a2360a9464
`OutboxEventEmitter` resolved matching triggers and inserted outbox rows
through `Arc<dyn TriggerRepo>` / `Arc<dyn OutboxRepo>`, i.e. against the
pool — each query on whatever connection it happened to get. That makes a
transactional outbox impossible: the data write and the outbox rows can
never share a transaction, so a crash (or an outbox error) between them
silently loses the trigger event.
Take the emitter down to a connection instead of a pool:
* `outbox_repo::insert_on(exec, row)` and `trigger_repo::list_matching_on`
/ `list_matching_shared_on(exec, ...)` are generic over `PgExecutor`, so
the same SQL serves a pooled connection or a `&mut *tx`. The repo trait
methods delegate to them — the SQL keeps exactly one home.
* `emit_on` / `emit_shared_on` take a `&mut PgConnection` and run the whole
fan-out on it. The `ServiceEventEmitter` impl acquires one pooled
connection and calls them, so behaviour is unchanged today; a caller
holding a transaction can now pass `&mut *tx` and have the outbox rows
commit with the write.
* `OutboxEventEmitter::new` takes the `PgPool` directly (it was only ever
constructed once, in the host wiring).
Also collapses the three copy-pasted per-app match queries (kv/docs/files
differ only in the `kind` discriminator and detail table) and the three
`emit_*` bodies into one `plan()` + one match fn, so the suppression
anti-join, the chain walk, and the empty-ops-means-any-op semantic each
exist once rather than three times.
No behaviour change — pure refactor. It is the seam the transactional
write lands on next.
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.