How to use GitHub Actions and AWS CodeDeploy for automated CI/CD builds and deployment


I recently migrated a client to a new AWS-based infrastructure, fully automated and managed via IaC (primarily Packer, Ansible and Terraform). However, a somewhat clunky old build/deploy system was still being used, so it was also time to migrate that to a new automated CI/CD (continuous integration/continuous delivery) system for builds and deployments. Keeping costs as low as possible was a priority, so I ruled out Jenkins since that would have cost money to maintain an additional instance for extended periods of time.

Since GitHub was already in use, GitHub Actions was an obvious choice because the virtual instances (known as “runners”) used for code builds only exist for as long as necessary to run all the build commands. Costs are therefore kept as low as possible. Since the infrastructure was already running on Amazon Web Services, AWS CodeDeploy made sense as an integrated solution for deploying code. The challenge therefore was to get the builds working on GitHub Actions, then to connect GitHub Actions to AWS CodeDeploy for full CI/CD deployments.

This simple diagram shows the desired CI/CD architecture with GitHub Actions and AWS CodeDeploy:

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How to set up a Kubernetes cluster with minikube and then with Amazon EKS

Purpose of this tutorial project

Our goal is to create a Kubernetes cluster serving the output of simple-webapp via nginx. simple-webapp is a simple Python app I wrote for these kinds of projects, which outputs a basic web page as proof of concept. In a real production environment, this would be a full-blown web application of some kind.

The Kubernetes cluster will consist of the following:

  • Two cluster Nodes.
  • A simple-webapp Deployment consisting of four Pods, each running the simple-webapp container, exposed internally to nginx via a ClusterIP Service.
  • An nginx Deployment consisting of four Pods, each running an nginx container with a modified nginx.conf file made available via a ConfigMap which allows nginx to reverse-proxy traffic to the simple-webapp service, exposed externally via a LoadBalancer Service.
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How to migrate an application to AWS with auto-scaled EC2 instances

For entrepreneurs, startups, and established companies trying out new projects, there hopefully comes a time when interest in the app increases such that incoming traffic levels start to rise significantly. This will likely necessitate various improvements to the infrastructure running the application so that it’s more robust, reliable and scalable.

The application may previously have been running on a cheap hosted server on a service like DigitalOcean, Linode or OVHcloud, or possibly even a single EC2 (Elastic Compute Cloud) instance on AWS (Amazon Web Services), and the desired solution would now be to move the application to a dynamically auto-scaled EC2 environment so that it can handle the increasing traffic without resource problems and site downtime.

In order to achieve this, it will also be necessary to set up the database on AWS, and the most realistic solution for this is to use Amazon’s RDS (Relational Database Service). I’ve recently covered this process in my article Migrating a MySQL database to AWS (with specific focus on RDS). You’ll also need to set up a load balancer, most likely an ELB (Elastic Load Balancer), to balance the incoming traffic across the auto-scaled EC2 application instances. I’ve recently covered this topic also, in my article Choosing and setting up a load balancer in AWS. So have a read through both of those articles to begin with, and below I’ll cover the rest of the process, i.e. auto-scaling the application instances on EC2.

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How to choose and set up a load balancer in AWS

When you want to run your web application on more than one EC2 instance for scaling and redundancy purposes, you will probably require some form of load balancer to distribute incoming requests evenly across the instances. There are various possible solutions for this.

One option is to launch another EC2 instance and install a load balancer on it yourself. There are quite a few open source load balancing options, though I would tend to recommend HAProxy as it’s fast, efficient, secure, and very flexible. This option involves setting up your Linux instance and installing the software you need yourself, then configuring your chosen load balancer and installing your SSL certificates, etc. Additionally you would need to estimate the necessary instance size to run the load balancing software without getting overloaded and slowing the site down (bearing in mind that SSL termination can be particularly CPU-intensive), then monitoring it accordingly.

Unless there’s a particular reason to take the approach of installing a load balancer on an EC2 instance, a simpler and more effective option – especially for companies taking their first steps into scaling multiple instances for their application – is likely to be Amazon’s own ELB (Elastic Load Balancer). This doesn’t require an EC2 instance with Linux setup, software installation and configuration, etc. It provides a simple interface with easy SSL termination and it will scale itself automatically as needed, so there is little required in the way of planning and monitoring.

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How to create a Slack notification from a CloudWatch alarm for an SQS queue, via SNS and Lambda

This article describes the process of creating a Slack notification from a CloudWatch alarm generated from an undesirable state in an SQS (Simple Queue Service) queue, via SNS (Simple Notification Service) and Lambda.

You can of course modify any of these to suit your differing requirements. For example, the source could be a different SQS state, or the source could be some other AWS service rather than SQS, or you may want to send the notification to somewhere other than Slack (in which case a different Lambda function may be required), etc.

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