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Audit #6. `KvServiceImpl` wrote the row, waited for it to commit, then asked the emitter to resolve matching triggers and insert outbox rows — a second transaction on a second connection. If that second step failed, the row was permanently in the store with its trigger having never fired: invisible to the caller (the write "succeeded"), unrecoverable by any retry, and only ever logged. The code said as much: // Audit finding (Medium): this is non-transactional with the data // write — the row above has already committed by the time emit() // runs, so an emit failure means triggers silently don't fire. Introduce `atomic_write::KvWriter` — the mutating half of the service (the write AND the fan-out it produces), so the two can share a transaction: * `PostgresKvWriter` opens a tx, writes via `kv_repo::*_on(&mut *tx, …)`, runs the fan-out on the SAME connection via `emit_on(&mut *tx, …)`, and commits. An emit failure now rolls the write back and surfaces to the script, which is the honest outcome — the caller learns the write did not happen instead of silently getting a store that disagrees with its triggers. * `BestEffortKvWriter` keeps the old write-then-log-on-emit-failure semantics for the in-memory unit tests (no Postgres). Both sit behind one trait, so the service body has a single code path and the choice is a constructor detail (`with_atomic_writes(pool)` in the host). Pool-deadlock rule, documented on the module: everything inside the tx runs on the tx's connection. A writer that held a tx and then reached for a second pooled connection could starve — the pool is sized to the execution concurrency cap, so N executions each wanting 2 connections deadlock. The fan-out takes `&mut *tx` and never touches a repo. `tests/atomic_write.rs` pins it by injecting an outbox failure (a Postgres BEFORE-INSERT trigger scoped to the test's own app_id, so parallel tests are unaffected): the set errors and the key is NOT in the store; likewise a delete rolls back rather than dropping a key nothing downstream hears about. 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.