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Office Tunnel Memory Footprint Note

docs/agents/office-tunnel-memory-note.md

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Office Tunnel Memory Footprint Note

During the ARM Desktop audit on 2026-05-03, run_tunnel.py was the clearest near-future memory optimization candidate. The process held roughly 573 MiB PSS while the main UI process held roughly 706 MiB PSS, even though the tunnel should mostly be a lightweight network edge.

Observed Shape

  • run_tunnel.py imports enough of the framework stack to pull in heavy provider and API dependencies.
  • The tunnel stays resident for the life of the container, so every eagerly imported module becomes steady-state memory.
  • The Desktop/Xpra service itself was not the largest outlier; the always-on tunnel process was.

Future Work

  • Split tunnel startup into a small import surface that only loads routing, auth, and socket plumbing required for health and proxy operation.
  • Lazy-import provider/framework modules only when a tunnel request truly needs them.
  • Review any ApiHandler or helper imports used by the tunnel path and replace broad framework imports with narrower functions.
  • Measure with smem -P run_tunnel.py, /proc/<pid>/smaps_rollup, and before/after cold-start RSS/PSS on ARM64.

Success Signal

The tunnel process should remain useful as an always-on edge while dropping its idle PSS substantially below the main UI process. A good first target is under 250 MiB PSS on ARM64 without changing tunnel behavior.