44f992cbb0
First milestone of the v1.2 Workflows track (blueprint §9.1/§9.2): the durable
DAG engine's foundation — the definition model, its validation, and the
declarative `apply` reconcile path. No execution yet (the orchestrator is M2).
- Migration 0071_workflows: `workflows` (owner-polymorphic like scripts, app-
owned in M1), `workflow_runs`, and `workflow_run_steps` (the per-step
competing-consumer lease table the M2 orchestrator will claim). Schema golden
reblessed.
- `shared::workflow`: the `WorkflowDefinition` / `WorkflowStepDef` DTOs (shared
by the CLI, apply, and the future orchestrator) + run/step status enums.
- Pure, DB-free `workflow_template` (input `{{ input.x }}` / `{{ steps.a.output.y }}`
resolution, type-preserving) and `workflow_expr` (a small safe JSON-predicate
evaluator for `when` — keeps manager-core free of a scripting engine).
- `workflow_repo`: read trait + reconcile tx free-fns (insert/update/delete).
- apply_service: `BundleWorkflow` + `Plan.workflows` + `CurrentState.workflows`
+ `ApplyReport.workflows_*`; server-side `validate_workflow_definition`
(unique/acyclic steps via topological sort, deps exist, function XOR workflow,
`when`/template parse) rejecting on a group node; `diff_workflows` by
lower(name) (Update on a definition change) + in-tx reconcile.
- CLI: `[[workflows]]` + `[[workflows.steps]]` manifest structs → wire bundle;
plan/apply render + report counts.
- Tests: 16 manager-core lib tests (template, expr, definition validation) +
the `workflows` CLI journey (apply → NoOp → prune; cyclic DAG rejected).
Deferred to later milestones: the orchestrator worker (M2), conditional/template
runtime wiring (M3), nested sub-workflows (M4), the SDK/API/CLI run surface
(M5), the dashboard (M6). The `group_id` column + run/step tables ship now so
those slot in without a migration churn.
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.