Developing distributed applications requires coordinating many components and dealing with latency and unreliability inherent in remote communication.
With Amazon Simple Workflow Service (Amazon SWF), you can develop asynchronous and distributed applications by providing a programming model and infrastructure for coordinating distributed components and maintaining their execution state in a reliable way. By relying on Amazon SWF, you are freed to focus on building the aspects of your application that differentiate it.
Components of a workflow
Components of a workflow The fundamental concept in Amazon SWF is the workflow. A workflow is a set of activities that carry out some objective, together with logic that coordinates the activities. For example, a workflow could receive a customer order and take whatever actions are necessary to fulfill the order.
Each workflow runs in a resource called a domain, which controls the workflow's scope. An AWS account can have multiple domains, each of which can contain multiple workflows, but workflows in different domains can't interact.
When designing an Amazon SWF workflow, you define each of the required activities. You then register each activity with Amazon SWF as an activity type. You will provide a name, version, and timeout values. For example, a customer may have an expectation that an order will ship within 24 hours.
In the process of carrying out the workflow, some activities may need to be performed more than once, perhaps with varying inputs. For example, in a customer-order workflow, you might have an activity that handles purchased items. If the customer purchases multiple items, then this activity would have to run multiple times. Amazon SWF has the concept of an activity task that represents one invocation of an activity. In our example, the processing of each item would be represented by a single activity task.
An activity worker is a program that receives activity tasks, performs them, and provides results. The task might actually be performed by a person. For example, a statistical analyst might receive sets of data, analyze the data, and then send back their analysis.
Activity tasks, and the activity workers that perform them, can run synchronously or asynchronously. Workers can run in one location or be distributed across multiple computers, potentially in different geographic regions. Different activity workers can be written in different programming languages and run on different operating systems. For example, one activity worker might be running on a server in Asia, while another might be running on a mobile device in North America.
The coordination logic in a workflow is contained in a software program called a decider. A decider schedules activity tasks, provides input to activity workers, processes events that arrive while the workflow is in progress, and ends (or closes) the workflow after the objective has been met.
The role of the Amazon SWF service is to function as a reliable central hub through which data is exchanged between the decider, the activity workers, and other relevant entities such as the person administering the workflow. Amazon SWF also maintains the state of each workflow execution, which saves your application from having to store the state in a durable way.
The decider directs the workflow by receiving decision tasks from Amazon SWF and responding back to Amazon SWF with decisions. A decision represents an action or set of actions, which are the next steps in the workflow. A typical decision would be to schedule an activity task. Decisions can also be used to delay tasks with timers, request cancellation of in-progress tasks, and to complete workflows.
The mechanism by which both the activity workers and the decider receive their tasks (activity tasks and decision tasks respectively) is by polling the Amazon SWF service.
Amazon SWF informs the decider of the state of the workflow by including, with each decision task, a copy of the current workflow execution history. The workflow execution history is composed of events, where an event represents a significant change in the state of the workflow execution. Examples of events include task completion, task time outs, or the expiration of a timer. The history is a complete, consistent, and authoritative record of the workflow's progress.
Amazon SWF access control uses AWS Identity and Access Management (IAM), so you can control access to AWS resources. For example, you can allow a user to access your account, but only to run certain workflows in a particular domain.
Running your workflow
The following provide an overview of the steps necessary to develop and run a workflow in Amazon SWF:
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Write activity workers to perform the processing steps in your workflow.
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Write a decider to handle the coordination logic of your workflow.
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Register your activities and workflow with Amazon SWF.
You can do this step programmatically or by using the AWS Management Console.
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Start your activity workers and decider.
These actors can run on any computing device that can access an Amazon SWF endpoint. For example, you could use compute instances in the cloud, such as Amazon Elastic Compute Cloud (Amazon EC2); servers in your data center; or even a mobile device, to host a decider or activity worker. Once started, the decider and activity workers should start polling Amazon SWF for tasks.
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Start one or more executions of your workflow.
You can start workflows programmatically or via the AWS Management Console.
Each execution runs independently and you can provide each with its own set of input data. When an execution is started, Amazon SWF schedules the initial decision task. In response, your decider begins generating decisions that initiate activity tasks. Execution continues until your decider makes a decision to close the execution.
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View workflow executions using the AWS Management Console.
You can filter and view complete details of running and completed executions. For example, you can select an open execution to see which tasks have been completed and what their results were.
Setting up your development environment
You have the option of developing for Amazon SWF in any of the
programming languages supported by AWS. For Java developers, the AWS Flow Framework is also available. For more information, see the AWS Flow Framework
To reduce latency and to store data in a location that meets your requirements, Amazon SWF provides endpoints in different Regions.
Each endpoint in Amazon SWF is completely independent. Any domains, workflows, and activities you have registered in one Region will not share data or attributes with those in another Region.
When you register an Amazon SWF domain, workflow, or activity, it exists only
within the Region you registered it in. For example, you could register a
domain named SWF-Flows-1 in two different Regions, but they will share no
data or attributes with each other — each acting as a completely independent
domain.
For a list of Amazon SWF endpoints, see Regions and Endpoints.
Develop with AWS SDKs
Amazon SWF is supported by the AWS SDKs for Java, .NET, Node.js, PHP, Python, and Ruby, providing a convenient way to use the Amazon SWF HTTP API in the programming language of your choice.
You can develop deciders, activity workers, or workflow starters using the API exposed by these libraries. And, you can use visibility operations through these libraries so you can develop your own Amazon SWF monitoring and reporting tools.
To download tools for developing and managing applications on AWS, including SDKs, go to the Developer Center
For detailed information about the Amazon SWF operations in each SDK, refer to the language-specific reference documentation for the SDK.
Consider the AWS Flow Framework
The AWS Flow Framework is an enhanced SDK for writing distributed, asynchronous programs that run as workflows on Amazon SWF. The framework is available for the Java programming language and provides classes for writing complex distributed programs.
With the AWS Flow Framework, you use preconfigured types to map the definition of your workflow
directly to methods in your program. The AWS Flow Framework supports standard object-oriented
concepts, such as exception-based error handling. Programs written with the AWS Flow Framework can
be created, run, and debugged entirely within your preferred editor or IDE. For more
information, see the AWS Flow Framework
