AWS Provisioning and Deployment with Linux EC2 instances using PowerShell

I didn’t expect to find myself needing to learn PowerShell for automation purposes, but I must admit I really like it. It seems sort of like an amalgam of Bash, Perl and Python. It’s an unexpectedly impressive creation from Microsoft. I’ve been using PowerShell on macOS but it can also be used easily on Linux, and Windows of course.

I created three simple PowerShell scripts for automated provisioning of Linux EC2 instances within AWS. Running these will provision an Amazon Linux 2 EC2 instance with SSH key pair and Security Group, with a webapp deployed thereon, plus an associated DNS record in Route 53.

You can find these scripts and related config here on my GitHub.

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How to use Ansible to provision an EC2 instance with an app running in a Docker container

I created this suite of Ansible playbooks to provision a basic AWS (Amazon Web Services) infrastructure on EC2 with a Staging instance, and to deploy a webapp on the Staging instance which runs in a Docker container, pulled from Docker Hub.

Firstly a Docker image is built locally and pushed to a private Docker Hub repository, then the EC2 SSH key and Security Groups are created, then a Staging instance is provisioned. Next, the Docker image is pulled on the Staging instance, then a Docker container is started from the image, with nginx set up on the Staging instance to proxy web requests to the container. Finally, a DNS entry is added for the Staging instance in Route 53.

This is a simple Ansible framework to serve as a basis for building Docker images for your webapp and deploying them as containers on Amazon EC2. It can be expanded in multiple ways, the most obvious being to add an auto-scaled Production environment with Docker containers and a load balancer. (For Ansible playbooks suitable for provisioning an auto-scaled Production environment, check out my previous article and associated files “How to use Ansible for automated AWS provisioning”.) More complex apps could be split across multiple Docker containers for handling front-end and back-end components, so this could also be added as needed.

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