5a630e1d9f
The user-facing surface for the durable DAG engine. A workflow run can now be
started three ways, all resolving the workflow by name in the caller's app
(`cx.app_id` / the resolved app — never a passed-in arg, the isolation
boundary), seeding a run the orchestrator advances.
SDK seam (shared):
- `WorkflowService` trait + `NoopWorkflowService` + `WorkflowError` in
`shared::workflow` (mirrors `InvokeService`); added to `Services` as a
noop-defaulted `with_workflow` builder (all `Services::new` call sites
unchanged).
- `WorkflowServiceImpl` (manager-core): resolves + seeds a run; authenticated
callers gated on `AppInvoke` (anonymous skips, script-as-gate), the same gate
`invoke()` uses.
- `executor-core::sdk::workflow` — the Rhai bridge `workflow::start(name, input)`
/ `workflow::start(name)`, registered in `register_all`. Returns the run id.
Admin API (manager-core `workflows_api`, mounted in the binary):
- `GET /apps/{app}/workflows` — definitions (AppRead)
- `POST /apps/{app}/workflows/{name}/runs` — start a run (AppInvoke)
- `GET /apps/{app}/workflows/{name}/runs` — run history (AppRead)
- `GET /apps/{app}/workflow-runs/{run_id}` — one run + its steps (AppRead)
`app_id` scopes every query; a foreign run 404s.
CLI (`pic workflows`): `ls` · `run <name> [--input JSON]` · `runs <name>` ·
`run-status <run_id>` — all `--app`-scoped; run definitions stay declarative
(`[[workflows]]` → `pic apply`).
Also: `list_runs_for_workflow` repo reader.
Tests: `workflow_service_start_seeds_a_run` (DB-gated — the SDK/API-shared
entry) + `workflow_run_executes_end_to_end` CLI journey (apply → `pic workflows
run` → poll `run-status` → succeeded, through the real binary + orchestrator).
fmt + clippy -D warnings clean, 449 manager-core lib tests, 14 orchestrator DB
tests, 18 executor-core lib tests, 3 workflow CLI journeys green.
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.