What is AWS Step Functions and How Does it Enable Event-driven Architectures?

Many organizations have historically relied on synchronous, request-response architectures. In these setups, different services and components are tightly coupled together. This is a natural way to approach things for many engineers, at least when tackling a new problem. The issue with request-response setups is that they are hard to manage, maintain, and extend, as applications grow increasingly complex. Any changes made to a single part of the application have the potential to affect many other components. In other words, it’s hard to update code related to one specific function without potentially breaking things somewhere else.

What’s more, request-response architectures don’t always scale or evolve well. Some components are better equipped to handle higher traffic than others. A spike in traffic can easily overwhelm one component of the workflow and bring down the entire application. Furthermore, adding a new service to the mix could mean refactoring a lot of existing code. Engineers from different departments may also have to work together constantly to ensure one group’s efforts don’t get in the way of another’s. Therefore, development cycles can be much slower for request-response architectures.

For these reasons, more businesses are adopting asynchronous, event-driven architectures. Event-driven architectures enable engineering teams to decouple interdependent services. Rather than have services communicate directly with one another, they can instead pass event information to event handlers that sit in the middle and trigger the next set of actions or wait for consumers to poll for updates.

AWS Tools for Event-Driven Architectures: A Closer Look

In the world of AWS, services like Amazon EventBridge, Amazon SNS, and Amazon SQS make decoupling monolithic applications easier. Amazon EventBridge can intercept events that happen across AWS environments and then pass that information on to other services. Amazon SNS is a messaging service that can receive event information and then publish it to many different subscribers simultaneously. Each one is designed to carry out a different set of actions. And Amazon SQS is a queuing service that sits between publishers and consumers, creating a buffer between services that allows for asynchronous execution.

Beyond these event management services, AWS also enables teams to execute Lambda functions based on different triggers. By using serverless functions, users don’t have to manage servers or provision capacity in advance. They can simply upload code and then let AWS handle the rest, scaling the capacity and throughput in the most cost-efficient manner

What makes AWS Lambda especially powerful is that teams can have Lambda functions trigger other Lambda functions, either synchronously or asynchronously. Combining multiple Lambda functions with services like Amazon EventBridge, Amazon SQS, or Amazon SNS is what starts to look like event-driven architecture in which every component can be managed independently, yet connected. The hard part is keeping everything organized. This is where AWS Step Functions comes in handy.

Organizing Complexity with AWS Step Functions

AWS Step Functions is a visual workflow tool that makes it easy to orchestrate microservices and coordinate activities amongst different AWS services. AWS Step Functions comes with a drag-and-drop user interface that allows engineers to visualize complex business logic. Teams can use conditional statements, process information in parallel, insert manual approvals, and more, all from within the visual interface. AWS Step Functions makes building event-driven architectures a breeze because it’s clear how asynchronous activities are orchestrated.

Of course, simply implementing AWS Step Functions isn’t a silver bullet for event-driven architectures. Engineers have to choose the right AWS services and make sure everything works together as intended. For those with limited cloud experience or exposure to services like AWS Lambda, working with an AWS expert like ClearScale can be valuable. We know when it makes sense to use AWS Step Functions and how to design the ideal workflow to solve key business challenges. Not only will we optimize your AWS Step Functions deployment, but we’ll also ensure every component involved performs at peak levels.

How Can ClearScale Help with AWS Step Functions?

ClearScale is an AWS Premier Tier Services Partner with deep knowledge of the AWS platform.  Since 2011, we’ve helped organizations build automated cloud architectures that address even the most complex business challenges. Our engineers have over 100 AWS technical certifications, and our group has earned 11 AWS competencies. That means we can design distributed applications with AWS Step Functions that cover a variety of use cases.

For example, in one engagement, we worked with an organization that facilitates connections between land conservancies and conscious communities. Our client wanted to upgrade its PostgreSQL database and data analytics pipeline to be able to handle more traffic. We used AWS Step Functions to orchestrate activities between three AWS services – Amazon S3, AWS Glue, and Amazon Athena – essential in the new and improved data pipeline. Our client now has a cost-effective and automated serverless architecture that handles data processing with ease.

In another project, we worked with a health-at-home solutions provider that wanted to automate a time-consuming process. Previously, the company’s employees were redacting PHI / PII from health records manually so that they could be shared with third parties for other purposes. We used AWS Step Functions to organize a series of AWS Lambda functions and machine learning solutions that performed the redaction automatically and with incredible precision. We estimate our work led to 3x efficiency improvement overall for the business.

We’ve also partnered with a company in the eCommerce space that wanted to spend less time managing and deploying infrastructure for machine learning purposes. Again, AWS Step Functions played a central role in our solution. We used the orchestration tool to automatically execute a series of steps related to ML model management, including data preparation, model training, and model deployment. Now, our client is able to deliver ML model updates to the market much faster than before.

Take Your AWS Deployment to the Next Level with ClearScale

Want to learn more about what it would look like to adopt event-driven architecture with AWS Step Functions and ClearScale? Check out ClearScale’s AWS Cloud DevOps services.

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