mirror of
https://github.com/blackboxprogramming/BlackRoad-Operating-System.git
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9644737ba7
## Domain Architecture - Complete domain-to-service mapping for 16 verified domains - Subdomain architecture for blackroad.systems and blackroad.io - GitHub organization mapping (BlackRoad-OS repos) - Railway service-to-domain configuration - DNS configuration templates for Cloudflare ## Extracted Services ### AIops Service (services/aiops/) - Canary analysis for deployment validation - Config drift detection - Event correlation engine - Auto-remediation with runbook mapping - SLO budget management ### Analytics Service (services/analytics/) - Rule-based anomaly detection with safe expression evaluation - Cohort analysis with multi-metric aggregation - Decision engine with credit budget constraints - Narrative report generation ### Codex Governance (services/codex/) - 82+ governance principles (entries) - Codex Pantheon with 48+ agent archetypes - Manifesto defining ethical framework ## Integration Points - AIops → infra.blackroad.systems (blackroad-os-infra) - Analytics → core.blackroad.systems (blackroad-os-core) - Codex → operator.blackroad.systems (blackroad-os-operator) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
import json
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from collections import defaultdict
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from datetime import datetime
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from pathlib import Path
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from typing import Dict, List
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from tools import storage
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from .utils import increment, log_event
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ROOT = Path(__file__).resolve().parents[1]
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COHORTS_DIR = ROOT / "artifacts" / "cohorts"
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DATA_DIR = ROOT / "samples" / "data"
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def define_cohort(name: str, criteria: Dict[str, str]) -> None:
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path = COHORTS_DIR / f"{name}.json"
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storage.write(str(path), criteria)
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def _period(ts: str, window: str) -> str:
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dt = datetime.fromisoformat(ts)
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if window == "M":
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return dt.strftime("%Y-%m")
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if window == "W":
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return f"{dt.isocalendar().year}-W{dt.isocalendar().week:02d}"
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if window == "Q":
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q = (dt.month - 1) // 3 + 1
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return f"{dt.year}-Q{q}"
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raise ValueError("unknown window")
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METRIC_FUNCS = {
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"revenue": lambda rows: sum(r["revenue"] for r in rows),
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"gross_margin_pct": lambda rows: (
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round(
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(sum(r["revenue"] - r["cost"] for r in rows) / revenue_sum * 100)
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if (revenue_sum := sum(r["revenue"] for r in rows))
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else 0,
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2,
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)
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),
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"nps": lambda rows: round(sum(r["nps"] for r in rows) / len(rows), 2),
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"return_rate": lambda rows: round(sum(r["return_rate"] for r in rows) / len(rows), 4),
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"uptime": lambda rows: round(sum(r["uptime"] for r in rows) / len(rows), 3),
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"mttr": lambda rows: round(sum(r["mttr"] for r in rows) / len(rows), 2),
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}
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def cohort_view(table: str, cohort_name: str, metrics: List[str], window: str) -> List[Dict[str, float]]:
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criteria = json.loads(storage.read(str(COHORTS_DIR / f"{cohort_name}.json")))
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rows = json.loads(Path(DATA_DIR / f"{table}.json").read_text())
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filtered = [r for r in rows if all(r.get(k) == v for k, v in criteria.items())]
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buckets: Dict[str, List[Dict]] = defaultdict(list)
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for r in filtered:
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buckets[_period(r["date"], window)].append(r)
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out: List[Dict[str, float]] = []
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for period, bucket in sorted(buckets.items()):
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rec = {"period": period}
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for m in metrics:
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rec[m] = METRIC_FUNCS[m](bucket)
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out.append(rec)
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increment("cohort_run")
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log_event({"type": "cohort_run", "cohort": cohort_name, "table": table})
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return out
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