6891eda66c
Extends Dispatcher with the v1.1.9 queue path. The queue table IS the
outbox for queue semantics, so the dispatcher polls queue_messages
directly via FOR UPDATE SKIP LOCKED — no outbox indirection.
Per tick (every 100ms):
1) outbox arm — unchanged
2) queue arm: list_active_queue_consumers() → per (app_id, queue_name)
attempt one claim. Bounded by registered-consumer count so one busy
queue can't starve others.
Per claimed message:
- Build TriggerEvent::Queue + ExecRequest (executes as the trigger's
registering principal, matching design notes §4)
- dispatch through executor.execute_with_identity (reuses AST cache)
- success → queue.ack(id, claim_token) — DELETE WHERE id AND token
- throw + attempt < max_attempts → queue.nack(...) — clear claim, set
deliver_after = NOW() + compute_backoff(attempt, backoff, base_ms, jitter)
- throw + exhausted → queue.dead_letter(...) atomic move to dead_letters
+ DELETE in one transaction. fan_out_dead_letter on the outbox arm
fires registered dead_letter handlers off the new row without changes.
Visibility-timeout reclaim task: separate tokio::spawn ticking on
queue_reclaim_interval_ms (default 30000). UPDATE clears claim_token /
claimed_at on rows whose claimed_at exceeds the per-queue
visibility_timeout_secs (joined from queue_trigger_details). A crashed
consumer thus loses its lease and the message becomes claimable again.
Dispatcher gains queue: Arc<dyn QueueRepo>; picloud/lib.rs threads
queue_repo.clone() into the construction.
ActiveQueueConsumer extended with app_id so the queue claim can be
performed without a follow-up trigger lookup; list_active_queue_consumers
SQL extended to SELECT t.app_id.
Co-Authored-By: Claude Opus 4.7 (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.