In this workshop, you will experiment how to run large-scale Monte Carlo simulations with the elastic infrastructure using AWS Batch. In the meantime, you will use AWS Lambda to run smaller workload requiring fast turnaround with the same container image used for AWS Batch. You can also choose to deploy the same infrastructure to a second region with the same procedure to meet compliance and resilience requirements.
You are familiar with AWS Batch and its benefits after finishing previous sections. Now we introduce AWS Lambda briefly as another compute service from AWS. You will also use Amazon Simple Storage Service (Amazon S3) for file storage and S3 Event Notifications to start simulation jobs when the input files are uploaded to the S3 input bucket.
AWS Lambda is a serverless, event-driven compute service that lets you run code for virtually any type of application or backend service without provisioning or managing servers. You can trigger Lambda from over 200 AWS services and software as a service (SaaS) applications, and only pay for what you use.
In addition to start running applications within seconds of an trigger event, there are several more benefits by choosing AWS Lambda. Some of them are listed below:
Amazon S3 is an object storage service offering industry-leading scalability, data availability, security, and performance. Customers of all sizes and industries can store and protect any amount of data for virtually any use case, such as data lakes, cloud-native applications, and mobile apps. With cost-effective storage classes and easy-to-use management features, you can optimize costs, organize data, and configure fine-tuned access controls to meet specific business, organizational, and compliance requirements.
Application operation workflow steps: