# Product Overview

XCE is an HPC (High-Performance Computing) cluster management system providing job scheduling, queue management, and cluster resource control. It targets organizations running batch workloads on on-premises or air-gapped compute clusters who need deterministic scheduling, multi-tenant access control, and zero external database dependencies.

## Core Capabilities

1. **Job lifecycle management** — submit, start, stop, restart, kill, and monitor jobs including job arrays. Resource usage data is collected and exposed via API.
2. **Queue and scheduling** — plugin-based scheduling engine for job-to-node placement with queue control (enable/disable) and expression-based resource filtering.
3. **Cluster and host management** — node status monitoring (online/offline/unavailable), cluster topology tracking, and host control operations.
4. **Multi-tenant RBAC + pluggable auth** — domain-based `action:scope` permission model (e.g., `job:view:self`). Auth backends: configfile, LDAP, OAuth2, PAM. Built-in IP whitelist and rate limiting.
5. **Controller persistence and HA** — WAL + checkpoint-based single-controller persistence with LSF-style priority election for standby failover and live replication over TCP (Cap'n Proto serialization).

## Target Use Cases

- **Local HPC batch computing** — long-running scientific/engineering workloads requiring deterministic scheduling, queue priority, and resource isolation.
- **Air-gapped / secure environments** — standalone deployments with file-based auth + SSL, no external cloud dependencies.
- **Multi-team shared clusters** — multiple teams sharing a cluster through RBAC with JWT token authentication.
- **No-shared-storage HPC** — controller uses local filesystem (ext4/xfs) for storage; job files transferred via API upload/download rather than network shares.

## Value Proposition

XCE provides a **fully integrated single-vendor stack** (no database setup, unified build system) with an open, buildable codebase (Nix flakes, AppImage packaging). Compared to Slurm/PBS, it eliminates the external database requirement. Compared to commercial LSF, it is open source and reproducibly buildable.

**Key architectural trade-off**: single-writer model throughout — no multi-master consensus. HA failover uses LSF-style priority election (simple, predictable) rather than Raft (10× complexity). All controller state is in-memory; persistence is WAL + checkpoint, not a traditional database.

## Active Development Context

The project is in a **persistence and HA transformation** (branch `persistent_ha`). Phases:

| Phase | Goal | Status |
|-------|------|--------|
| P0 | Restart survival (WAL + checkpoint) | Implementing |
| P1 | Standby election and takeover | Designed |
| P2 | Live replication primary → standby | Designed |
| P2.5 | Worker/scheduler auto-reconnect on failover | Designed |
| P3–P4 | Hardening, metrics, docs | Planned |

Key design decisions already locked:
- No `fork()` for snapshots (mutex inheritance deadlock in multithreaded controller)
- No Raft (single writer makes consensus overhead unjustified)
- No BoltDB (using dual zarray COW for application-level checkpointing)
- No application-layer encryption (trust OS boundary: chmod 0700, LUKS/dm-crypt)
- No WAL logging for job deletion (deferred to checkpoint time to simplify replay)