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Collection of workshops to demonstrate best practices in using Amazon EC2 Spot Instances. https://aws.amazon.com/ec2/spot/

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Ec2 Spot Workshop - running-amazon-ec2-workloads-at-scale

An AWS CloudFormation stack, which will include:
    An Amazon Virtual Private Cloud (Amazon VPC) with subnets in two Availability Zones
    An AWS Cloud9 environment
    Supporting IAM policies and roles
    Supporting security groups
    An Amazon EFS file system
    An Amazon S3 bucket to use with AWS CodeDeploy
An Amazon EC2 launch template
An Amazon RDS database instance
An Application Load Balancer (ALB) with a listener and target group
An Amazon EC2 Auto Scaling group, with:
    A scheduled scaling action
    A dynamic scaling policy
An AWS CodeDeploy application deployment
An AWS Systems Manager run command to emulate load on the service

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Collection of workshops to demonstrate best practices in using Amazon EC2 Spot Instances. https://aws.amazon.com/ec2/spot/

Website for this workshops is available at https://ec2spotworkshops.com

Building the Workshop site

The content of the workshops is built using hugo.

Local Build

To build the content

  • clone this repository
  • install hugo
  • The project uses hugo learn template as a git submodule. To update the content, execute the following code
pushd themes/learn
git submodule init
git submodule update --checkout --recursive
popd
hugo serve -D

Containerized Development

The image can also serve as a development enviornment using docker-compose. The following command will spin up a container exposing the website at localhost:1313 and mount config.toml and the directories ./content, ./layouts and ./static, so that local changes will automatically be picked up by the development container.

$ docker-compose up -d  ## To see the logs just drop '-d'
Starting ec2-spot-workshops_hugo_1 ... done

License

This library is licensed under the Amazon Software License.

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Collection of workshops to demonstrate best practices in using Amazon EC2 Spot Instances. https://aws.amazon.com/ec2/spot/

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  • Python 54.0%
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