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v1.0.0 HPC Scheduling Advisory Platform

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@github-actions github-actions released this 22 Feb 21:14
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v1.0.0
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v1.0.0 — Production-Ready HPC Scheduling Advisory Platform

Systems-first HPC scheduling research and engineering platform (Python + Rust) for reproducible policy evaluation under uncertainty. This release marks the first production-ready milestone with a 9.0/10 industrial-grade readiness score across 15 audit dimensions.

Highlights

  • Contract-driven simulation — Deterministic replay with executable invariants, fidelity gating, and fairness/starvation bounds
  • Full credibility protocol — Multi-trace orchestration with per-trace fidelity, sensitivity sweeps, and recommendation dossiers
  • Kubernetes-ready — 9 production manifests (Deployment, HPA, ServiceMonitor, OTel Collector, Alertmanager)
  • 13-job CI/CD pipeline — Lint, strict mypy, SAST, dependency audit, secret scan, E2E smoke test, cross-language parity, coverage gate, OpenAPI compat, Docker build, and release gate with SBOM
  • 100+ tests at 75%+ coverage — including Hypothesis property-based tests for simulation invariants, fidelity metrics, adapter contracts, and recommendation engine

What's New (since 0.1.0)

Core Platform

  • Multi-format ingestion (SWF, Slurm, PBS/Torque) with canonical parquet export
  • Runtime quantile modeling (p10/p50/p90) with monotonic enforcement and fallback semantics
  • Resource-fit modeling (fragmentation classifier + node size regressor)
  • Deterministic simulation for FIFO_STRICT, EASY_BACKFILL_BASELINE, and ML_BACKFILL_P50
  • Recommendation engine with single-objective and Pareto multi-objective modes
  • Benchmark suite with regression gate and history tracking

Production Infrastructure

  • FastAPI with per-endpoint rate limiting, request draining, and deprecation headers (RFC 8594/9745)
  • Prometheus metrics + Grafana dashboard (8 panels)
  • OpenTelemetry distributed tracing with per-environment sampling
  • SLOs (99.5% availability), error budgets, and Alertmanager routing (PagerDuty + Slack)
  • File-based API key auth with 3-tier loading and hot rotation
  • Docker (multi-stage, pinned digests, secrets mount) + Kubernetes manifests

Engineering Quality

  • Strict mypy (disallow_untyped_defs = true) with PEP 561 marker
  • Property-based tests (Hypothesis) across 5 core modules
  • Cross-language adapter parity testing (Python ↔ Rust)
  • 10 JSON schemas locked with additionalProperties: false
  • Immutable run manifests with hashes, seeds, and environment fingerprints
  • Pre-commit hooks (ruff, bandit, mypy, hadolint)

Operations

  • 32 documentation files: 10-chapter technical docs, 9 ops guides, 5 runbooks, 3 security docs
  • Disaster recovery drill script
  • Drift monitoring with PSI + metric degradation tracking
  • Artifact retention with production-model protection

Quick Start

pip install -e ".[dev]"
hpcopt ingest swf --input data/raw/trace.swf.gz --dataset-id my_trace --out data/curated
hpcopt simulate replay-baselines --trace data/curated/my_trace.parquet --capacity-cpus 64
Assets 4
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