computing providers, focusing specifically on providers of Internet of Things (IoT) technology. Through IoT, EMS would be able to collect all the sensor data and deliver it to the Fuelsuite interface. In 2015, when EMS first started looking at cloud providers and their IoT services, Dupuy found that Amazon Web Services (AWS) was way ahead of Microsoft Azure.
“From what I’d read, I was more confident in the AWS IoT roadmap, We were investing millions of dollars in this project, so I had to be sure of the provider we were going to work with.”-Dupuy
EMS then engaged with AWS partner network (APN) Advanced Consulting Partner DIUS, which organized a two-day workshop with key stakeholders to agree on a shared vision for Fuelsuite.
“The expertise that DiUS has in AWS and IoT gave us a lot of confidence,”.-Dupuy
Just as importantly, DiUS agreed to the plan of designing, supporting productization, and launching the IoT-enabled Fuelsuite solution for a major EMS customer retail network within 12 months. “DiUS showed that it was possible to meet our schedule by rolling out the platform at first with just enough AWS IoT capabilities for customers, and then extending those capabilities down the line.”
The Benefits : -
EMS, in partnership with DiUS, is now developing Fuelsuite further, adding new services for the fuel industry. It will also be launching the product internationally. Dupuy says, “An advantage of AWS is that machine learning, deep learning, and other new artificial intelligence services can easily be applied to a customer’s aggregated data that is collected through the Fuelsuite solution.”
THANKYOU for reading!