Deep Dive Into Step Functions in Relation To HPC
AWS Step Functions allows you to deploy and manage HPC tasks with a visual editor. Developers use the AWS workflow editor to build state machine diagrams and step functions, enabling them to share and modify HPC application's behaviour.
If you want to trigger processes or tasks automatically, make sure you configure AWS Step Functions based on your requirements or needs. In today’s article, we will discuss the benefits of Step Functions and their working mechanism within the HPC environment.
Benefits of Step Functions
There are many advantages of AWS Step Functions for high-performance computing applications. It is crucial to know Step Functions and their elements for the proper execution of HPC applications.
Step Functions allow you to create complex workflows within multiple services while mitigating the risk of higher operational overhead. That way, you can maintain minimal overhead for your HPC application.
Besides, developers use Step Functions to manage states between executions without setting up or utilizing databases or job queues. If you want to decouple your workflow logic, you can use AWS Step Functions to decrease the complexity of your HPC application. The purpose is to decouple your business logic from workflow logic.
Components of AWS Step Functions
There are three primary components of AWS Step Functions. These are state machines, states, and tasks. In this section, we will give you essential information on AWS Step Functions and their components based on the research of Clovertex Clouding Computing experts. Continue reading!
Step Functions’ primary component is known as the state machine. You can use this component to define your process flow and streamline your step function creation. Remember, State machines are based on JSON files. You can build state machines and run them through the AWS console or API for your HPC application.
It is often difficult to design these files due to their complexity. For instance, these files are more complex than JSON files when it comes to design. The reason is that developers use Amazon State Language specifications. The good news is that you can use a real-time graph within the console for proper setup.
It is critical to define different states within the state machine to run your HPC application accurately. According to Clovertex, states mean a task or service status. You can use these states as triggers for your HPC workflows.
For instance, you can start, pause, complete, and terminate tasks using states. There are various options that you can use for state configuration. These include choice state, fail or succeed state, pass state, wait state, parallel state, and task state.
Developers can also use Step Functions to define tasks within their state machines in a high-performance computing environment. According to Clovertex researchers, tasks are individual steps that guide you through the Steps Functions. Make sure you create an acidity or Lambda function during the task creation process.
Lambda allows you to run small chunks of code on an infrastructure that is not based on a server. You can use Lambda to perform individual operations. Likewise, you can use it as the backend for your HPC applications. You can write a Lambda function in various languages. Companies use Lambda functions on a pay-for-use basis.
Clovertex has experienced cloud computing and HPC professionals who can accurately use Step Functions to create manual and automated triggers for different tasks within your HPC application.
Our professionals can accurately create a step function by configuring a state machine. We follow a step-by-step approach to get the most out of Step Functions. Contact us today if you need assistance on running Step Functions for your HPC.