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Tag: docker (Page 1 of 3)

VSCode & PHP XDebug from Localhost, WSL2 and Docker containers

VSCode seems to be one of the up and coming IDEs over the last year. I personally switched from Jetbrains IDEs to VSCode fo most of my development work at some point in 2020.

Apparently up until now I have avoided running the PHP debugger Xdebug. I had to do a little search around to figure out the correct settings for my setup decided to write them down in this handy blog post.

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dockerit v0.0.5 (Easier than docker run)

dockerit is a small CLI tool that I have been working on during the start of 2021. It’s intended to make running one off commands and CLI tooling easier in docker. Rather than having to write a long string of parameters for docker run, instead you can just use dockerit. This applies to both CLI usage, but also via bash aliases.

You can download a build binary of dockerit from the Github releases page.

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PHP 7 composer docker image digest

At some point in the last weeks the composer docker image that can be found on docker hub switched from PHP7 to PHP8. Some projects, such as wikibase-docker, still require PHP7 for installation.

It looks like the composer image is not going to be providing an additional tag using a pre PHP 8 version, thus an old digest will be needed.

tldr; here is the digest that you want for composer with PHP7 (tag-details)

docker pull composer@sha256:d374b2e1f715621e9d9929575d6b35b11cf4a6dc237d4a08f2e6d1611f534675
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Go Docker SDK, Raw Terminal Ctrl+C handling

I spent my weekend in working on a new project called dockerit. It’s a simple wrapper around Docker written in Go and making use of the Docker SDK.

One of the biggest sticking points for me, being fairly new with the Golang world, was trying to pass stdin stdout and stderr between the container and host terminal correctly, while also having good performance and doing the expected things (like Ctrl+C to cancel).

The full code for setting up and, interacting with and removing my container can be found here. The main steps are broken down below.

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Creating a new replica after purging binlogs with bitnami mariadb docker images

I have been using the bitnami mariadb docker images and helmfiles for just over a year now in a personal project (wbstack). I have 1 master and 1 replica setup in a cluster serving all of my SQL needs. As the project grew disk space became pressing and from an early time I has to start automatically purging the bin logs setting expire_logs_days to 14. This meant that I could no longer easily scale up the cluster, as new replicas would not be able to entirely build themselves.

This blog post walks through the way that I ended up creating a new replica from my master after my replica corrupt itself and I was all out of binlogs. This directly relates to the Github issue on the bitnami docker images of https://github.com/bitnami/bitnami-docker-mariadb/issues/177

The walkthrough was performed on a Google Kubernetes Engine cluster using the 7.3.16 bitnami/mariadb helm charts which contain the 10.3.22-debian-10-r92 bitnami/mariadb docker image. So if you are using something newer expect some differences, but in principle it should all work the same.

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mediawiki-docker-dev v1 rewrite

Back in 2017 at the Wikimedia Hackathon, I played around with Docker and docker-compose in relation to MediaWiki and testing with multiple setups at once while developing, meaning multiple PHP versions, web servers and databases. My original slides can still be found here.

Since then mediawiki-docker-dev evolved into less of a testing system and more of a development environment, allowing the use of a master replica DB setup, easily swappable PHP versions, debugging and more. The project on GitHub currently has 40 stars, 38 forks and has seen 17 people contributing back.

Over the past couple of years, developer productivity and development environments have been a big discussion area. The Wikimedia technical conference in 2019 had the main topic of Developer Productivity. There have also been a few efforts in a few directions trying to figure out what is best for the majority of people. These include local-charts (Kubernetes based environment) and MediaWiki-Docker (simple docker-compose based environment).

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Reducing Java JVM memory usage in Containers and on Kubernetes

For a while I have been running a Wikibase query service update script for WBStack, which is a Java application on a Kubernetes cluster. Part of that journey has included the updater using all available memory, hitting into the kubernetes memory limit and being OOM killed. The title of the post is a little verbose, but I wanted to include all of the keywords that might help people find the answers to the memory issues that I was running into.

Before getting into my weeds, if you want the answers head straight to https://developers.redhat.com/blog/2017/04/04/openjdk-and-containers/

UPDATE: This blog post was written with Java 8. Java 10+ now automatically recognizes memory limits and enforces them. https://www.docker.com/blog/improved-docker-container-integration-with-java-10/

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Automatic cleanup of old gcloud container images

I have been using Google Cloud Build for a budget project for roughly a year now. Cloud Build stores built images in a storage bucket which you are of course billed for. Within the first weeks of using it I realized that I needed some automated way to cleanup unused and old images that were built there.

At the time I had a quick search around on the web for something already implemented that I could copy, but I came up blank, and decided putting my problem off would be the best solution. I filed issue number 6 for my project and left it for future me.

Now it’s time to finally close that issue, and I hope others might also find the small bash script useful.

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WBStack Infrastructure

WBStack currently runs on a Google Cloud Kubernetes cluster made up of 2 virtual machines, one e2-medium and one e2-standard-2. This adds up to a current total of 4 vCPUs and 12GB of memory. No Google specific services make up any part of the core platform at this stage meaning WBStack can run wherever there is a Kubernetes cluster with little to no modification.

A simplified overview of the internals can be seen in the diagram below where blue represents the Google provided services, with green representing everything running within the kubernetes cluster.

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