All phases
02
Aigarth Core
Compute reservation engine, capacity allocator, queue, scheduler, region mgmt.
Progress
100%
Tasks done
11 / 11
0 remaining
Owner
Core lead
Status: complete
Tasks
Kanban for this phase. Move tasks between columns to update status.
Backlog
0
To do
0
In progress
0
In review
0
Done
11
Research Qubic reference stack (qubic.org, docs.qubic.org, GitHub)
p0
Eng lead + AI agents1 SP
Compute service scaffold (Fastify + Drizzle + node-postgres + JWT, port 7003)
p0
Eng lead + AI agents1 SP
Compute schema (6 tables: regions, clusters, members, jobs, reservations, audit log)
p0
Eng lead + AI agents2 SP
Region + cluster services (CRUD, members, region filter, stats)
p0
Eng lead + AI agents2 SP
Job service: submit, lifecycle, cost model, capacity check, cancel
p0
Eng lead + AI agents4 SP
Reservation service: create, credit math, early-release with penalty
p0
Eng lead + AI agents2 SP
Routes: regions, clusters, jobs, reservations, credits, stats
p0
Eng lead + AI agents2 SP
Job monitor worker (NATS subscribe + auto-progress + deadline expiry)
p0
Eng lead + AI agents1 SP
Seed: 2 regions (global, eu-west) + 3 clusters (general, training, inference) + 369 computor memberships
p1
Eng lead + AI agents1 SP
E2E test: 30+ assertions across 12 sections (green on first run)
p0
Eng lead + AI agents1 SP
Decision: don't build a generic compute scheduler (defer to Qubic's tick execution)
p1
Eng lead + AI agents2 SP