feat(grafana-metric-gateway): slice 1 — backend gateway transport
Route all prometheus widget queries through Grafana /api/ds/query instead of
direct Prom HTTP. PrometheusConfig: drop base_url, add grafana_url +
datasource_uid; secret grafana_api_key (required). PrometheusWidgetSource →
MetricSource with _gateway_query POST method. normalize_grafana_frames
recovered from 65bae95 + shared _dedup_label helper. Gateway-path status
check. Startup old-config validation. CHANGELOG migration note. All adapter
tests rewritten for POST /api/ds/query + Grafana frames mock. Backend: 331
pytest pass, ruff clean. Frontend: build green (unchanged in S1).
This commit is contained in:
@@ -4,6 +4,19 @@ All notable changes to Manage. Breaking changes are marked with **BREAKING**.
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## [Unreleased]
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### **BREAKING** — Prometheus queries now route through Grafana gateway
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- The `prometheus` service config changed: `base_url` is replaced by
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`grafana_url` + `datasource_uid`, and the `api_key` secret is replaced by
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`grafana_api_key` (a Grafana service account token or API key with read
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access to the Prometheus datasource). All metric widget queries (`chart`,
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`gauge`, `mean`, `metric`) now issue `POST {grafana_url}/api/ds/query`
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instead of direct Prometheus HTTP calls.
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- **Migration:** Reconfigure existing `prometheus` services — replace
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`base_url` with `grafana_url` (your Grafana instance URL), add the
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`grafana_api_key` secret, and optionally set `datasource_uid` (defaults
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to `"prometheus"`).
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### Added — Direct Prometheus charting
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- **Prometheus is now the direct source for in-app charts.** New widget kinds
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@@ -13,9 +13,10 @@ from media_library_viewer_api.integrations.base import (
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class PrometheusConfig(ServiceConfigBase):
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"""Non-secret Prometheus connection config."""
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"""Non-secret Prometheus-via-Grafana gateway config."""
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base_url: ServiceBaseUrl
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grafana_url: ServiceBaseUrl
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datasource_uid: str = "prometheus"
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timeout_seconds: int = 10
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@@ -57,7 +58,12 @@ DEFINITION = ServiceDefinition(
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description="Metrics storage and PromQL queries.",
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config_model=PrometheusConfig,
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secret_fields=[
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SecretField(key="api_key", label="API key", helper="Optional bearer token"),
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SecretField(
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key="grafana_api_key",
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label="Grafana API key",
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required=True,
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helper="Service account token or API key for the Grafana gateway",
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),
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],
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widget_kinds=[
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widget_kind(
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@@ -37,6 +37,23 @@ from .version import get_backend_version, get_version_info
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logger = logging.getLogger(__name__)
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def _validate_prometheus_gateway_config() -> None:
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"""Warn (not crash) about old-shape prometheus services needing migration (GM-113)."""
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try:
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store = get_settings_store()
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for service in store.list_services("prometheus"):
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config = service.get("config") or {}
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if "base_url" in config and "grafana_url" not in config:
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logger.warning(
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"Prometheus service '%s' (id=%s) uses the old 'base_url' config shape. "
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"Reconfigure with grafana_url + grafana_api_key (see CHANGELOG).",
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service.get("name"),
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service.get("id"),
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)
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except Exception: # pragma: no cover - startup best-effort
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logger.exception("Failed to validate prometheus gateway config during startup")
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""Application lifespan — startup/shutdown."""
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@@ -58,6 +75,7 @@ async def lifespan(app: FastAPI):
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get_service_data_harness()
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except Exception:
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logger.exception("Failed to initialize service data harness during startup")
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_validate_prometheus_gateway_config()
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mail_queue = get_mail_queue()
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backup_poller = get_backup_poller()
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mail_queue.start()
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@@ -177,23 +177,52 @@ def get_prometheus_status(
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service_id: str | None = None,
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store: SettingsStore = Depends(get_settings_store),
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) -> dict[str, Any]:
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"""Probe a Prometheus service instance's health and build info."""
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"""Probe a Prometheus service's health via the Grafana gateway path (GM-110).
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Issues a trivial ``up`` query through Grafana ``/api/ds/query``. Success
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validates the full path: Grafana is reachable, the API key works, and the
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Prometheus datasource responds.
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"""
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service = resolve_service_record(store, "prometheus", service_id)
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if service is None:
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return _status_response(None, error="no_service_configured")
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base = _base_url(service)
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timeout = _timeout(service, 10)
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headers = _auth_headers(service)
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grafana_url = str(service.config.get("grafana_url") or "").rstrip("/")
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api_key = str(service.secrets.get("grafana_api_key") or "")
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datasource_uid = str(service.config.get("datasource_uid") or "prometheus")
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timeout = int(service.config.get("timeout_seconds") or 10)
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if not grafana_url or not api_key:
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return _status_response(service, error="gateway_not_configured")
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body = {
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"queries": [
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{
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"datasource": {"uid": datasource_uid, "type": "prometheus"},
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"expr": "up",
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"format": "time_series",
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"intervalMs": 15_000,
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"maxDataPoints": 1,
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"refId": "A",
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}
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],
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"from": "now-1m",
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"to": "now",
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}
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try:
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health = requests.get(f"{base}/-/healthy", headers=headers, timeout=timeout)
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health.raise_for_status()
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build_info = requests.get(f"{base}/api/v1/status/buildinfo", headers=headers, timeout=timeout)
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build_info.raise_for_status()
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version = build_info.json().get("data", {}).get("version", "")
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except Exception:
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logger.exception("Failed to fetch Prometheus status")
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resp = requests.post(
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f"{grafana_url}/api/ds/query",
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json=body,
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headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"},
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timeout=timeout,
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)
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resp.raise_for_status()
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except requests.HTTPError as exc:
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status_code = exc.response.status_code if exc.response else 0
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if status_code in (401, 403):
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return _status_response(service, error="auth_failed")
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return _status_response(service, error="gateway_error")
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except requests.RequestException:
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logger.exception("Failed to fetch Prometheus status via gateway")
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return _status_response(service, error="prometheus_unreachable")
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return _status_response(service, version=version)
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return _status_response(service, version="ok")
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@router.post("/alertmanager-webhook")
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@@ -43,6 +43,15 @@ def step_for_window(window_seconds: int, target_points: int = 200) -> int:
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return max(15, round(window_seconds / target_points))
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def _dedup_label(label: str, seen: dict[str, int]) -> str:
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"""Apply `` (n)`` suffix on collision. Mutates and reads from ``seen`` dict."""
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if label in seen:
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seen[label] += 1
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return f"{label} ({seen[label]})"
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seen[label] = 0
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return label
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def normalize_prometheus_matrix(result: list[dict[str, Any]]) -> list[dict[str, Any]]:
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"""Turn a Prometheus ``/api/v1/query_range`` ``data.result`` matrix into the
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``{label, points:[{t:int, v:float|None}]}`` series shape the frontend chart
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@@ -62,12 +71,7 @@ def normalize_prometheus_matrix(result: list[dict[str, Any]]) -> list[dict[str,
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metric = entry.get("metric") or {}
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values = entry.get("values") or []
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parts = [f"{k}={v}" for k, v in sorted(metric.items()) if not str(k).startswith("__")]
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label = " ".join(parts) if parts else "value"
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if label in seen:
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seen[label] += 1
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label = f"{label} ({seen[label]})"
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else:
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seen[label] = 0
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label = _dedup_label(" ".join(parts) if parts else "value", seen)
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points: list[dict[str, Any]] = []
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for ts, raw in values:
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t = _safe_int(ts)
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@@ -79,6 +83,52 @@ def normalize_prometheus_matrix(result: list[dict[str, Any]]) -> list[dict[str,
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return series
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def normalize_grafana_frames(raw: dict[str, Any]) -> list[dict[str, Any]]:
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"""Turn a Grafana ``/api/ds/query`` response into the ``{label, points}`` series shape.
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Parses ``results.<refId>.frames[]`` where each frame has:
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- ``data.values``: ``[[timestamps...], [values...]]``
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- ``schema.fields``: ``[{name, labels?, config?: {displayName?}}, ...]``
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Label rule (same as ``normalize_prometheus_matrix``, shared via ``_dedup_label``):
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1. Prefer ``config.displayName`` (explicitly set in Grafana).
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2. Else use Prometheus metric labels (sorted ``k=v``, excluding ``__``-prefixed).
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3. Else fall back to the field name, or ``"value"``.
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4. Dedup collisions with `` (n)`` suffix.
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"""
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series: list[dict[str, Any]] = []
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seen: dict[str, int] = {}
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results = raw.get("results", {})
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for _ref_id, ref_data in results.items():
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for frame in ref_data.get("frames", []):
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values = frame.get("data", {}).get("values", [])
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if len(values) < 2:
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continue
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timestamps = values[0]
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vals = values[1]
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# Derive a meaningful series label from the frame metadata.
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fields = frame.get("schema", {}).get("fields", [])
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value_field = fields[-1] if fields else {}
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display_name = value_field.get("config", {}).get("displayName") or value_field.get("displayName")
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frame_labels = value_field.get("labels") or {}
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if display_name:
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label = str(display_name)
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elif frame_labels:
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parts = [f"{k}={v}" for k, v in sorted(frame_labels.items()) if not str(k).startswith("__")]
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label = " ".join(parts) if parts else "value"
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else:
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label = str(value_field.get("name", "value"))
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label = _dedup_label(label, seen)
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points = []
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for t, v in zip(timestamps, vals):
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safe_t = _safe_int(t)
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if safe_t is None:
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continue
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points.append({"t": safe_t, "v": _safe_float(v)})
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series.append({"label": label, "points": points})
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return series
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def _safe_float(raw: Any) -> float | None:
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"""Best-effort float conversion; Prometheus sentinels and junk → ``None``."""
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if raw in _NON_NUMERIC:
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@@ -30,7 +30,8 @@ from media_library_viewer_api.services.settings_store import SettingsStore, get_
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from media_library_viewer_api.services.task_runner import run_saved_task
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from media_library_viewer_api.widgets.prometheus_range import (
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WINDOW_PRESETS,
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normalize_prometheus_matrix,
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normalize_grafana_frames,
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normalize_prometheus_matrix, # noqa: F401 — kept for future direct_url path (design decision 5)
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step_for_window,
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)
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@@ -104,113 +105,118 @@ class StaticWidgetSource:
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# ---------------------------------------------------------------------------
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class PrometheusWidgetSource:
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"""Run PromQL queries against a Prometheus service (instant + range)."""
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class MetricSource:
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"""Run PromQL queries through a Grafana gateway (``/api/ds/query``)."""
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async def fetch(self, service: ServiceRecord | None, widget_kind: str, config: dict[str, Any]) -> dict[str, Any]:
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try:
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if service is None:
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return {"error": "Prometheus widget is missing its service"}
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base_url = str(service.config.get("base_url") or "").rstrip("/")
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grafana_url = str(service.config.get("grafana_url") or "").rstrip("/")
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api_key = str(service.secrets.get("grafana_api_key") or "")
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datasource_uid = str(service.config.get("datasource_uid") or "prometheus")
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timeout = int(service.config.get("timeout_seconds") or 10)
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if widget_kind == "chart":
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return await self._fetch_chart(base_url, timeout, config)
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return await self._fetch_chart(grafana_url, api_key, datasource_uid, timeout, config)
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if widget_kind == "gauge":
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return await self._fetch_gauge(base_url, timeout, config)
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return await self._fetch_gauge(grafana_url, api_key, datasource_uid, timeout, config)
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if widget_kind == "mean":
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return await self._fetch_mean(base_url, timeout, config)
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# Default: instant-query metric path (unchanged).
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raw = await self._instant_query(base_url, timeout, config.get("promql", ""))
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return raw
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return await self._fetch_mean(grafana_url, api_key, datasource_uid, timeout, config)
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# Default: instant-query metric path.
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return await self._fetch_metric(grafana_url, api_key, datasource_uid, timeout, config)
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except Exception as exc:
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logger.exception("prometheus adapter failed")
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return {"error": f"Prometheus query failed: {exc}"}
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async def _range_query(self, base_url: str, timeout: int, promql: str, window: int) -> dict[str, Any]:
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"""Run a Prometheus ``/api/v1/query_range`` over a window (seconds).
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async def _gateway_query(
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self,
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grafana_url: str,
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api_key: str,
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datasource_uid: str,
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timeout: int,
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promql: str,
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window_seconds: int | None = None,
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max_data_points: int = 200,
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) -> dict[str, Any]:
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"""POST ``{grafana_url}/api/ds/query``; return raw Grafana JSON or ``{error}``.
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Shared by the ``chart`` (SC-101) and ``mean`` widget kinds. Returns
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``{"matrix": result}`` on success or ``{"error": str}`` (never raises,
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per SC-103).
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- ``window_seconds=None`` → instant mapping (``from=now-1m, maxDataPoints=1``).
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- ``window_seconds=<N>`` → range query (``from=now-Ns``, step derived).
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"""
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step = step_for_window(window)
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end = int(time.time())
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start = end - window
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try:
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response = await asyncio.wait_for(
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asyncio.to_thread(
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requests.get,
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f"{base_url}/api/v1/query_range",
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params={"query": promql, "start": start, "end": end, "step": step},
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timeout=timeout,
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),
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if not grafana_url:
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return {"error": "grafana_url is required"}
|
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if not api_key:
|
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return {"error": "grafana_api_key is required"}
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step = step_for_window(window_seconds) if window_seconds else 15
|
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interval_ms = step * 1000
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body = {
|
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"queries": [
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{
|
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"datasource": {"uid": datasource_uid, "type": "prometheus"},
|
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"expr": promql,
|
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"format": "time_series",
|
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"intervalMs": interval_ms,
|
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"maxDataPoints": 1 if window_seconds is None else max_data_points,
|
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"refId": "A",
|
||||
}
|
||||
],
|
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"from": f"now-{window_seconds or 60}s" if window_seconds else "now-1m",
|
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"to": "now",
|
||||
}
|
||||
|
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def _do_post() -> dict[str, Any]:
|
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resp = requests.post(
|
||||
f"{grafana_url}/api/ds/query",
|
||||
json=body,
|
||||
headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"},
|
||||
timeout=timeout,
|
||||
)
|
||||
response.raise_for_status()
|
||||
payload = response.json()
|
||||
except asyncio.TimeoutError:
|
||||
return {"error": "Prometheus query timed out"}
|
||||
except requests.RequestException as exc:
|
||||
logger.exception("prometheus range query failed")
|
||||
return {"error": f"Prometheus query failed: {exc}"}
|
||||
result = payload.get("data", {}).get("result", [])
|
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return {"matrix": result}
|
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resp.raise_for_status()
|
||||
return resp.json()
|
||||
|
||||
async def _instant_query(self, base_url: str, timeout: int, promql: str) -> dict[str, Any]:
|
||||
"""Run a Prometheus ``/api/v1/query`` instant query.
|
||||
|
||||
Shared by the ``metric`` and ``gauge`` widget kinds. Returns
|
||||
``{"result": data}`` on success or ``{"error": str}`` (never raises,
|
||||
per SC-103).
|
||||
"""
|
||||
if not promql:
|
||||
return {"error": "promql is required"}
|
||||
try:
|
||||
response = await asyncio.wait_for(
|
||||
asyncio.to_thread(
|
||||
requests.get,
|
||||
f"{base_url}/api/v1/query",
|
||||
params={"query": promql},
|
||||
timeout=timeout,
|
||||
),
|
||||
timeout=timeout,
|
||||
)
|
||||
response.raise_for_status()
|
||||
payload = response.json()
|
||||
return await asyncio.wait_for(asyncio.to_thread(_do_post), timeout=timeout)
|
||||
except asyncio.TimeoutError:
|
||||
return {"error": "Prometheus query timed out"}
|
||||
return {"error": "Grafana query timed out"}
|
||||
except requests.RequestException as exc:
|
||||
logger.exception("prometheus instant query failed")
|
||||
return {"error": f"Prometheus query failed: {exc}"}
|
||||
return {"result": payload.get("data", {})}
|
||||
logger.exception("grafana gateway query failed")
|
||||
return {"error": f"Grafana query failed: {exc}"}
|
||||
|
||||
async def _fetch_chart(self, base_url: str, timeout: int, config: dict[str, Any]) -> dict[str, Any]:
|
||||
"""Range query → ``{series}`` for the chart widget (SC-101..SC-104)."""
|
||||
async def _fetch_chart(
|
||||
self, grafana_url: str, api_key: str, datasource_uid: str, timeout: int, config: dict[str, Any]
|
||||
) -> dict[str, Any]:
|
||||
"""Range query → ``{series}`` for the chart widget (GM-106)."""
|
||||
promql = config.get("promql")
|
||||
if not promql:
|
||||
return {"error": "promql is required"}
|
||||
window = WINDOW_PRESETS.get(config.get("window", "1h"), WINDOW_PRESETS["1h"])
|
||||
raw = await self._range_query(base_url, timeout, promql, window)
|
||||
raw = await self._gateway_query(grafana_url, api_key, datasource_uid, timeout, promql, window_seconds=window)
|
||||
if "error" in raw:
|
||||
return raw
|
||||
return {"series": normalize_prometheus_matrix(raw["matrix"])}
|
||||
return {"series": normalize_grafana_frames(raw)}
|
||||
|
||||
async def _fetch_gauge(self, base_url: str, timeout: int, config: dict[str, Any]) -> dict[str, Any]:
|
||||
"""Instant query → scalar for the gauge widget (SC-109, SC-110, SC-111).
|
||||
async def _fetch_gauge(
|
||||
self, grafana_url: str, api_key: str, datasource_uid: str, timeout: int, config: dict[str, Any]
|
||||
) -> dict[str, Any]:
|
||||
"""Instant query → scalar for the gauge widget (GM-107).
|
||||
|
||||
Scalar-only: a multi-series query returns an error (SC-111). Threshold
|
||||
config (``warn_at``/``crit_at``/``min``/``max``/``unit``) is passed
|
||||
through for the frontend renderer.
|
||||
Scalar-only: a multi-series query returns an error. Threshold config is
|
||||
passed through for the frontend renderer.
|
||||
"""
|
||||
raw = await self._instant_query(base_url, timeout, config.get("promql") or "")
|
||||
promql = config.get("promql") or ""
|
||||
if not promql:
|
||||
return {"error": "promql is required"}
|
||||
raw = await self._gateway_query(grafana_url, api_key, datasource_uid, timeout, promql, window_seconds=None)
|
||||
if "error" in raw:
|
||||
return raw
|
||||
result = raw["result"].get("result", [])
|
||||
if len(result) != 1:
|
||||
series = normalize_grafana_frames(raw)
|
||||
if len(series) != 1:
|
||||
return {"error": "Gauge requires a single-series query; refine your PromQL"}
|
||||
try:
|
||||
value = float(result[0]["value"][1])
|
||||
except (KeyError, IndexError, ValueError, TypeError):
|
||||
points = series[0]["points"]
|
||||
if not points:
|
||||
return {"error": "Gauge query returned no scalar value"}
|
||||
value = points[-1]["v"]
|
||||
if value is None:
|
||||
return {"error": "Gauge query returned no scalar value"}
|
||||
return {
|
||||
"value": value,
|
||||
@@ -221,36 +227,46 @@ class PrometheusWidgetSource:
|
||||
"unit": config.get("unit"),
|
||||
}
|
||||
|
||||
async def _fetch_mean(self, base_url: str, timeout: int, config: dict[str, Any]) -> dict[str, Any]:
|
||||
"""Range query → client-side mean for the mean widget (SC-112..SC-114).
|
||||
async def _fetch_mean(
|
||||
self, grafana_url: str, api_key: str, datasource_uid: str, timeout: int, config: dict[str, Any]
|
||||
) -> dict[str, Any]:
|
||||
"""Range query → client-side mean for the mean widget (GM-108).
|
||||
|
||||
Runs ``query_range`` over the configured window preset, averages all
|
||||
non-null numeric samples of the single series, and returns a scalar.
|
||||
Scalar-only: a multi-series query returns an error (SC-114).
|
||||
Runs a gateway range query over the configured window preset, averages
|
||||
all non-null numeric samples of the single series, and returns a scalar.
|
||||
Scalar-only: a multi-series query returns an error.
|
||||
"""
|
||||
promql = config.get("promql")
|
||||
if not promql:
|
||||
return {"error": "promql is required"}
|
||||
window = WINDOW_PRESETS.get(config.get("window", "1h"), WINDOW_PRESETS["1h"])
|
||||
raw = await self._range_query(base_url, timeout, promql, window)
|
||||
raw = await self._gateway_query(grafana_url, api_key, datasource_uid, timeout, promql, window_seconds=window)
|
||||
if "error" in raw:
|
||||
return raw
|
||||
result = raw["matrix"]
|
||||
if len(result) != 1:
|
||||
series = normalize_grafana_frames(raw)
|
||||
if len(series) != 1:
|
||||
return {"error": "Mean requires a single-series query; refine your PromQL"}
|
||||
points = result[0].get("values") or []
|
||||
nums: list[float] = []
|
||||
for _, v in points:
|
||||
if v in (None, "NaN", "+Inf", "-Inf"):
|
||||
continue
|
||||
try:
|
||||
nums.append(float(v))
|
||||
except (TypeError, ValueError):
|
||||
continue
|
||||
nums = [p["v"] for p in series[0]["points"] if p["v"] is not None]
|
||||
if not nums:
|
||||
return {"error": "Mean query returned no numeric samples in the window"}
|
||||
mean = sum(nums) / len(nums)
|
||||
return {"value": mean, "unit": config.get("unit")}
|
||||
return {"value": sum(nums) / len(nums), "unit": config.get("unit")}
|
||||
|
||||
async def _fetch_metric(
|
||||
self, grafana_url: str, api_key: str, datasource_uid: str, timeout: int, config: dict[str, Any]
|
||||
) -> dict[str, Any]:
|
||||
"""Instant query → ``{result}`` for the metric widget (GM-109).
|
||||
|
||||
Returns ``{result: [{label, points}]}`` — the normalized series shape.
|
||||
The frontend ``PrometheusMetricWidget`` renders the last point of each
|
||||
series.
|
||||
"""
|
||||
promql = config.get("promql") or ""
|
||||
if not promql:
|
||||
return {"error": "promql is required"}
|
||||
raw = await self._gateway_query(grafana_url, api_key, datasource_uid, timeout, promql, window_seconds=None)
|
||||
if "error" in raw:
|
||||
return raw
|
||||
return {"result": normalize_grafana_frames(raw)}
|
||||
|
||||
|
||||
class AlertmanagerWidgetSource:
|
||||
@@ -437,7 +453,7 @@ class QbittorrentWidgetSource:
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
SERVICE_ADAPTERS: dict[str, WidgetSource] = {
|
||||
"prometheus": PrometheusWidgetSource(),
|
||||
"prometheus": MetricSource(),
|
||||
"qbittorrent": QbittorrentWidgetSource(),
|
||||
"alertmanager": AlertmanagerWidgetSource(),
|
||||
"jellyfin": JellyfinWidgetSource(),
|
||||
|
||||
+16
-11
@@ -751,11 +751,15 @@ class TestPrometheusStatus:
|
||||
|
||||
def test_prometheus_status_when_unreachable(self, test_client):
|
||||
service = ServiceRecord(
|
||||
id="p1", service_type="prometheus", name="Prometheus", config={"base_url": "http://prometheus:9090"}
|
||||
id="p1",
|
||||
service_type="prometheus",
|
||||
name="Prometheus",
|
||||
config={"grafana_url": "http://grafana:3000", "datasource_uid": "prometheus"},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
with (
|
||||
patch(f"{_MON}.resolve_service_record", return_value=service),
|
||||
patch(f"{_MON}.requests.get", side_effect=Exception("refused")),
|
||||
patch(f"{_MON}.requests.post", side_effect=__import__("requests").ConnectionError("refused")),
|
||||
):
|
||||
response = test_client.get("/api/monitoring/prometheus-status")
|
||||
assert response.status_code == 200
|
||||
@@ -763,22 +767,23 @@ class TestPrometheusStatus:
|
||||
assert data["up"] is False
|
||||
assert data["error"] == "prometheus_unreachable"
|
||||
|
||||
def test_prometheus_status_returns_version(self, test_client):
|
||||
def test_prometheus_status_returns_ok(self, test_client):
|
||||
service = ServiceRecord(
|
||||
id="p1", service_type="prometheus", name="Prometheus", config={"base_url": "http://prometheus:9090"}
|
||||
id="p1",
|
||||
service_type="prometheus",
|
||||
name="Prometheus",
|
||||
config={"grafana_url": "http://grafana:3000", "datasource_uid": "prometheus"},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
health = MagicMock()
|
||||
health.raise_for_status = MagicMock()
|
||||
build_info = MagicMock()
|
||||
build_info.raise_for_status = MagicMock()
|
||||
build_info.json.return_value = {"status": "success", "data": {"version": "2.55.1"}}
|
||||
gateway_resp = MagicMock()
|
||||
gateway_resp.raise_for_status = MagicMock()
|
||||
with (
|
||||
patch(f"{_MON}.resolve_service_record", return_value=service),
|
||||
patch(f"{_MON}.requests.get", side_effect=[health, build_info]),
|
||||
patch(f"{_MON}.requests.post", return_value=gateway_resp),
|
||||
):
|
||||
response = test_client.get("/api/monitoring/prometheus-status")
|
||||
assert response.status_code == 200
|
||||
data = response.json()
|
||||
assert data["up"] is True
|
||||
assert data["version"] == "2.55.1"
|
||||
assert data["version"] == "ok"
|
||||
assert data["service_id"] == "p1"
|
||||
|
||||
@@ -6,6 +6,8 @@ import pytest
|
||||
|
||||
from media_library_viewer_api.widgets.prometheus_range import (
|
||||
WINDOW_PRESETS,
|
||||
_dedup_label,
|
||||
normalize_grafana_frames,
|
||||
normalize_prometheus_matrix,
|
||||
step_for_window,
|
||||
)
|
||||
@@ -104,3 +106,152 @@ class TestNormalizePrometheusMatrix:
|
||||
{"t": 1, "v": 3.5},
|
||||
{"t": 3, "v": None},
|
||||
]
|
||||
|
||||
|
||||
class TestDedupLabel:
|
||||
"""The shared label-dedup helper used by both normalizers (GM-104)."""
|
||||
|
||||
def test_first_use_returns_label_unchanged(self) -> None:
|
||||
seen: dict[str, int] = {}
|
||||
assert _dedup_label("value", seen) == "value"
|
||||
assert seen == {"value": 0}
|
||||
|
||||
def test_collision_appends_suffix(self) -> None:
|
||||
seen: dict[str, int] = {}
|
||||
assert _dedup_label("job=x", seen) == "job=x"
|
||||
assert _dedup_label("job=x", seen) == "job=x (1)"
|
||||
assert _dedup_label("job=x", seen) == "job=x (2)"
|
||||
|
||||
def test_different_labels_dont_collide(self) -> None:
|
||||
seen: dict[str, int] = {}
|
||||
assert _dedup_label("a", seen) == "a"
|
||||
assert _dedup_label("b", seen) == "b"
|
||||
|
||||
|
||||
class TestNormalizeGrafanaFrames:
|
||||
"""GM-104: frames normalizer recovered from 65bae95 + shared dedup."""
|
||||
|
||||
def test_empty_response(self) -> None:
|
||||
assert normalize_grafana_frames({"results": {}}) == []
|
||||
assert normalize_grafana_frames({}) == []
|
||||
|
||||
def test_single_frame_with_values(self) -> None:
|
||||
raw = {
|
||||
"results": {
|
||||
"A": {
|
||||
"frames": [
|
||||
{
|
||||
"data": {"values": [[1000, 2000], [1.5, 2.5]]},
|
||||
"schema": {"fields": [{"name": "Time"}, {"name": "Value"}]},
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
out = normalize_grafana_frames(raw)
|
||||
assert len(out) == 1
|
||||
assert out[0]["label"] == "Value"
|
||||
assert out[0]["points"] == [
|
||||
{"t": 1000, "v": 1.5},
|
||||
{"t": 2000, "v": 2.5},
|
||||
]
|
||||
|
||||
def test_display_name_takes_priority(self) -> None:
|
||||
raw = {
|
||||
"results": {
|
||||
"A": {
|
||||
"frames": [
|
||||
{
|
||||
"data": {"values": [[100, 200], [0.75, 0.80]]},
|
||||
"schema": {
|
||||
"fields": [
|
||||
{"name": "Time"},
|
||||
{
|
||||
"name": "Value",
|
||||
"labels": {"instance": "host:9100"},
|
||||
"config": {"displayName": "CPU Usage"},
|
||||
},
|
||||
]
|
||||
},
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
out = normalize_grafana_frames(raw)
|
||||
assert out[0]["label"] == "CPU Usage"
|
||||
|
||||
def test_labels_fallback_when_no_display_name(self) -> None:
|
||||
raw = {
|
||||
"results": {
|
||||
"A": {
|
||||
"frames": [
|
||||
{
|
||||
"data": {"values": [[100], [1.0]]},
|
||||
"schema": {
|
||||
"fields": [
|
||||
{"name": "Time"},
|
||||
{
|
||||
"name": "Value",
|
||||
"labels": {"__name__": "up", "instance": "h:9100"},
|
||||
},
|
||||
]
|
||||
},
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
out = normalize_grafana_frames(raw)
|
||||
assert out[0]["label"] == "instance=h:9100"
|
||||
|
||||
def test_falls_back_to_value_when_no_metadata(self) -> None:
|
||||
raw = {
|
||||
"results": {
|
||||
"A": {
|
||||
"frames": [
|
||||
{
|
||||
"data": {"values": [[100], [1.0]]},
|
||||
"schema": {"fields": [{"name": "Time"}, {}]},
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
out = normalize_grafana_frames(raw)
|
||||
assert out[0]["label"] == "value"
|
||||
|
||||
def test_dedup_collisions(self) -> None:
|
||||
raw = {
|
||||
"results": {
|
||||
"A": {
|
||||
"frames": [
|
||||
{
|
||||
"data": {"values": [[100], [1.0]]},
|
||||
"schema": {"fields": [{}, {"name": "Value"}]},
|
||||
},
|
||||
{
|
||||
"data": {"values": [[100], [2.0]]},
|
||||
"schema": {"fields": [{}, {"name": "Value"}]},
|
||||
},
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
out = normalize_grafana_frames(raw)
|
||||
labels = [s["label"] for s in out]
|
||||
assert labels == ["Value", "Value (1)"]
|
||||
|
||||
def test_skips_frames_with_insufficient_values(self) -> None:
|
||||
raw = {
|
||||
"results": {
|
||||
"A": {
|
||||
"frames": [
|
||||
{"data": {"values": [[100]]}, "schema": {"fields": []}},
|
||||
{"data": {"values": [[100], [1.0]]}, "schema": {"fields": [{}, {}]}},
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
out = normalize_grafana_frames(raw)
|
||||
assert len(out) == 1
|
||||
|
||||
@@ -117,7 +117,7 @@ def test_widget_kind_lookup():
|
||||
def test_service_config_schema_is_json_schema():
|
||||
schema = get_service_definition("prometheus").config_schema
|
||||
assert schema["type"] == "object"
|
||||
assert "base_url" in schema["properties"]
|
||||
assert "grafana_url" in schema["properties"]
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -182,7 +182,7 @@ def test_list_service_types(client):
|
||||
def test_service_type_includes_secret_and_widget_metadata(client):
|
||||
response = client.get("/api/services/types")
|
||||
prom = next(item for item in response.json() if item["service_type"] == "prometheus")
|
||||
assert [sf["key"] for sf in prom["secret_fields"]] == ["api_key"]
|
||||
assert [sf["key"] for sf in prom["secret_fields"]] == ["grafana_api_key"]
|
||||
assert set(wk["kind"] for wk in prom["widget_kinds"]) == {"metric", "chart", "gauge", "mean"}
|
||||
|
||||
|
||||
@@ -195,8 +195,8 @@ def _prometheus_payload(**overrides):
|
||||
payload = {
|
||||
"service_type": "prometheus",
|
||||
"name": "Production Prometheus",
|
||||
"config": {"base_url": "https://prometheus.example.com"},
|
||||
"secrets": {"api_key": "secret-token"},
|
||||
"config": {"grafana_url": "https://grafana.example.com", "datasource_uid": "prometheus"},
|
||||
"secrets": {"grafana_api_key": "secret-token"},
|
||||
"enabled": True,
|
||||
}
|
||||
payload.update(overrides)
|
||||
@@ -208,10 +208,10 @@ def test_create_and_list_service(client):
|
||||
assert response.status_code == 201
|
||||
created = response.json()
|
||||
assert created["service_type"] == "prometheus"
|
||||
assert created["config"]["base_url"] == "https://prometheus.example.com"
|
||||
assert created["config"]["grafana_url"] == "https://grafana.example.com"
|
||||
# Plaintext secrets are never returned.
|
||||
assert "secrets" not in created
|
||||
assert created["secrets_set"] == {"api_key": True}
|
||||
assert created["secrets_set"] == {"grafana_api_key": True}
|
||||
|
||||
response = client.get("/api/services/instances")
|
||||
assert response.status_code == 200
|
||||
@@ -242,11 +242,11 @@ def test_update_service_preserves_unsent_secrets(client):
|
||||
json={
|
||||
"service_type": "prometheus",
|
||||
"name": "Renamed Prometheus",
|
||||
"config": {"base_url": "https://prometheus.example.com", "timeout_seconds": 10},
|
||||
"config": {"grafana_url": "https://grafana.example.com", "timeout_seconds": 10},
|
||||
},
|
||||
).json()
|
||||
assert updated["name"] == "Renamed Prometheus"
|
||||
assert updated["secrets_set"] == {"api_key": True}
|
||||
assert updated["secrets_set"] == {"grafana_api_key": True}
|
||||
|
||||
|
||||
def test_update_service_can_clear_secret(client):
|
||||
@@ -256,11 +256,11 @@ def test_update_service_can_clear_secret(client):
|
||||
json={
|
||||
"service_type": "prometheus",
|
||||
"name": "Production Prometheus",
|
||||
"config": {"base_url": "https://prometheus.example.com"},
|
||||
"secrets": {"api_key": ""},
|
||||
"config": {"grafana_url": "https://grafana.example.com"},
|
||||
"secrets": {"grafana_api_key": ""},
|
||||
},
|
||||
).json()
|
||||
assert updated["secrets_set"] == {"api_key": False}
|
||||
assert updated["secrets_set"] == {"grafana_api_key": False}
|
||||
|
||||
|
||||
def test_unknown_service_type_rejected(client):
|
||||
@@ -274,7 +274,7 @@ def test_unknown_service_type_rejected(client):
|
||||
def test_invalid_config_rejected(client):
|
||||
response = client.post(
|
||||
"/api/services/instances",
|
||||
json={"service_type": "prometheus", "name": "x", "config": {"base_url": ""}},
|
||||
json={"service_type": "prometheus", "name": "x", "config": {"grafana_url": ""}},
|
||||
)
|
||||
assert response.status_code == 422
|
||||
# Force a real validation error via bad type.
|
||||
@@ -292,10 +292,10 @@ def test_service_base_url_requires_http_schema(bad_url):
|
||||
"""Every service base_url must include an http:// or https:// schema."""
|
||||
model = get_service_definition("prometheus").config_model
|
||||
with pytest.raises(ValidationError):
|
||||
model.model_validate({"base_url": bad_url, "timeout_seconds": 5})
|
||||
model.model_validate({"grafana_url": bad_url, "timeout_seconds": 5})
|
||||
|
||||
|
||||
@pytest.mark.parametrize("service_type", ["prometheus", "alertmanager", "jellyfin", "authentik", "nextcloud"])
|
||||
@pytest.mark.parametrize("service_type", ["alertmanager", "jellyfin", "authentik", "nextcloud"])
|
||||
def test_service_base_url_accepts_absolute_urls(service_type):
|
||||
model = get_service_definition(service_type).config_model
|
||||
instance = model.model_validate({"base_url": "https://example.com"})
|
||||
@@ -308,7 +308,7 @@ def test_unknown_secret_field_rejected(client):
|
||||
json={
|
||||
"service_type": "prometheus",
|
||||
"name": "x",
|
||||
"config": {"base_url": "https://prometheus.example.com"},
|
||||
"config": {"grafana_url": "https://grafana.example.com"},
|
||||
"secrets": {"password": "leak"},
|
||||
},
|
||||
)
|
||||
@@ -321,7 +321,7 @@ def test_credential_key_in_config_rejected(client):
|
||||
json={
|
||||
"service_type": "prometheus",
|
||||
"name": "x",
|
||||
"config": {"base_url": "https://prometheus.example.com", "api_key": "leak"},
|
||||
"config": {"grafana_url": "https://grafana.example.com", "api_key": "leak"},
|
||||
},
|
||||
)
|
||||
assert response.status_code == 422
|
||||
@@ -369,7 +369,7 @@ def test_delete_service_cascades_to_widgets(client, tmp_path):
|
||||
"""
|
||||
store = app.dependency_overrides[get_settings_store]()
|
||||
service = store.upsert_service(
|
||||
{"service_type": "prometheus", "name": "Prometheus", "config": {"base_url": "u"}, "enabled": True}
|
||||
{"service_type": "prometheus", "name": "Prometheus", "config": {"grafana_url": "u"}, "enabled": True}
|
||||
)
|
||||
|
||||
# Ensure the service_id column exists and seed a referencing widget.
|
||||
|
||||
+142
-107
@@ -3,6 +3,7 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from types import SimpleNamespace
|
||||
from typing import Any
|
||||
from unittest.mock import patch
|
||||
|
||||
import pytest
|
||||
@@ -42,7 +43,7 @@ def client(tmp_path):
|
||||
|
||||
|
||||
def _make_prometheus_service(client, name="Production Prometheus", **config_overrides):
|
||||
config = {"base_url": "https://prometheus.example.com"}
|
||||
config = {"grafana_url": "https://grafana.example.com", "datasource_uid": "prometheus"}
|
||||
config.update(config_overrides)
|
||||
return client.post(
|
||||
"/api/services/instances",
|
||||
@@ -302,7 +303,7 @@ def test_fetch_widget_service_disabled(client):
|
||||
json={
|
||||
"service_type": "prometheus",
|
||||
"name": service["name"],
|
||||
"config": {"base_url": "https://prometheus.example.com"},
|
||||
"config": {"grafana_url": "https://grafana.example.com", "datasource_uid": "prometheus"},
|
||||
"enabled": False,
|
||||
},
|
||||
)
|
||||
@@ -469,39 +470,45 @@ def test_jellyfin_definition_has_now_playing_widget():
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prometheus_chart_adapter_runs_range_query():
|
||||
"""SC-101: chart kind hits /api/v1/query_range and returns {series}."""
|
||||
from media_library_viewer_api.widgets.sources import PrometheusWidgetSource
|
||||
"""GM-106: chart kind hits /api/ds/query and returns {series}."""
|
||||
from media_library_viewer_api.widgets.sources import MetricSource
|
||||
|
||||
adapter = PrometheusWidgetSource()
|
||||
adapter = MetricSource()
|
||||
service = ServiceRecord(
|
||||
id="s",
|
||||
service_type="prometheus",
|
||||
name="p",
|
||||
config={"base_url": "http://p:9090", "timeout_seconds": 5},
|
||||
config={"grafana_url": "http://grafana:3000", "datasource_uid": "prometheus", "timeout_seconds": 5},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
payload = SimpleNamespace(
|
||||
raise_for_status=lambda: None,
|
||||
json=lambda: {
|
||||
"data": {
|
||||
"result": [
|
||||
{
|
||||
"metric": {"__name__": "up", "instance": "h:9100"},
|
||||
"values": [[100, "1"], [130, "1"]],
|
||||
}
|
||||
]
|
||||
"results": {
|
||||
"A": {
|
||||
"frames": [
|
||||
{
|
||||
"data": {"values": [[100, 130], [1.0, 1.0]]},
|
||||
"schema": {
|
||||
"fields": [
|
||||
{"name": "Time"},
|
||||
{"name": "Value", "labels": {"__name__": "up", "instance": "h:9100"}},
|
||||
]
|
||||
},
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
},
|
||||
)
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.get", return_value=payload) as mock_get:
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.post", return_value=payload) as mock_post:
|
||||
result = await adapter.fetch(service, "chart", {"promql": "up", "window": "1h"})
|
||||
|
||||
# query_range endpoint + window-derived start/end/step params.
|
||||
call = mock_get.call_args
|
||||
assert call.args[0].endswith("/api/v1/query_range")
|
||||
params = call.kwargs["params"]
|
||||
assert params["query"] == "up"
|
||||
assert {"start", "end", "step"}.issubset(params)
|
||||
# {series} shape with the shared normalization (label drops __name__).
|
||||
call = mock_post.call_args
|
||||
assert call.args[0].endswith("/api/ds/query")
|
||||
body = call.kwargs["json"]
|
||||
assert body["queries"][0]["expr"] == "up"
|
||||
assert body["queries"][0]["datasource"]["uid"] == "prometheus"
|
||||
assert "series" in result
|
||||
assert result["series"][0]["label"] == "instance=h:9100"
|
||||
assert result["series"][0]["points"] == [{"t": 100, "v": 1.0}, {"t": 130, "v": 1.0}]
|
||||
@@ -509,26 +516,43 @@ async def test_prometheus_chart_adapter_runs_range_query():
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prometheus_chart_adapter_requires_promql():
|
||||
from media_library_viewer_api.widgets.sources import PrometheusWidgetSource
|
||||
from media_library_viewer_api.widgets.sources import MetricSource
|
||||
|
||||
adapter = PrometheusWidgetSource()
|
||||
service = ServiceRecord(id="s", service_type="prometheus", name="p", config={"base_url": "http://p:9090"})
|
||||
adapter = MetricSource()
|
||||
service = ServiceRecord(
|
||||
id="s",
|
||||
service_type="prometheus",
|
||||
name="p",
|
||||
config={"grafana_url": "http://grafana:3000", "datasource_uid": "prometheus"},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
result = await adapter.fetch(service, "chart", {"promql": ""})
|
||||
assert result == {"error": "promql is required"}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prometheus_chart_adapter_degrades_on_http_error():
|
||||
"""SC-103: a connection error returns {error} rather than raising."""
|
||||
"""GM-103: a connection error returns {error} rather than raising."""
|
||||
import requests as req_mod
|
||||
|
||||
from media_library_viewer_api.widgets.sources import PrometheusWidgetSource
|
||||
from media_library_viewer_api.widgets.sources import MetricSource
|
||||
|
||||
adapter = PrometheusWidgetSource()
|
||||
adapter = MetricSource()
|
||||
service = ServiceRecord(
|
||||
id="s", service_type="prometheus", name="p", config={"base_url": "http://p:9090", "timeout_seconds": 2}
|
||||
id="s",
|
||||
service_type="prometheus",
|
||||
name="p",
|
||||
config={
|
||||
"grafana_url": "http://grafana:3000",
|
||||
"datasource_uid": "prometheus",
|
||||
"timeout_seconds": 2,
|
||||
},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.get", side_effect=req_mod.ConnectionError("refused")):
|
||||
with patch(
|
||||
"media_library_viewer_api.widgets.sources.requests.post",
|
||||
side_effect=req_mod.ConnectionError("refused"),
|
||||
):
|
||||
result = await adapter.fetch(service, "chart", {"promql": "up", "window": "1h"})
|
||||
assert "error" in result
|
||||
assert "failed" in result["error"].lower()
|
||||
@@ -632,7 +656,7 @@ def test_widget_reference_lifecycle(widget_ref_client):
|
||||
{
|
||||
"service_type": "prometheus",
|
||||
"name": "Prometheus",
|
||||
"config": {"base_url": "https://prometheus.example.com"},
|
||||
"config": {"grafana_url": "https://grafana.example.com", "datasource_uid": "prometheus"},
|
||||
"secrets": {"api_key": "tok"},
|
||||
"enabled": True,
|
||||
},
|
||||
@@ -690,7 +714,7 @@ def test_widget_reference_detach(widget_ref_client):
|
||||
{
|
||||
"service_type": "prometheus",
|
||||
"name": "Prometheus",
|
||||
"config": {"base_url": "https://prometheus.example.com"},
|
||||
"config": {"grafana_url": "https://grafana.example.com", "datasource_uid": "prometheus"},
|
||||
"secrets": {"api_key": "tok"},
|
||||
"enabled": True,
|
||||
},
|
||||
@@ -794,46 +818,57 @@ def test_widget_reference_update_sort_order(widget_ref_client):
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Prometheus gauge + mean adapter tests (SC-109..SC-114)
|
||||
# Prometheus gauge + mean adapter tests (GM-107..GM-108)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def _grafana_single_frame(values, labels=None, display_name=None):
|
||||
"""Build a Grafana /api/ds/query frames response for a single series."""
|
||||
field: dict[str, Any] = {"name": "Value"}
|
||||
if labels:
|
||||
field["labels"] = labels
|
||||
if display_name:
|
||||
field["config"] = {"displayName": display_name}
|
||||
return {
|
||||
"results": {
|
||||
"A": {
|
||||
"frames": [
|
||||
{
|
||||
"data": {"values": values},
|
||||
"schema": {"fields": [{"name": "Time"}, field]},
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prometheus_gauge_adapter_returns_scalar():
|
||||
"""SC-109: gauge kind hits /api/v1/query and returns {value, thresholds}."""
|
||||
from media_library_viewer_api.widgets.sources import PrometheusWidgetSource
|
||||
"""GM-107: gauge kind hits /api/ds/query and returns {value, thresholds}."""
|
||||
from media_library_viewer_api.widgets.sources import MetricSource
|
||||
|
||||
adapter = PrometheusWidgetSource()
|
||||
adapter = MetricSource()
|
||||
service = ServiceRecord(
|
||||
id="s",
|
||||
service_type="prometheus",
|
||||
name="p",
|
||||
config={"base_url": "http://p:9090", "timeout_seconds": 5},
|
||||
config={"grafana_url": "http://grafana:3000", "datasource_uid": "prometheus", "timeout_seconds": 5},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
payload = SimpleNamespace(
|
||||
raise_for_status=lambda: None,
|
||||
json=lambda: {
|
||||
"data": {
|
||||
"result": [
|
||||
{"metric": {"__name__": "cpu"}, "value": [100, "0.75"]},
|
||||
]
|
||||
}
|
||||
},
|
||||
json=lambda: _grafana_single_frame([[100], [0.75]]),
|
||||
)
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.get", return_value=payload) as mock_get:
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.post", return_value=payload) as mock_post:
|
||||
result = await adapter.fetch(
|
||||
service,
|
||||
"gauge",
|
||||
{
|
||||
"promql": "cpu_usage",
|
||||
"warn_at": 0.8,
|
||||
"crit_at": 0.95,
|
||||
"unit": "%",
|
||||
},
|
||||
{"promql": "cpu_usage", "warn_at": 0.8, "crit_at": 0.95, "unit": "%"},
|
||||
)
|
||||
call = mock_get.call_args
|
||||
assert call.args[0].endswith("/api/v1/query")
|
||||
assert call.kwargs["params"]["query"] == "cpu_usage"
|
||||
call = mock_post.call_args
|
||||
assert call.args[0].endswith("/api/ds/query")
|
||||
assert call.kwargs["json"]["queries"][0]["expr"] == "cpu_usage"
|
||||
assert result["value"] == 0.75
|
||||
assert result["warn_at"] == 0.8
|
||||
assert result["crit_at"] == 0.95
|
||||
@@ -842,28 +877,31 @@ async def test_prometheus_gauge_adapter_returns_scalar():
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prometheus_gauge_adapter_rejects_multi_series():
|
||||
"""SC-111: gauge must be scalar-only; multi-series returns error."""
|
||||
from media_library_viewer_api.widgets.sources import PrometheusWidgetSource
|
||||
"""GM-107: gauge must be scalar-only; multi-series returns error."""
|
||||
from media_library_viewer_api.widgets.sources import MetricSource
|
||||
|
||||
adapter = PrometheusWidgetSource()
|
||||
adapter = MetricSource()
|
||||
service = ServiceRecord(
|
||||
id="s",
|
||||
service_type="prometheus",
|
||||
name="p",
|
||||
config={"base_url": "http://p:9090"},
|
||||
config={"grafana_url": "http://grafana:3000", "datasource_uid": "prometheus"},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
payload = SimpleNamespace(
|
||||
raise_for_status=lambda: None,
|
||||
json=lambda: {
|
||||
"data": {
|
||||
"result": [
|
||||
{"metric": {"instance": "a"}, "value": [100, "1"]},
|
||||
{"metric": {"instance": "b"}, "value": [100, "2"]},
|
||||
]
|
||||
"results": {
|
||||
"A": {
|
||||
"frames": [
|
||||
{"data": {"values": [[100], [1.0]]}, "schema": {"fields": [{}, {"name": "A"}]}},
|
||||
{"data": {"values": [[100], [2.0]]}, "schema": {"fields": [{}, {"name": "A"}]}},
|
||||
]
|
||||
}
|
||||
}
|
||||
},
|
||||
)
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.get", return_value=payload):
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.post", return_value=payload):
|
||||
result = await adapter.fetch(service, "gauge", {"promql": "up"})
|
||||
assert "error" in result
|
||||
assert "single-series" in result["error"].lower()
|
||||
@@ -871,14 +909,15 @@ async def test_prometheus_gauge_adapter_rejects_multi_series():
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prometheus_gauge_adapter_requires_promql():
|
||||
from media_library_viewer_api.widgets.sources import PrometheusWidgetSource
|
||||
from media_library_viewer_api.widgets.sources import MetricSource
|
||||
|
||||
adapter = PrometheusWidgetSource()
|
||||
adapter = MetricSource()
|
||||
service = ServiceRecord(
|
||||
id="s",
|
||||
service_type="prometheus",
|
||||
name="p",
|
||||
config={"base_url": "http://p:9090"},
|
||||
config={"grafana_url": "http://grafana:3000", "datasource_uid": "prometheus"},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
result = await adapter.fetch(service, "gauge", {"promql": ""})
|
||||
assert result == {"error": "promql is required"}
|
||||
@@ -886,30 +925,22 @@ async def test_prometheus_gauge_adapter_requires_promql():
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prometheus_mean_adapter_computes_average():
|
||||
"""SC-112: mean kind averages non-null values over the window."""
|
||||
from media_library_viewer_api.widgets.sources import PrometheusWidgetSource
|
||||
"""GM-108: mean kind averages non-null values over the window."""
|
||||
from media_library_viewer_api.widgets.sources import MetricSource
|
||||
|
||||
adapter = PrometheusWidgetSource()
|
||||
adapter = MetricSource()
|
||||
service = ServiceRecord(
|
||||
id="s",
|
||||
service_type="prometheus",
|
||||
name="p",
|
||||
config={"base_url": "http://p:9090", "timeout_seconds": 5},
|
||||
config={"grafana_url": "http://grafana:3000", "datasource_uid": "prometheus", "timeout_seconds": 5},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
payload = SimpleNamespace(
|
||||
raise_for_status=lambda: None,
|
||||
json=lambda: {
|
||||
"data": {
|
||||
"result": [
|
||||
{
|
||||
"metric": {"__name__": "cpu"},
|
||||
"values": [[100, "1.0"], [130, "2.0"], [160, "3.0"]],
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
json=lambda: _grafana_single_frame([[100, 130, 160], [1.0, 2.0, 3.0]]),
|
||||
)
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.get", return_value=payload):
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.post", return_value=payload):
|
||||
result = await adapter.fetch(service, "mean", {"promql": "cpu", "window": "1h"})
|
||||
assert result["value"] == 2.0
|
||||
assert result["unit"] is None
|
||||
@@ -917,28 +948,31 @@ async def test_prometheus_mean_adapter_computes_average():
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prometheus_mean_adapter_rejects_multi_series():
|
||||
"""SC-114: mean must be scalar-only; multi-series returns error."""
|
||||
from media_library_viewer_api.widgets.sources import PrometheusWidgetSource
|
||||
"""GM-108: mean must be scalar-only; multi-series returns error."""
|
||||
from media_library_viewer_api.widgets.sources import MetricSource
|
||||
|
||||
adapter = PrometheusWidgetSource()
|
||||
adapter = MetricSource()
|
||||
service = ServiceRecord(
|
||||
id="s",
|
||||
service_type="prometheus",
|
||||
name="p",
|
||||
config={"base_url": "http://p:9090"},
|
||||
config={"grafana_url": "http://grafana:3000", "datasource_uid": "prometheus"},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
payload = SimpleNamespace(
|
||||
raise_for_status=lambda: None,
|
||||
json=lambda: {
|
||||
"data": {
|
||||
"result": [
|
||||
{"metric": {"instance": "a"}, "values": [[100, "1"]]},
|
||||
{"metric": {"instance": "b"}, "values": [[100, "2"]]},
|
||||
]
|
||||
"results": {
|
||||
"A": {
|
||||
"frames": [
|
||||
{"data": {"values": [[100], [1.0]]}, "schema": {"fields": [{}, {"name": "A"}]}},
|
||||
{"data": {"values": [[100], [2.0]]}, "schema": {"fields": [{}, {"name": "A"}]}},
|
||||
]
|
||||
}
|
||||
}
|
||||
},
|
||||
)
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.get", return_value=payload):
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.post", return_value=payload):
|
||||
result = await adapter.fetch(service, "mean", {"promql": "up", "window": "1h"})
|
||||
assert "error" in result
|
||||
assert "single-series" in result["error"].lower()
|
||||
@@ -946,45 +980,46 @@ async def test_prometheus_mean_adapter_rejects_multi_series():
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prometheus_mean_adapter_skips_nan_values():
|
||||
"""SC-112: NaN / Inf values are excluded from the mean computation."""
|
||||
from media_library_viewer_api.widgets.sources import PrometheusWidgetSource
|
||||
"""GM-108: NaN values are excluded from the mean computation."""
|
||||
from media_library_viewer_api.widgets.sources import MetricSource
|
||||
|
||||
adapter = PrometheusWidgetSource()
|
||||
adapter = MetricSource()
|
||||
service = ServiceRecord(
|
||||
id="s",
|
||||
service_type="prometheus",
|
||||
name="p",
|
||||
config={"base_url": "http://p:9090"},
|
||||
config={"grafana_url": "http://grafana:3000", "datasource_uid": "prometheus"},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
# Grafana frames shape with NaN — normalize_grafana_frames converts string "NaN" to None
|
||||
payload = SimpleNamespace(
|
||||
raise_for_status=lambda: None,
|
||||
json=lambda: {
|
||||
"data": {
|
||||
"result": [
|
||||
{
|
||||
"metric": {},
|
||||
"values": [[100, "2.0"], [130, "NaN"], [160, "4.0"]],
|
||||
}
|
||||
]
|
||||
"results": {
|
||||
"A": {
|
||||
"frames": [
|
||||
{"data": {"values": [[100, 130, 160], [2.0, "NaN", 4.0]]}, "schema": {"fields": [{}, {}]}}
|
||||
]
|
||||
}
|
||||
}
|
||||
},
|
||||
)
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.get", return_value=payload):
|
||||
with patch("media_library_viewer_api.widgets.sources.requests.post", return_value=payload):
|
||||
result = await adapter.fetch(service, "mean", {"promql": "up", "window": "1h"})
|
||||
# (2.0 + 4.0) / 2 = 3.0 (NaN excluded)
|
||||
assert result["value"] == 3.0
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prometheus_mean_adapter_requires_promql():
|
||||
from media_library_viewer_api.widgets.sources import PrometheusWidgetSource
|
||||
from media_library_viewer_api.widgets.sources import MetricSource
|
||||
|
||||
adapter = PrometheusWidgetSource()
|
||||
adapter = MetricSource()
|
||||
service = ServiceRecord(
|
||||
id="s",
|
||||
service_type="prometheus",
|
||||
name="p",
|
||||
config={"base_url": "http://p:9090"},
|
||||
config={"grafana_url": "http://grafana:3000", "datasource_uid": "prometheus"},
|
||||
secrets={"grafana_api_key": "key"},
|
||||
)
|
||||
result = await adapter.fetch(service, "mean", {"promql": ""})
|
||||
assert result == {"error": "promql is required"}
|
||||
|
||||
Reference in New Issue
Block a user