bd9c3fa4f0
A per-app "Workflows" tab: list definitions, browse run history, and inspect a run's per-step progress with a static layered DAG. - API: the run-detail endpoint now returns each step's `depends_on` (loaded from the definition via a new `get_workflow_by_id` reader) so the dashboard can draw the graph edges — the run's step rows don't carry them. - dashboard `$lib/api`: a `workflows` namespace (list / runs / start / run) + the matching types. - `apps/[slug]/workflows/+page.svelte`: workflow table → drill into runs → drill into a run. The run view renders a step table plus an SVG DAG (nodes = steps colored by status, laid out by longest-path level; edges = depends_on, arrowed) and a "Start run" button. Nested/parked steps show their child run. - AppTabBar + the per-app layout gain the Workflows tab (admin-only). Tests: `npm run check` clean (0 errors); two Playwright smoke tests (navigation tabs — workflows loads cleanly + renders its empty state) pass against the full stack. With M6 the v1.2 Workflows track (M1 schema/validation → M2 durable orchestrator → M3 when/templating → M4 nested → M5 SDK/API/CLI → M6 dashboard) is COMPLETE. Co-Authored-By: Claude Opus 4.8 <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.