8b62b137c0
`trigger_depth` bounds how DEEP a trigger/invoke chain runs, but nothing bounded
how WIDE one execution could fan out. A single anonymous request running
`for i in 0..1_000_000 { invoke_async("w", #{}) }` costs a few Rhai ops plus one
cheap outbox INSERT per iteration, so within the op / wall-clock budget it could
write ~10^5 durable rows — each dispatched as its own execution — flooding the
outbox and dispatcher (a durable-amplification DoS).
Add a per-execution ceiling on DURABLE emissions (`invoke_async`,
`pubsub::publish_durable`, `queue::enqueue`, and the shared-topic/-queue
variants), env `PICLOUD_MAX_EMISSIONS_PER_EXECUTION` (default 1000). It's a
thread-local counter wrapped by a re-entrancy-aware `EmissionBudgetScope` around
every `execute_ast`: the OUTERMOST scope resets it, so a fresh dispatched
handler (a new pooled-thread task) gets a full budget while a synchronous
`invoke()` / interceptor re-entry nested in the same call stack SHARES it (fan-
out counted across the whole synchronous chain). The outermost Drop re-zeroes
the counter so a pooled thread never leaks a count into the next task.
Pinned by an `emit_budget` unit test (outermost resets, nested shares, ceiling
trips); the invoke/queue/pubsub/workflow journeys (small counts) stay green.
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.