Not sure whether you should invest in AWS Step Functions for your business? Studying What Is AWS Step Function, its functions, and its uses in detail should make your decision easier.
In this AWS guide, we’ll shed some light on yet another valuable Amazon web service called AWS Step Functions. Some of the aspects we’ll cover include:
- What is AWS Step Function?
- How does AWS Step Functions Works?
- AWS Step Functions Use Cases
- Features of AWS Step Functions
- 1 What Is AWS Step Function?
- 2 How AWS Step Functions Works
- 3 AWS Step Functions Use Cases
- 4 Features of AWS Step Functions
- 5 AWS step function Pricing?
- 6 AWS step functions vs lambda
- 7 AWS step functions vs swf
- 8 Conclusion
What Is AWS Step Function?
Step Functions is a serverless computing service provided by AWS that involves a Finite State Machine Implementation.
The process is made of state machines or workflows, tasks, which are single units of work or individual states. You’ll need to understand the Finite State Machine (FSM) model here.
Finite State Machines are a method to model software system workflows. It performs the simple job of using given transitions and states to finish the tasks at hand.
State Machines refer to an abstract machine system that can be in a single state at once but can switch between states by a finite number.
This means it won’t allow infinity loops, thereby entirely eliminating an expensive error source.
You can use state machines in Step Functions in your serverless architecture to synchronize various AWS services to establish processes that address your business need in a well-defined manner.
But why exactly would a business owner want to do this? Coordinating different AWS services into various serverless workflows enables them to quickly develop and update apps.
Moreover, Step Functions also allow you to create and run workflows that coordinate several services such as AWS Lambda and Amazon ECS to produce applications loaded with features.
On each step, for instance, you may call a Lambda function, as well as wait for external API input or human interactions.
This is why many professionals view Steps as a mighty service. Not to forget the serverless feature of Step Functions, which means minimal operational overhead and on-demand pricing.
Now that you have a fair idea of AWS Step Functions, let’s find out how it works:
How AWS Step Functions Works
AWS Step Functions comprise three key components, namely, state machines, tasks, and states. Here is an overview of each component:
1. State Machine
- As the most important component of AWS Step Functions, the state machine outlines the process flow and directs the step function you develop.
- Made up of JSON files, state machines can be created and executed via the AWS Console or the API.
- Since these files require you to utilize Amazon State Language Specifications, they are more difficult to design than normal JSON files.
- Yet, a real-time graph in the console can be of great help when setting things up.
You define several states within a state machine. State denotes the status of a service or task.
Serving as workflow triggers, states are used to start, terminate, pause, or complete tasks.
The clearly defined options that you’re restricted to when configuring states include choice state, task state, succeed or fail rate, parallel state, pass state, and wait for state.
- Within your state machine, you also create tasks, which refer to the specific steps you need to complete in your step function.
- You may create tasks either as an activity or as a Lambda function. Lambda service allows you to execute small code blocks on serverless infrastructure.
- It can be used as a backend for serverless applications or to run individual operations. Charged on a pay-for-use basis, you can write Lambda functions in many languages.
- Activities, on the other hand, are processes or bits of code performed or hosted on non-Lambda resources or services.
- This may cover lengthy processes than manual tasks or what Lambda can deliver. You need to access the GetActivityTask API to use activities.
- Then, SendTaskFailure and SendTaskSuccess can be used to report the result.
AWS Step Functions Use Cases
1. Synchronizing Data
Suppose you host a static website using AWS S3 and distribute the content globally using AWS CloudFront.
To upload your website content, you may need two S3 buckets, one of which will be used for staging and testing and the other for production.
Your goal is to achieve a production bucket update through all changes in the staging bucket, without the need for creating a new bucket whenever a website update is required.
In this case, the Step Functions workflow delivers tasks in two independent, parallel loops, one of which copies objects from the source bucket to the destination bucket, leaving out any objects that already exist in the destination bucket.
The second loop, on the other hand, will delete the objects from the destination bucket that aren’t in the source bucket. An AWS Lambda functions set delivers the following individual steps:
- Validating input
- Getting lists of objects from the source bucket and destination bucket
- Delete or copy objects in batches
2. Automating Machine Learning Workflows
The Data Science SDK of AWS Step Functions works like an open-source library that allows you to develop workflows that help in processing.
And publishing machine learning models using Amazon Step Functions and AWS SageMaker.
Thanks to the Python API offered by SDK, everything from training, tuning, and transforming to modeling and configuring endpoints is covered in the machine learning pipeline.
These workflows can be managed and executed directly in Python.
3. Pulling Data from Images or PDFs for Processing
This use case has to with combining AWS Lambda, AWS Textract, and AWS Step Functions to scan an invoice that’s in PDF format with the goal to extract its data and text to process payments, for example.
AWS Textract scrutinizes the data and text from invoices and organizes an AWS Step Functions workflow via Lambda, SNS, and SQS for every job success.
The lambda function is the first step in the workflow, from where the results of successful results analysis are saved in S3.
This is followed by a second Lambda function that will process the assessed document to determine whether payment processing is possible for the invoice, updating DynamoDB with the information.
If it’s possible to process the payment, the workflow finds out whether it’s approved for payment.
If it’s approved for payment, another Lambda function will archive the processed invoice, thereby ending the workflow.
If it isn’t approved for payment, it will use SNS to notify a reviewer, who will then approve the invoice manually.
4. Building a Web-Based Application
Suppose you manage a banking system, in which a potential customer’s name and address are validated before a new account can be created for them.
Two lambda functions, namely CheckName and CheckAddress, simultaneously run as task states.
Upon completion of the two functions, the Approve application lambda function is executed by the workflow.
To handle errors from task states, you may define retry and catch clauses.
Since error handling is something that your workflow code can take, the Lambda functions can have less code and focus on business logic.
Features of AWS Step Functions
The following features of AWS Step Functions should help you understand its efficacy:
1. Integration of AWS Services
Using the service tasks in AWS Step Functions, you’re able to configure the workflow to integrate various other AWS services.
Examples of these services include AWS Lambda, Amazon SNS, Amazon EKS, Amazon Dynamo DB, Amazon Fargate, AWS ECS, and more. This feature makes AWS Step Functions reliable and flexible.
2. Built-In Error Handling
AWS Step Functions handles exceptions and errors automatically through its built-in retry and try/catch, no matter how much time the task takes for completion.
Timed-out or failed tasks can be automatically retried and different errors can be addressed in different ways. You may even fall back to the designated recovery code and cleanup to recover gracefully.
3. Automated Scaling
To address any changes in workloads, AWS Step Functions helps you run the application steps by automatically scaling the underlying compute and operations.
Its automated scaling ensures that the application workflow’s performance stays consistent despite the increase in the number of requests.
4. Component Reuse
AWS Step Functions helps coordinate microservices and your existing Lambda functions into robust applications, allowing you to rewire them quickly into new compositions.
Your workflow tasks can run on mobile devices, instances, functions, containers, and anywhere else. But take the time to understand the procedure of reusing existing application components.
5. Visual Monitoring
Opening an application is as easy as tapping a button, and then viewing the visual execution of the steps, so you can immediately confirm that the workflow is operating as expected and in order.
Errors are clearly pinpointed by the console, allowing you to immediately determine the root cause and conduct trouble-shooting.
AWS step function Pricing?
AWS step functions vs lambda
AWS step functions vs swf
To sum it up, it’s important to understand State Machines before jumping into What Is AWS Step Function.
State Machines are a solution to model your system by defining states and the transitions between them.
AWS Step Functions is an implementation of this Finite State Machine offered by Amazon as a serverless service.
After studying this guide, if you feel AWS Step Functions is the right solution for your business, go ahead and invest in it!
We hope you find this AWS step function tutorial helpful and that you learned something new.
I am an Amazon Web Services Professional, having more than 11 years of experience in AWS and other technologies. Extensively working in various AWS tools like S3, Lambda, API, Kinesis, Load Balancers, EKS, ECS and many more. Working as a Solution Architect and Technology Lead for Architecting and Implementing the same for different clients.