Recently Google introduced its serverless offering called Cloud Run which abstracts away all infrastructure management, so you can focus on building apps. By combining Cloud Run, Cloud Build and Cloud Source Repositories, we can build a simple, serverless CI/CD pipeline that automatically deploys an app whenever new commits are pushed. Basically you’ll get a Heroku-style interface for much less money and about 20 minutes of work.

If you’ve been following the Cryptocurrency world closely you’d be aware about the inherent risks and the possibility of losing all of your coins. Earlier this month I decided to move to a hardware based wallet for better peace of mind.

TLDR: Phinx has moved to the Cake Software Foundation.

Earlier this year I ran the 2017 Phinx product survey. The main goal behind this survey was to gauge public interest about a pro version and the features to work on next. I was fortunate enough to collect hundreds of responses. It turns out more than 80% of people use Phinx in the workplace with MySQL being the most popular database of choice. Whilst there was actually a decent amount of interest in a commercial version I’ve decided this is not the option I’m going to take.

In 2015 I ran a Phinx product survey to gauge interest from the community and decide what to work on next. It was a quiet success and I was fortunate enough to receive hundreds of responses. I’m running a similar survey again now and it would be awesome if you could spare 30 seconds of your time by helping to complete it.

Jenkins 2.0 is finally stable and has been promoted to the latest tag in the official Docker image. Developers can now take advantage of the new Pipelines feature and UI improvements. I’ve been a big fan of Jenkins since the Hudson days and use it on a daily basis - not only for continuous integration, but also for running cron jobs and miscellaneous tasks. However version 2 ships with a setup wizard that is enabled by default. This makes automated provisioning of the software more cumbersome. I’ll briefly demonstrate how I manage to work around this hurdle with a simple Docker image I’ve put together.