155c5471b7
The §11.6 M4 byte quota mixed two incompatible byte measures: `used` came from Postgres as `octet_length(value::text)` (jsonb CANONICAL text — whitespace after `:` and `,`, keys normalized), while `old_len`/`new_len` were computed in Rust with `serde_json::to_vec` (COMPACT, no spaces). The projection `used - old_len + new_len` therefore subtracted and added a *smaller* measure than what is actually stored, so a group could be admitted over its ceiling — the cap drifted permissive. The two forms are not reconcilable in Rust (jsonb also reorders/dedups keys), so the projection has to be measured by Postgres. Add `projected_total_bytes` to `GroupKvRepo` (keyed by collection+key) and `GroupDocsRepo` (keyed by the replaced doc id, `None` on create). Each computes `SUM(canonical) - existing_row(canonical) + new_value(canonical)` in ONE query, binding the new value as compact TEXT and re-parsing it through `::jsonb::text` so PG measures it in exactly the form it stores. All three terms now share one metric. The services call it instead of the mixed Rust math; the near-cap fast-path (`rows_after * max_value_bytes <= ceiling` → skip the SUM) is kept, so the common case still does no extra work. The docs `update` path no longer needs its old-doc fetch (the subtraction happens in SQL), removing a read. The in-memory test repos implement the same projection with their own (compact) metric, so the quota unit tests keep their exact byte arithmetic. No schema change. Note: the check-then-write TOCTOU (concurrent writers can each pass and collectively overshoot) is NOT addressed here — it needs a transaction spanning the check and the write, the same missing infrastructure as the transactional outbox. Tracked separately. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
PiCloud
A lightweight, self-hosted, event-driven serverless compute platform. Upload a Rhai script, get an HTTP endpoint. Designed to run on a single modest server with no idle CPU cost, and to scale out to a small cluster when you need it.
Status: Phase 1 — MVP scaffolding in progress.
The authoritative design lives in
serverless_cloud_blueprint.md.
Why
Existing serverless platforms are either cloud-locked, heavyweight, or both. PiCloud aims for the opposite end of the spectrum: one binary, one database, one reverse proxy — running on hardware you already own.
Architecture (one paragraph)
PiCloud splits into three logical services — manager (control plane: scripts, schedules, dashboard), orchestrator (per-node event ingress and dispatch), and executor (per-node Rhai sandbox) — each backed by a *-core Rust library. In MVP they run in a single process; in cluster mode they run as three binaries with one manager and one orchestrator + executor per node. Caddy fronts everything; PostgreSQL is the single source of truth.
See CLAUDE.md for working notes and serverless_cloud_blueprint.md for the full design.
Quick Start
Coming as scaffolding lands. For now:
# Rust toolchain (pinned via rust-toolchain.toml)
cargo check --workspace
# Run the all-in-one MVP binary (once main.rs is wired up)
cargo run -p picloud
Repository Layout
crates/
shared/ cross-cutting types
executor-core/ Rhai engine + sandbox
orchestrator-core/ event ingress, dispatch
manager-core/ control plane
picloud/ MVP all-in-one binary
picloud-{manager,orchestrator,executor}/ cluster-mode binaries (skeleton)
dashboard/ SvelteKit
caddy/ Caddyfile
docker/ Dockerfiles
docs/
git-workflow.md Trunk-based workflow
Contributing
See docs/git-workflow.md for the branching and commit conventions. TL;DR: trunk-based, short-lived branches, Conventional Commits, no force-pushing main.
License
TBD.