Files
SciMesh/coordinator
Efremenko Arhip bda22666d7 feat(coordinator): scaffold task-queue service in Go
Adds the SciMesh coordinator: a durable task-queue server on PostgreSQL
that owns all database access, with workers reaching it over HTTP only.

Structured as a modular monolith following Clean Architecture:

  domain     entities and their invariants, no I/O
  usecase    business operations + repository/clock ports
  transport  HTTP handlers, DTOs, auth, error mapping
  storage    PostgreSQL repositories, transactions carried in context
  infra      config, pool, clock, server, lease reaper

Dependencies point strictly inward; domain imports nothing from the module.

Working: layer wiring, routing, shared-token auth, access logging, request
IDs, domain-error to status-code mapping, transactional boundaries,
graceful shutdown (HTTP drain -> reaper stop -> pool close), migrations,
and a Compose stack starting Postgres -> migrations -> coordinator.

The domain is complete and covered by unit tests that need no database:
lease ownership, stale attempts, idempotent result replay, retry budgets,
and lease expiry.

Repository methods are stubs returning ErrNotImplemented (HTTP 501). The
SQL for atomic claiming (FOR UPDATE SKIP LOCKED) and for lease expiry is
written and ready to wire up.

See coordinator/ARCHITECTURE.md for the layer map and a request traced
through every layer.
2026-07-22 13:49:01 +03:00
..

SciMesh Coordinator

Durable task-queue server for SciMesh, in Go on PostgreSQL. It owns all database access; workers talk to it only over HTTP and never receive DB credentials.

Built as a modular monolith following Clean Architecture — one binary, four layers, dependencies pointing strictly inward. See docs/database-integration-task.md and docs/worker-daemon-task.md in the repo root for the full contract.

Layers

        infra       config, pgxpool, http.Server, clock    ← frameworks & drivers
        transport   http handlers      ← inbound: who calls us
        storage     sql repositories   ← outbound: who we call
        usecase     business operations + PORTS            ← application rules
        domain      Task, Job + their invariants           ← enterprise rules

                            ┌── transport ──┐
        domain ◄── usecase ◄┤               ├◄── infra
                            └── storage ────┘

transport and storage are one layer — the "interface adapters" ring — split by direction rather than by category, so a file's path tells you its role.

The rule that matters: source dependencies point only inward. domain imports nothing from this module; usecase sees only domain; transport and storage know nothing of each other. Verify it at any time with:

go list -f '{{range .Imports}}{{.}}{{"\n"}}{{end}}' ./internal/domain | grep internal   # must be empty

Layout

coordinator/
  cmd/coordinator/main.go      # composition root: the only place with concrete types
  internal/
    domain/                    # entities + rules, no I/O
      task.go                    Task, lease/complete/fail/expire transitions
      job.go                     Job, chunk fan-out, status derivation
      errors.go                  business-rule violations
    usecase/                   # one type per operation, dependencies injected
      ports.go                   TaskRepository, JobRepository, TxManager, Clock
      dto.go                     use-case boundary inputs
      task.go                    claim, renew, complete, fail, expire
      job.go                     create, status, results, stitch
    transport/http/            # routing, DTOs, middleware, error mapping
    storage/postgres/          # SQL behind the ports; TxManager via context
    infra/                     # config.go db.go clock.go server.go
  migrations/                  # golang-migrate SQL, run as an explicit command

A full map — file-by-file table, a request traced through every layer, and a "where do I add X" guide — lives in ARCHITECTURE.md.

Quickstart

With Docker (nothing to install but Docker)

make up                       # Postgres → migrations → coordinator
curl localhost:8080/health
make logs                     # follow the coordinator
make down                     # stop (add down-clean to drop the DB volume)

up starts three services in order: Postgres waits until pg_isready passes, a one-shot migrate container applies the schema and exits, and only then does the coordinator start — so it never queries a database that has no tables.

Needs BuildKit. The Dockerfile uses RUN --mount=type=cache to reuse the Go module and compiler caches between builds. If the build fails with "the --mount option requires BuildKit", install the buildx plugin — pacman -S docker-buildx on Arch, apt install docker-buildx-plugin on Debian.

Locally, against your own Postgres

cp .env.example .env          # then edit DATABASE_URL / WORKER_AUTH_TOKEN
                              # it is loaded automatically — no export needed

make tidy                     # fetch deps (needs network once)
make migrate-up               # apply schema (needs the migrate CLI)
make run                      # start the server

Configuration

Settings come from the environment. A .env file is loaded at startup via godotenv as a local-dev convenience (override its path with ENV_FILE):

  • a missing .env is not an error — production injects real env vars;
  • real environment variables always win over the file, so an orchestrator's values are never shadowed by a stale .env baked into an image.

See .env.example; only DATABASE_URL is required.

Endpoints

Method Path Purpose
POST /jobs Create job + pending tasks transactionally
POST /tasks/claim Atomically lease one task (204 if none)
POST /tasks/{task_id}/heartbeat Renew the caller's lease
POST /tasks/{task_id}/result Record a completed result (idempotent)
POST /tasks/{task_id}/failure Record failure / retryable state
GET /jobs/{job_id} Aggregate job progress
GET /health Liveness (unauthenticated)

Status

Scaffold with a complete, tested domain. Layers, wiring, routing, auth, access logging, error mapping, transactions, migrations, and graceful shutdown are in place. Repository methods are stubs returning ErrNotImplemented (→ HTTP 501); the SQL for claiming and lease expiry is written and ready to wire.

Roadmap:

  1. schema + migrations
  2. ClaimNext, InsertBatch — atomic claim via FOR UPDATE SKIP LOCKED
  3. GetForUpdate, Update, CountByStatus — completes the result/failure paths
  4. file upload / chunk download
  5. ExpireLeases — SQL is written, needs wiring
  6. stitcher: merge per-chunk top-k into the final CSV
  7. integration tests against real Postgres via TEST_DATABASE_URL

Tests

internal/domain is covered by unit tests that need no database — lease ownership, stale attempts, idempotent replays, retry budgets, and expiry are all pure functions of entity state:

go test ./...
go vet ./...

Integration tests (concurrent claiming, migrations) come in phase 7 and require a real PostgreSQL instance supplied through TEST_DATABASE_URL.