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I'm an Engineer at The @ Company, building the @platform, a technology that is putting people in control of their data and removing the frictions and surveillance associated with today’s Internet. I was previously a Fellow at DXC Technology where I held various CTO roles. Before that I held CTO and Director of R&D roles at Cohesive Networks, UBS, Capital SCF and Credit Suisse, where I worked on app servers, compute grids, security, mobile, cloud, networking and containers.
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For a long while we ran The atPlatform on Ubuntu Linux, but we found that doing stuff with nodes on a large Docker Swarm spiked CPU usage for cloud-init. Every start or stop of a container was a change to networking, and every change to networking ca...
In this step-by-step guide I will walk you through all steps required to setup your own private dess using AWS.
Do you wish to store and share objects on Flutter without worrying about databases, infrastructure and other annoyances? What would these objects look like and how would you make them? The atPlatform already has you covered! Let’s take a deep dive in...
On running tests that are expected to fail
GitHub recently launched a beta for their new project boards, which provide a lot more flexibility than the old Kanban boards. I've been excited about the new functionality ever since I heard of the 'Memex' project. With the new boards comes a new A...
A few weeks ago Justin Garrison tweeted:
When I try to do something new I’ve been following the same pattern for a decade
- Do it in the GUI at least once
- Do it manually in the CLI
- Automate it with a script or declarative tool like Terraform
- (If needed) build a declarative API for others to use
This roughly echoes my own approach to automation, but I've been noticing recently that sometimes I'm going straight to step 3 without even trying 1 & 2.
An example would be multi architecture builds for Docker images. We've been doing x86_64 builds for a while, but we also wanted to do 32bit and 64bit Arm for Raspberry Pis, Apple M1, AWS Graviton etc.
We were already using a GitHub Action to create the x86_64 image, and to get that working from the boilerplate below needed just a couple of things:
tags: linename: Docker
on:
workflow_dispatch:
jobs:
docker:
runs-on: ubuntu-latest
steps:
-
name: Set up QEMU
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v2
with:
push: true
tags: accountname/imagename:tagname
-
name: Image digest
run: echo ${{ steps.docker_build.outputs.digest }}
To get the Action to make Arm images too all I needed to add was a platforms section after tags:
tags: |
accountname/imagename:tagname
accountname/imagename:latest
accountname/imagename:GHA${{ github.run_number }}
platforms: |
linux/amd64
linux/arm/v7
linux/arm64/v8
You'll see that I also added some extra stuff to the tags there to get :latest and a tag associated with the Action run number.
And that's all that was needed. Without ever trying to create a multi-arch image manually, I pressed the run button and it made me images for all 3 architectures. I can't actually imagine how doing it manually would be any easier - even for one iteration never mind for a repeatable system.
NB: I'm using on: workflow_dispatch: here whilst I test the Action, but soon enough it will be plumbed into the pipeline and running without human touch.
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