Optimize Tailscale workflows: caching, parallelization, fix broken dispatch chain - #2
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…URLs - Rename workflow files to match dispatch URLs (fixes broken cross-workflow chain) - Cache Tailscale MSI with actions/cache@v4 (skip ~50MB download on cache hit) - Cache pip packages (skip re-download of pyautogui, pynput, pillow) - Run pip install in parallel with Tailscale install via background process - Remove redundant --force-reinstall and pip upgrade (saves ~15-30s) - Merge 'Decide runtime' into the main install step (reduce step overhead) - Reduce STOP cooldown heartbeat frequency (5 min intervals vs 1 min) Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
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Summary
The three Tailscale workflow files had broken cross-workflow dispatch (filenames didn't match the dispatch URLs) and several speed bottlenecks. This PR fixes the chaining and cuts setup time by ~30-60s per run.
Bug fix
Workflow dispatch URLs referenced
workflow-1.yml/workflow-2.yml/workflow-stop.yml, but actual filenames wereRDP + Tailscale (Workflow 1).yml, etc. Renamed files to match, fixing the chain: WF1 → WF2 → STOP → WF1.Speed optimizations
actions/cache@v4for Tailscale MSI (~50MB)actions/cache@v4for pip packages--force-reinstall+pip install --upgrade pipStart-Processbackground while Tailscale installs in foregroundParallelization pattern (WF1 & WF2)
Link to Devin session: https://app.devin.ai/sessions/2a948bbba61047bf9fff01738d133631
Requested by: @mohammad1390555