github actions

Calling GitHub CI from a Wikimedia GitLab repo

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I want to spend some more time developing a-wikimedia-cli (previosuly called mwcli), expanding what it can do, and adding integration tests for more of its functionality along the way. Having tests is useful, but having to wait for them every time you change something makes that slightly less appealing. Especially when your development system seems to be intense bursts of work and branches on the odd evening, or odd weekend, and not much development the rest of the time.

Some of the more involved tests create MediaWiki environments, start databases, install things, turn them off, turn them back on again and check that the CLI has done what it was supposed to. These have been running using Docker-in-Docker (or dind for short) on Wikimedia Cloud VPS machines for some time now, alongside the other checks and builds managed by Wikimedia GitLab. However the are only 2 small workers in the pool for the Docker-in-Docker tests, which are limited to 4 simultaneous jobs due to CPU and RAM constraints. not to mention it’s a waste leaving them on most of the time…

Meanwhile, the project also has a repository on GitHub which is mirrored to from GitLab, where GitHub Actions has machines quite capable of running these tests.

I have thought about moving entirely over to GitHub to solve this problem before, and have spun up forks there with CI before to make sure integration style tests pass before promoting them into branches in GitLab. However I never made a complete move. I have also dabbled with doing cross repo CI before for this setup, however it often ended in a disappointing mess.

However, maybe this time it will work *wink wink*…

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Developer previews with AWS, Terraform and GitHub Actions

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As a developer, one of the most critical aspects of your workflow is the ability to test and preview your code changes before deploying them to production. This is where developer previews come in.

This post will outline how to create your own simple developer preview system, using Github Actions for building, AWS S3 for hosting, and Terraform to provision it all. Giving you more control, and a lower cost.

Shout out to Pedro Brandão from Significa whose post I read as inspiration for this setup.

What are Developer Previews?

Developer previews, also known as feature branches or pull request previews, allow developers to create isolated environments to test their changes without impacting the main production environment. It enables teams to collaborate, review, and validate code before merging it into the main branch. With developer previews, you can catch bugs, validate new features, and gather feedback early in the development process, ensuring a smoother deployment to production.

Existing services

Many dedicated platforms exist that offer developer preview as a service. These platforms provide a streamlined solution for creating and managing isolated environments for testing code changes. Examples of such services include Netlify’s Deploy Previews, Vercel’s Preview Deployments, and Heroku Review Apps. These platforms integrate seamlessly with popular version control systems and automatically deploy feature branches or pull requests, allowing developers to easily preview their changes. By leveraging these dev-preview services, developers can simplify the process of creating and managing preview environments, enabling faster iteration and effective collaboration within development teams.

However, all these services have a cost, which will always be higher than the do-it-yourself approach.

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Twitter bot powered by Github Actions (WikidataMeter)

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Recently 2 new Twitter bots appeared in my feed, fullyjabbed & fullyjabbedUK, created by iamdanw and powered entirely by Github Actions (code).

I have been thinking about writing a Twitter bot for some time and decided to copy this pattern running a cron based Twitter bot on Github Actions, with an added bit of free persistence using jsonstorage.net.

This post if my quick walkthrough of my new bot, WikidataMeter, what it does and how it works. You can find the code version when writing this blog post here, and the current version here.

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