AWS Step Functions are built with state machines and tasks in mind. A workflow is a state machine. A task is a workflow state that represents a single unit of work performed by another AWS service. Each step in a workflow represents a state.
What is AWS?
AWS is an abbreviation for Amazon Web Services. It is a platform that provides cloud computing solutions that are flexible, dependable, scalable, simple to use, and cost-effective.
AWS provides you with a virtual environment in which you can load the software and services that your application requires.
Users can choose the operating system, programming language, web application platform, database, and other services users require from AWS.
In this blog, we’re going to guide you through AWS Step Functions
Table of Contents:
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What is AWS Step Functions?
AWS Step Functions enable you to design and implement the execution flow of AWS serverless modules in an application. This allows developers to concentrate solely on ensuring that each module performs its intended function, rather than worrying about connecting each module to others.
Step Functions is a workflow orchestrator that assists in the design and implementation of complex workflows. Step Functions coordinate between tasks when we need to build a workflow or have multiple tasks that need orchestration. This simplifies the development of multi-step systems.
Step Functions are based on two fundamental concepts: Tasks and State Machines.
Tasks perform all work in the state machine. A task completes work by executing an activity or an AWS Lambda function, or by passing parameters to API actions of other AWS services.
The Amazon States Language, which is based on JSON, is used to define a state machine. When an AWS Step Functions state machine is created, it connects the components and displays the developers’ system and how it is configured.
Why are AWS Step Functions Important?
You can quickly build and update apps by coordinating multiple AWS services into different serverless workflows. Furthermore, Step Functions allows you to both design and run workflows that combine various services, such as Amazon ECS and AWS Lambda, into feature-rich applications.
On each step, for example, you can call a Lambda function, but you can also wait for human interactions or external API input. As a result, Step Functions provides a valuable service. And, best of all, Step Functions are also serverless! This means on-demand pricing and low operational costs.
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Working Process of AWS Step Functions
AWS Step Functions is made up of the following major components:
State Machine:
As previously stated, the state machine is an essential component of the AWS Step Functions service. It defines state communication and how data is passed from one state to another.
A state machine is a type of technology known in computer science that can store various status values and update them based on inputs. AWS Step Functions expands on this idea by referring to an application workflow as a state machine. Using the Amazon States Language, developers can create a state machine in Step Functions with JSON files.
State:
A state is identified by its name, which can be any string but must be unique across the entire state machine. It performs the following functions:
- Work is performed in the state machine (a Task state)
- Selects one of several execution paths (a Choice state)
- Stop the workflow based on success or failure (a Fail or Succeed state)
- It simply converts its input to output or injects some fixed data (a Pass state)
- For a set time, pause the workflow (Wait state)
- Allows for a delay for a set amount of time or until a specific time/date (a Wait state)
- Proceed parallel execution branches (Parallel state)
- Execution should be repeated for each item of input (Map state)
The states you choose to include in your state machine, as well as the relationships between them, form the foundation of your Amazon Step Functions workflow.
Task State:
Within your state machine, a task state (also known as a task) is used to complete a single unit of work. Tasks can be used to invoke API actions from over 200 Amazon and AWS services. Your workflows can include two types of tasks:
Activity tasks allow you to connect a workflow step to a batch of code that is running somewhere else. An activity worker is an external batch of code that polls Amazon Step Functions for work, asynchronously completes the work using your code, and returns results. Activity tasks are common in adaptive workflows that require some human intervention (to verify a user account, for example).
Service tasks enable you to connect workflow steps to specific AWS services. Step Functions makes requests to other services, waits for the task to finish, and then moves on to the next step in the workflow. They are easily usable for automated tasks such as executing a Lambda function.
You’ll be able to visualize and validate your state machine as a series of steps in your AWS console. Step Functions logs the execution time of each step, any input and output, the number of retries, and any errors that occur. This information enables engineering teams to quickly determine which step or steps caused a workflow to fail and which steps preceded that failure
Integration of AWS Step Functions With other Amazon Services
Step Functions can be activated in four different ways:
- API Gateway
- S3 events
- CloudWatch Events
- Step Functions API – StartExecution
Step Functions are more than just Lambda Functions. It supports a variety of other Integration Patterns, including SQS, DynamoDB, SNS, ECS, and many others
The Amazon State Language allows you to call AWS services directly from your state definition. A step function can provide the following services directly:
- Task execution: Using Lambda function calls, AWS Batch jobs, or Amazon ECS tasks, you can run tasks synchronously or asynchronously.
- Database operations: Amazon DynamoDB can be used to insert or retrieve data.
- Messaging: You can use Amazon SNS to publish a topic or Amazon SQS to send a message.
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Advantages and disadvantages of AWS Step Functions
When deciding whether or not to use Step Functions in AWS, consider the following advantages and disadvantages. These can assist you in determining whether AWS Step Functions is appropriate for your organization’s situation and how much value it can provide.
- It manages multiple steps in your application’s workflow. Step Functions track which steps are being performed and which data is passed between steps as your workflow executes, allowing your application to pick up where it left off in the event of a network failure.
- Step Functions manages workflow steps, errors, and restarts to ensure that application tasks are completed properly. Fewer user requests fail as a result of improved application resilience.
- Engineers can spend less time writing integration code that defines the relationship between distributed application components when they use Amazon Step Functions. Step Functions coordinate parallel processes, exception handling, retries, and timeouts based on the business logic you stipulate.
- Step Functions separate business logic from the code that defines how your application works. This separation enables teams to quickly modify workflows, independently scale components, and reuse workflow code across multiple applications.
Above all, the main advantage of AWS Step Functions is that it removes the need to manually orchestrate your application components and define how they should interact. Engineers can thus spend less time writing workflow code and more time focusing on higher-value business logic.
Despite all of Step Functions’ powerful features, a few things are missing:
- Amazon Step Functions is a patented technology service that can only be used on AWS. If you later decide to migrate to a different cloud vendor, you will need to redesign the orchestration layer or completely replace it with an alternative offered by the new vendor.
- The maximum retention period for execution history logs is 90 days. It cannot be extended, which may preclude the use of Step Functions in businesses with longer retention needs.
- The Amazon States Language, which is used to configure step functions, is a complicated language. This language’s syntax is based on JSON. This means that the language is designed for machine readability rather than human readability. This language is difficult to learn, and you can only use it for AWS Step Functions because it is proprietary to AWS.
AWS Step Functions vs AWS Lambda
AWS Lambda and AWS Step Functions are two distinct serverless computing services offered by AWS that serve different purposes. AWS Lambda is a computing service that facilitates the execution of code in response to specific events, and it automates the management of compute resources.
Users only need to upload their code and specify the event source, and the rest is handled by AWS Lambda. Furthermore, the service supports multiple programming languages, which makes it flexible and user-friendly. On the other hand, AWS Step Functions is a workflow service that enables the coordination of distributed applications and microservices through visual workflows.
The service enables the construction of complex, multi-step workflows with built-in error handling, retry logic, and conditional branching. This is all achievable without the need for custom code.
In essence, AWS Lambda is tailored for executing particular functions in response to events while AWS Step Functions is more suited for creating and overseeing intricate workflows that involve multiple services and functions.
AWS Step Functions Examples
You can write a state machine that calls an Amazon Lambda function and waits for its output before moving on to the next task. In the following example, a Task state calls a Lambda function called my-function, which receives an event payload with three parameters. When the Lambda function succeeds and returns a result, the state changes to “NEXT STATE.”
...
"Invoke": {
"Type": "Task",
"Resource": "arn:aws:states:::lambda:invoke",
"Parameters": {
"FunctionName""arn:aws:lambda:us-east-2:123456789012:function:my-function:1",
"Payload": {
"max-depth": 10,
"current-depth": 0,
"error-rate": 0.05
}
},
"Next": "NEXT_STATE",
"TimeoutSeconds": 25
}
Best Practices of Step Functions
To avoid basic problems with AWS Step Functions, follow the best practices listed below:
- Resume process from the fail state: In a workflow, we sometimes need to resume the process from the fail state rather than starting over. This is not a built-in feature, but there is a workaround to accomplish this.
- Avoid infinite runs: State Machine can run indefinitely. It has a one-year maximum execution time. Furthermore, it includes the option to “Continue as new Execution.” This allows you to start a new execution before terminating the current one. This opens the door to it running indefinitely by accident. Monitoring execution metrics is a good way to identify and correct errors.
- Handle timeouts: The Amazon State Language does not set timeouts in state machine definitions by default. If a Lambda Function or Activity encounters a problem and continues to run without responding to Step Functions, it will wait for at least a year (max timeout).
AWS Step Functions Pricing
AWS Step Functions has a usage-based pricing model that varies depending on whether you are using a standard or express workflow. The system counts a state transition each time a workflow step is executed. The system then generates a billing price based on the total number of state transitions, which includes all state machines and retries.
Step Functions offers a free tier that includes 4,000 state transitions per month. If you exceed this limit, you will be charged at the official rate. The system tracks all charges daily and bills the total amount monthly.
There are two main pricing models available after the free tier:
Standard Workflows:
- The cost per million state transitions is $25. The duration of use and memory usage are charged separately.
- A maximum of one year, 2,000 executions per section, and 4,000 state transitions are permitted.
- Quick workflows
Pricing is divided into several parts:
- $1.00 for every million requests
- For the first 1,000 GB-hours, memory costs $0.00001667 per GB-second, then drops to $0.00000456 per GB-second after 4,000 GB-hours.
- Maximum execution time of 5 minutes, 100,000 executions per section and unlimited state transitions are all possible.
Conclusion
In this blog, we looked at the AWS fundamental concepts of Step Functions and how they work. Step Functions should be referred to as state-as-a-service. We would not be able to maintain the state of each execution with multiple lambda functions/activities without it. Using visual workflows, AWS Step Functions makes it simple to coordinate the components of distributed applications and microservices.
Building applications from individual components that each perform a distinct function allows you to quickly scale and change applications. Step Functions is a dependable way to coordinate components and step through your application’s functions