These are the materials for the AWS re:Invent 2017 workshop, LFS309 - High Throughput Genomics on AWS
During the hands-on sessions, workshop attendees will build the following typical workflow for genomics analysis.
Be sure to complete the prerequisites before attending the workshop.
For this workshop you will need:
|Amazon Virtual Private Cloud (VPC)||Yes||Maybe||All compute resources will launch in one of your VPCs in the us-west-2 region. You can either create a new VPC specifically for this workshop (recommended) or leverage one of your existing VPCs.|
|AWS CloudFormation||Yes||No||Used to execute CloudFormation templates to create the resources in other AWS services.|
|AWS Identity and Access Management (IAM)||Yes||Yes||IAM Roles will be created and used within the other services, such as Amazon EC2, AWS Batch, and AWS Lambda|
|Amazon Simple Storage Service (S3)||Yes||Yes||Bucket will be created for output of results.|
|AWS Batch||Yes||Yes||A new AWS Batch environment is created during this workshop. If you already have a Batch environment you can utilize it, but this will not be supported during the workshop|
|AWS Lambda||Yes||Yes||Lamdba functions will be created and executed within the workshop|
|AWS Step Functions||Yes||Yes||Step Functions will be created and executed during the workshop|
|Amazon Elastic Compute Cloud (EC2)||Yes||Yes||Instances will be launched by AWS Batch|
|Amazon EC2 Container Service (ECS)||Yes||Yes||AWS Batch relies on ECS to distribute the Docker containers on the instantiated EC2 instances|
|Amazon EC2 Container Registry (ECR)||Yes||Yes||We will be creating a ECR repository for hosting the Docker containers in this workshop|
If you are not able to have administrative access to the above services, please pair up with a table mate who can to accomplish the hands-on-labs.
A link to the slides will be shared at the workshop.
You will have the opportunity to implement a genomics workflow across three hands-on-labs. These are:
The first lab consists of creating a Docker container for an application, and the AWS Batch environment that will be used to perform the individual units of work. You will also run a example task on data to test out the environment.
The second lab builds on the second by creating the AWS Lambda and AWS Step Functions necessary to build out the full environment.
The last exercise summarizes the previous two labs, and has instructions on how to break down the AWS environment you created so that ongoing charges are not incurred.