This guide shows how to deploy own Docker apps (with AdminForth as example) to Amazon EC2 instance with Docker and Terraform involving Docker self-hosted registry.

Needed resources:

• GitHub actions Free plan which includes 2000 minutes per month (1000 of 2-minute builds per month - more then enough for many projects, if you are not running tests etc). Extra builds would cost 0.008$ per minute.
• AWS account where we will auto-spawn EC2 instance. We will use t3a.small instance (2 vCPUs, 2GB RAM) which costs ~14$ per month in us-east-1 region (cheapest region). Also it will take $2 per month for EBS gp2 storage (20GB) for EC2 instance

This is it, registry will be auto-spawned on EC2 instance, so no extra costs for it. Also GitHub storage is not used, so no extra costs for it.

The setup has next features:

• Build process is done using IaaC approach with HashiCorp Terraform, so almoast no manual actions are needed from you. Every resource including EC2 server instance is described in code which is commited to repo so no manual clicks are needed.
• Docker build process is done on GitHub actions, so EC2 server is not overloaded
• Changes in infrastructure including changing server type, adding S3 Bucket, changing size of sever disk is also can be done by commiting code to repo.
• Docker images and cache are stored on EC2 server, so no extra costs for Docker registry are needed.
• Total build time for average commit to AdminForth app (with Vite rebuilds) is around 2 minutes.

Our framework has a CI pipeline that runs npm run build, publishes the package to NPM (npm publish), and creates a new release on GitHub. It also sends a notification about the release to a Slack webhook for our team.

Secrets for these services were stored in our CI’s built-in Vault (we are running a self-hosted Woodpecker CI).

Recently, while moving plugins to separate repositories, I decided to try Infisical for centralized secrets management instead of the internal CI Vault. Infisical provides a self-hosted open-source solution, has a well-organized UI, and offers better access control than our CI Vault. It was important to me that I could reuse secrets across different repositories without copying them every time I created a new plugin.

Here’s what I did:

I have a feeling that after first ~600 versions of Adminforth we faced all possible issues with manual versioning and release notes.

Manual versioning and CHANGELOG.md is unreliable as human beings are. It is pretty easy to forget it with relevant information, forget to include some changes, forget to push it to GitHub, push it at wrong time, and many more things.

That is why we decided to move the idea of generating versions, and GitHub releases from git commit messages using great tool called semantic-release.

In this post I will explain why we did a transition from manual releases to automatic, what profits we got from it, and also will show you simple example how to do it in your project!

Every reliable system requires a backup strategy.

If you have no own backup infrastructure, here can suggest a small docker container that will help you to backup your database to AWS Glacier.

Here is more advanced snippet to deploy AdminForth to Terraform.

Here Terraform state will be stored in the cloud, so you can run this deployment from any machine including stateless CI/CD.

We will use GitHub Actions as CI/CD, but you can use any other CI/CD, for example self-hosted free WoodpeckerCI.

Here is a row snippet to deploy AdminForth to Terraform.

Many developers today are using copilots to write code faster and relax their minds from a routine tasks.

But what about writing plain text? For example blogs and micro-blogs: sometimes you want to share your progress but you are lazy for typing. Then you can give a try to AI-assisted blogging. Our Open-Source AdminForth framework has couple of new AI-capable plugins to write text and generate images.

Couple of days ago we released a plugin which allows you to co-write texts and strings with the AI.

Today LLM is already a must tool to speed-up writing, brainstorming, or generating ideas.

Here is how it looks in action: