Rebuild Website workflow (PrismJS/prism)

The Rebuild Website workflow from PrismJS/prism, explained and optimized by Latchkey.

What it does

This is the Rebuild Website workflow from the PrismJS/prism repository, a real project running GitHub Actions. It is shown here with attribution under its MIT license.

Below, Latchkey shows a faster, safer version produced by its optimization engine.

The workflow

name: Rebuild Website

on:
  push:
    branches:
      # FIXME: Use the main branch when v2 is out
      - v2

jobs:
  trigger-rebuild:
    runs-on: ubuntu-latest
    steps:
      - name: Trigger Netlify Build Hook
        run: curl -X POST -d "{}" "${{ secrets.WEBSITE_BUILD_HOOK_URL }}?trigger_title=The+Prism+code+has+been+updated"

The same workflow, on Latchkey

Removes redundant runs and caps runaway jobs. Added and changed lines are highlighted.

name: Rebuild Website
 
on:
  push:
    branches:
      # FIXME: Use the main branch when v2 is out
      - v2
 
concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true
 
jobs:
  trigger-rebuild:
    timeout-minutes: 30
    runs-on: latchkey-small
    steps:
      - name: Trigger Netlify Build Hook
        run: curl -X POST -d "{}" "${{ secrets.WEBSITE_BUILD_HOOK_URL }}?trigger_title=The+Prism+code+has+been+updated"
 

What changed

• Run on Latchkey managed runners with one line (runs-on), which apply the fixes below automatically and self-heal transient failures. This example uses latchkey-small; pick the runner size that fits the job.
• Cancel superseded runs when a branch or PR gets a newer push.
• Add a job timeout so a hung step cannot burn hours of runner time.

What Latchkey heals here

This workflow has steps that commonly fail on transient issues (network, registries, flaky browsers). On Latchkey managed runners they are detected, retried, and self-healed instead of failing your build:

• Network fetches

This workflow runs 1 job per trigger. On Latchkey the same minutes cost up to 58% less than GitHub-hosted, with zero queue time.