How to build a Serverless Workflow with AWS Step Functions (Part 1)?

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AWS Step Functions is a serverless orchestration solution that enables you to effortlessly coordinate several Lambda functions into customizable workflows that are simple to debug and modify.

To see the full implementation of How to Build a Serverless Workflow with AWS Step Functions, refer to part 2 of the blog here.

In this blog, we will cover:

  • What is AWS Step Functions?
  • What languages do AWS Step Functions use?
  • When to use AWS Step Functions?
  • How Step Functions are our friend?
  • Companies using AWS Step Functions
  • Conclusion

What is AWS Step Functions?

AWS Step Functions is a serverless function orchestrator that makes it easy to coordinate multiple AWS service components of distributed applications and microservices using visual workflows. It is a reliable way to coordinate components and step through the functions of your application.

When your distributed applications become complex, the complexity of managing them also grows. With its built-in operational controls, Step Functions manages sequencing, error handling, retry logic, and state, and provides a graphical console to arrange and visualize the components of your application as a series of steps. This makes it simple to build and run multi-step applications. It automatically triggers and tracks each step, and retries when there are errors, so your application executes in order.


Build-in Service Primitives: It includes pre-built states for your workflow that implement fundamental service primitives for you, allowing you to remove that functionality from your application. States can transfer data to other states and microservices, handle exceptions, set timeouts, make judgments, and run many pathways in parallel, among other things.

AWS service Integration: Configure your Step Functions workflow which includes computing services (AWS Lambda, Amazon ECS, Amazon EKS, and AWS Fargate), database services (Amazon DynamoDB), messaging services (Amazon SNS and Amazon SQS), data processing and analytics services (Amazon Athena, AWS Batch, AWS Glue, Amazon EMR, and AWS Glue DataBrew), machine learning services (Amazon SageMaker), and APIs created by Amazon API Gateway.

High-volume Orchestration: By adding express workflow you are able to build high-volume, short-duration workflows. Express Workflows can coordinate AWS Lambda function invocations, AWS IoT Rules Engine actions, and Amazon EventBridge events from over a hundred AWS third-party SaaS event sources. 

Workflow Configuration: AWS Step Functions, characterizes your workflows as state machines, which transform complex code into easy-to-understand statements and diagrams. It’s faster and easier to create apps and validate that they’re implementing your desired features.

State Management: No need to manage the state yourself with data stores or by building complex state management into all of your tasks. It keeps track of your application’s state during execution, including tracking which steps it’s in and saving data that moves between steps in your workflow.

Built-in error handling: Handles errors and exceptions with built-in try/catch and retry automatically You can automatically retry failed or timed-out tasks, respond differently to different types of errors and recover designated cleanup and recovery code.

Security: Step Functions supports VPC Endpoints (VPCE) using AWS PrivateLink. You can access it from VPC-enabled AWS Lambda functions and other AWS services.

Pay per use: You pay for each transition from one state to the next. Billing is metered by state transition, and you do not pay for idle time, regardless of how long each state persists (up to one year).

How do AWS Step Functions work?

AWS Step Functions

AWS Step Functions

Error handling

How do AWS Step Functions work?

Branching and human interaction patterns

How do AWS Step Functions work?

Chaining patterns

How do AWS Step Functions work?

Sage patterns

How do AWS Step Functions work?


Flexible recovery: Orchestrating a sequence of applications, managing their retries, and debugging any failures to make sure that your application executes in order and as expected.

Efficient workflow:  Build visual workflows that enable the fast translation of business requirements into technical requirements. You can build applications in a matter of minutes, and when needs change, you can swap or reorganize components without customizing any code.

Lesser Coding: Step Functions allows you to have many parallel executions of a workflow at the same time, making sure that performance scales with your application’s load. This removes extra code that may be repeated in your microservices and functions.

Use Cases

Transcode Media File: you can use Lambda to thumbnail images, transcode videos, index files, process logs, validate content, and aggregate and filter data in real time. 

Sequence batch processing: Step Functions can coordinate multiple AWS Batch jobs that take raw reads generated from sequencers and then process them in a pipeline to identify the variation in a sample compared to a reference. Before proceeding to the next step in the pipeline, it will wait for each job to finish.

AWS Step Functions use cases

Send messages from automatic workflow: Various internet sites and data repositories are monitored, and the Step Functions workflow manages a manual approval from an administrator before continuing on to ingest the data. Data is then sent to Amazon SQS. SQS expands the data, extracts the hashes and metadata about the hashes, performs any necessary deduplication, and publishes it to Amazon S3.

Publish events from serverless workflow: Incorporate Amazon SNS into your Step Functions workflows to get notifications about the workflow’s success or failure.

Coordinate container tasks in microservices and serverless applications: Can be used to draw conclusions about how to best process data. This Step Functions workflow will evaluate whether to perform post-processing of each file using AWS Lambda or AWS Fargate, according to the size and resolution of the image, in order to optimize runtime and costs.

Access databases from serverless workflow:  Enable Step Functions to coordinate all of the steps of a checkout process on an e-commerce site, for example. Step Functions can read and write from Amazon DynamoDB as needed to manage inventory records.

Sequence machine learning in workflows: You can use Step Functions to accelerate the delivery of secure, resilient machine learning applications, all while reducing the amount of code that you have to write and maintain.

AWS Step Functions use cases

Coordinate extract transform and load (ETL): You might consider looking at the relationships between online user engagement and sales revenue and prospects forecasted in the future. To blend and prepare data for analysis, you can utilize Step Functions to coordinate numerous AWS Glue processes.

AWS Step Functions use cases

What languages do AWS Step Functions use?

AWS Step Functions state machines are defined in JSON you may use an AWS SDK in the language of your choosing. AWS Lambda supports code written in Node.js (JavaScript), Python, Golang (Go), and C# (using the .NET Core runtime and other languages).

When to use AWS Step Functions?

If you are building an application where rapid iteration on state transitions is a priority, and if most or all of the actions in the application are performed using AWS Lambda functions, AWS Step Functions will be a great fit for your use case. It will cut down on the time you spend creating orchestration logic, allowing you to devote more time to your business logic.

How Step Functions is our friend?

AWS Step Functions offer a service that could be described as “state as a service.” It’s difficult to store and keep the state of execution up to date when you’re employing several Lambda Functions to finish a task. You’ll almost certainly use S3 or a database, making this a tedious and time-consuming operation. SFN will keep track of your status across all tasks and arrange them to run only when necessary and in the correct order.

You can set the timeout for the length of the activity or call the API using the HeartbeatSeconds option.

AWS Step Functions lets you create a retry strategy for each issue that your Lambda Functions might encounter.

Companies using Step Functions

Companies using AWS Step Functions


In this blog, we have discussed AWS Step functions, their features, benefits, use cases, etc. You can refer to our Part 2 of the blog to implement AWS Step Functions in business scenarios to handle the tracking of resolution of issues raised by the customers.  

We will discuss more such topics and other AWS services in our upcoming blog.

Meanwhile …

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