Initial commit: API gateway with admin console
- FastAPI async gateway with httpx proxying to multiple upstreams - SQLite database with SQLAlchemy ORM - Admin console: manage services, users, API keys, endpoint access - Per-key, per-endpoint granular access control - OpenAPI document sync and caching (5-minute TTL) - Request/response logging with full transaction inspection - In-memory rate limiting (per-key, fixed-window) - Tiered log retention (7d payloads, 90d rows, incremental vacuum) - TLS verification toggle per service (for self-signed certificates) - Service connectivity validation with automatic endpoint refresh - Request browser with filters and deep-link inspection - Docker setup with persistent volume - Modal forms for create/edit flows Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
This commit is contained in:
Samuel Amar
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"""JSON endpoints backing the monitoring charts.
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All endpoints accept:
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hours — window size (1..720)
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service_id — restrict to one service
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user_id — restrict to keys owned by one user
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key_id — restrict to one API key
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Time series use adaptive buckets: 5 min (<=6 h), 1 h (<=48 h), 1 day beyond.
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SQLite-specific date functions are used (see README).
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"""
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import time
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from datetime import datetime, timedelta, timezone
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from fastapi import APIRouter, Depends, Query
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from sqlalchemy import Integer, func
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from sqlalchemy.orm import Query as OrmQuery, Session
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from app.admin.deps import current_user
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from app.database import get_db
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from app.models import ApiKey, Endpoint, RequestLog, Service, User
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router = APIRouter(prefix="/admin/api", dependencies=[Depends(current_user)])
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class Filters:
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def __init__(
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self,
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hours: int = Query(24, ge=1, le=720),
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service_id: int | None = Query(None),
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user_id: int | None = Query(None),
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key_id: int | None = Query(None),
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):
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self.hours = hours
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self.since = datetime.now(timezone.utc) - timedelta(hours=hours)
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self.service_id = service_id
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self.user_id = user_id
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self.key_id = key_id
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def apply(self, q: OrmQuery, joined_key: bool = False) -> OrmQuery:
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"""Apply window + filters. Pass joined_key when the query already
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joins ApiKey so we don't join twice."""
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q = q.filter(RequestLog.timestamp >= self.since)
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if self.service_id:
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q = q.filter(RequestLog.service_id == self.service_id)
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if self.key_id:
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q = q.filter(RequestLog.api_key_id == self.key_id)
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if self.user_id:
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if not joined_key:
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q = q.join(ApiKey, RequestLog.api_key_id == ApiKey.id)
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q = q.filter(ApiKey.user_id == self.user_id)
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return q
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def _bucket_seconds(hours: int) -> int:
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if hours <= 6:
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return 300
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if hours <= 48:
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return 3600
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return 86400
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def _label_format(hours: int, bucket: int) -> str:
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if bucket < 3600:
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return "%H:%M"
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if bucket == 3600:
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return "%H:00" if hours <= 24 else "%m-%d %H:00"
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return "%Y-%m-%d"
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def _bucket_expr(bucket: int):
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# epoch - (epoch % bucket) floors to the bucket start; plain `/` must be
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# avoided because SQLAlchemy renders it as true (float) division.
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epoch = func.cast(func.strftime("%s", RequestLog.timestamp), Integer)
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return epoch - (epoch % bucket)
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def _series(f: Filters, db: Session, *aggregates):
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"""Group the filtered logs into time buckets and fill gaps with None.
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Returns (labels, [values-per-aggregate])."""
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bucket = _bucket_seconds(f.hours)
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fmt = _label_format(f.hours, bucket)
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expr = _bucket_expr(bucket).label("bucket")
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rows = (
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f.apply(db.query(expr, *aggregates))
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.group_by("bucket").order_by("bucket").all()
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)
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found = {int(r[0]): r for r in rows}
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start = int(f.since.timestamp()) // bucket * bucket
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now = int(time.time())
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labels: list[str] = []
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series: list[list] = [[] for _ in aggregates]
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for t in range(start, now + 1, bucket):
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labels.append(datetime.fromtimestamp(t, timezone.utc).strftime(fmt))
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row = found.get(t)
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for i in range(len(aggregates)):
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series[i].append(row[i + 1] if row else None)
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return labels, series
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@router.get("/stats/summary")
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def summary(f: Filters = Depends(), db: Session = Depends(get_db)):
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total = f.apply(db.query(func.count(RequestLog.id))).scalar() or 0
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errors = f.apply(db.query(func.count(RequestLog.id))).filter(
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RequestLog.status_code >= 500).scalar() or 0
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avg_latency = f.apply(db.query(func.avg(RequestLog.latency_ms))).scalar() or 0
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return {
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"total_requests": total,
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"error_count": errors,
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"error_rate": round(errors / total * 100, 2) if total else 0,
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"avg_latency_ms": round(avg_latency, 1),
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"active_services": db.query(Service).filter(Service.is_active).count(),
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"active_keys": db.query(ApiKey).filter(ApiKey.is_active).count(),
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}
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@router.get("/stats/timeseries")
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def timeseries(f: Filters = Depends(), db: Session = Depends(get_db)):
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labels, (ok, errors) = _series(
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f, db,
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func.sum(func.iif(RequestLog.status_code < 500, 1, 0)),
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func.sum(func.iif(RequestLog.status_code >= 500, 1, 0)),
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)
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return {
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"labels": labels,
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"ok": [int(v) if v is not None else 0 for v in ok],
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"errors": [int(v) if v is not None else 0 for v in errors],
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}
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@router.get("/stats/latency-timeseries")
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def latency_timeseries(f: Filters = Depends(), db: Session = Depends(get_db)):
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labels, (avg_ms,) = _series(f, db, func.avg(RequestLog.latency_ms))
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return {
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"labels": labels,
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"avg_ms": [round(v, 1) if v is not None else None for v in avg_ms],
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}
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@router.get("/stats/by-service")
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def by_service(f: Filters = Depends(), db: Session = Depends(get_db)):
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q = (
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db.query(Service.name, func.count(RequestLog.id).label("count"))
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.join(RequestLog, RequestLog.service_id == Service.id)
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)
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rows = (
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f.apply(q)
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.group_by(Service.id)
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.order_by(func.count(RequestLog.id).desc())
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.all()
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)
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return {"labels": [r.name for r in rows], "counts": [r.count for r in rows]}
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@router.get("/stats/by-endpoint")
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def by_endpoint(f: Filters = Depends(), db: Session = Depends(get_db)):
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q = (
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db.query(Service.slug, Endpoint.method, Endpoint.path,
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func.count(RequestLog.id).label("count"))
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.select_from(RequestLog)
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.join(Endpoint, RequestLog.endpoint_id == Endpoint.id)
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.join(Service, Endpoint.service_id == Service.id)
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)
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rows = (
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f.apply(q)
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.group_by(Endpoint.id)
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.order_by(func.count(RequestLog.id).desc())
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.limit(15)
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.all()
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)
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return {
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"labels": [f"{r.slug}: {r.method} {r.path}" for r in rows],
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"counts": [r.count for r in rows],
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}
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@router.get("/stats/by-status")
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def by_status(f: Filters = Depends(), db: Session = Depends(get_db)):
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q = (
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db.query(RequestLog.status_code, func.count(RequestLog.id))
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)
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rows = (
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f.apply(q)
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.group_by(RequestLog.status_code)
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.order_by(RequestLog.status_code)
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.all()
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)
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return {"labels": [str(r[0]) for r in rows], "counts": [r[1] for r in rows]}
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@router.get("/stats/latency-by-service")
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def latency_by_service(f: Filters = Depends(), db: Session = Depends(get_db)):
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q = (
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db.query(Service.name, func.avg(RequestLog.latency_ms).label("avg_ms"))
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.join(RequestLog, RequestLog.service_id == Service.id)
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)
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rows = (
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f.apply(q)
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.group_by(Service.id)
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.order_by(func.avg(RequestLog.latency_ms).desc())
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.all()
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)
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return {"labels": [r.name for r in rows], "avg_ms": [round(r.avg_ms, 1) for r in rows]}
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@router.get("/stats/top-keys")
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def top_keys(f: Filters = Depends(), db: Session = Depends(get_db)):
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q = (
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db.query(ApiKey.name, func.count(RequestLog.id).label("count"))
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.join(RequestLog, RequestLog.api_key_id == ApiKey.id)
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)
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rows = (
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f.apply(q, joined_key=True)
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.group_by(ApiKey.id)
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.order_by(func.count(RequestLog.id).desc())
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.limit(10)
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.all()
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)
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return {"labels": [r.name for r in rows], "counts": [r.count for r in rows]}
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@router.get("/stats/by-user")
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def by_user(f: Filters = Depends(), db: Session = Depends(get_db)):
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q = (
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db.query(User.username, func.count(RequestLog.id).label("count"))
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.select_from(RequestLog)
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.join(ApiKey, RequestLog.api_key_id == ApiKey.id)
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.join(User, ApiKey.user_id == User.id)
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)
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rows = (
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f.apply(q, joined_key=True)
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.group_by(User.id)
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.order_by(func.count(RequestLog.id).desc())
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.limit(15)
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.all()
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)
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return {"labels": [r.username for r in rows], "counts": [r.count for r in rows]}
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