What does this AWS Solutions Implementation do?

The Scale-Out Computing on AWS solution helps customers easily deploy and operate a multiuser environment for computationally intensive workflows such as Computer-Aided Engineering (CAE). The solution features a large selection of compute resources, a fast network backbone, unlimited storage, and budget and cost management directly integrated within AWS. This solution deploys a user interface (UI) with cloud workstations, file management, and automation tools that enable you to create your own queues, scheduler resources, Amazon Machine Images (AMIs), and management functions for user and group permissions.

AWS Solutions Implementation overview

The diagram below presents the architecture you can automatically deploy using the solution's implementation guide and accompanying AWS CloudFormation template.

Scale-Out Computing on AWS | Architecture Diagram
 Click to enlarge

Scale-Out Computing on AWS architecture

At its core, this solution implements a scheduler Amazon Elastic Compute Cloud (Amazon EC2) instance, which leverages AWS CloudFormation and Amazon EC2 Auto Scaling to automatically provision the resources necessary to execute cluster user tasks, such as scale-out compute jobs and remote visualization sessions.

This solution also deploys Amazon Elastic File System (Amazon EFS) for persistent storage; AWS Lambda functions to verify the required prerequisites and create a default signed certificate for an Application Load Balancer (ALB) to manage access to Desktop Cloud Visualization (DCV) workstation sessions; an Amazon Elasticsearch Service (Amazon ES) cluster to store job and host information; and AWS Secrets Manager to store the solution configuration files. The solution also leverages AWS Identity and Access Management (IAM) roles to enforce least privileged access.

Scale-Out Computing on AWS

Version 2.5.0
Last updated: 07/2020
Author: AWS

Estimated deployment time: 35 min

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User Interface

Scale-Out Computing on AWS deploys and sets up an example UI with a common set of APIs that the administrator and users can use to interact with their Amazon EC2 cluster.

Real Time Analytics

Schedulers and application logs are ingested in real-time and stored in the data lake for further processing.

Pre- and Post-Processing in the Cloud

The solution leverages Desktop Cloud Visualization (DCV) graphical sessions to enable users to easily access the cluster to perform any pre- and post-processing visualization actions.

Custom Code and Automation

The solution is deployed with a collection of scripts that are customizable and can be extended to help users collect data and execute common cluster tasks.
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