40-clients/ucepsa/edge-oee-demo/ops/deploy_context_regression_dashboard_v0313.sh

#!/usr/bin/env bash
set -euo pipefail

ACTION="${1:-deploy}"
GRAFANA_CONTAINER="${GRAFANA_CONTAINER:-mv_ucepsa_grafana}"
REPO_ROOT="${REGRESSION_DASHBOARD_REPO_ROOT:-/srv/mesavault/40-clients/ucepsa/edge-oee-demo}"
DASHBOARD_FILE="${REGRESSION_DASHBOARD_FILE:-$REPO_ROOT/grafana/dashboards/ucepsa-shopfloor-context-health.dashboard.json}"
FOLDER_UID="${REGRESSION_DASHBOARD_FOLDER_UID:-ucepsa-mesavault}"
DASHBOARD_UID="ucepsa-shopfloor-context-health"
DATASOURCE_UID="bfnbcasbm6hhca"

resolve_url() {
    if [[ -n "${GRAFANA_URL:-}" ]]; then
        printf '%s' "$GRAFANA_URL"
        return
    fi

    local port_line host_port container_ip
    port_line="$(
        docker port "$GRAFANA_CONTAINER" 3000/tcp 2>/dev/null \
          | head -n 1 || true
    )"

    if [[ -n "$port_line" ]]; then
        host_port="${port_line##*:}"
        printf 'http://127.0.0.1:%s' "$host_port"
        return
    fi

    container_ip="$(
        docker inspect "$GRAFANA_CONTAINER" \
          --format '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}'
    )"

    if [[ -z "$container_ip" ]]; then
        echo "ERROR: no se pudo resolver Grafana." >&2
        exit 1
    fi

    printf 'http://%s:3000' "$container_ip"
}

if [[ -z "${GRAFANA_API_TOKEN:-}" ]]; then
    echo "ERROR: falta GRAFANA_API_TOKEN." >&2
    exit 1
fi

export GRAFANA_URL_RESOLVED
GRAFANA_URL_RESOLVED="$(resolve_url)"

python3 - \
  "$ACTION" \
  "$DASHBOARD_FILE" \
  "$FOLDER_UID" \
  "$DASHBOARD_UID" \
  "$DATASOURCE_UID" <<'PY'
import json
import os
import sys
import urllib.error
import urllib.parse
import urllib.request

action, dashboard_file, folder_uid, dashboard_uid, datasource_uid = sys.argv[1:]
base_url = os.environ["GRAFANA_URL_RESOLVED"].rstrip("/")
token = os.environ["GRAFANA_API_TOKEN"]


def request(method, path, payload=None):
    body = None
    headers = {
        "Accept": "application/json",
        "Authorization": f"Bearer {token}",
    }

    if payload is not None:
        body = json.dumps(
            payload,
            ensure_ascii=False,
        ).encode("utf-8")
        headers["Content-Type"] = "application/json"

    req = urllib.request.Request(
        base_url + path,
        data=body,
        headers=headers,
        method=method,
    )

    try:
        with urllib.request.urlopen(
            req,
            timeout=20,
        ) as response:
            raw = response.read()
            return (
                json.loads(raw.decode("utf-8"))
                if raw
                else None
            )
    except urllib.error.HTTPError as exc:
        detail = exc.read().decode(
            "utf-8",
            errors="replace",
        )
        raise RuntimeError(
            f"Grafana API {method} {path}: "
            f"HTTP {exc.code}: {detail}"
        ) from exc


health = request("GET", "/api/health")
if not health or health.get("database") != "ok":
    raise RuntimeError(
        f"Grafana no está saludable: {health!r}"
    )

if action == "deploy":
    with open(
        dashboard_file,
        encoding="utf-8",
    ) as handle:
        dashboard = json.load(handle)

    result = request(
        "POST",
        "/api/dashboards/db",
        {
            "dashboard": dashboard,
            "folderUid": folder_uid,
            "overwrite": True,
            "message": (
                "MESAVAULT regression hardening "
                "SHADOW v0.3.13"
            ),
        },
    )
    print(json.dumps(
        {
            "status": "deployed",
            "dashboard_uid": dashboard_uid,
            "folder_uid": folder_uid,
            "response": result,
        },
        ensure_ascii=False,
        indent=2,
    ))

elif action == "validate":
    result = request(
        "GET",
        "/api/dashboards/uid/"
        + urllib.parse.quote(dashboard_uid),
    )
    dashboard = result["dashboard"]
    panels = {
        panel.get("id"): panel
        for panel in dashboard.get("panels", [])
    }

    datasource_uids = sorted({
        panel.get("datasource", {}).get("uid")
        for panel in dashboard.get("panels", [])
        if isinstance(
            panel.get("datasource"),
            dict,
        )
        and panel.get(
            "datasource",
            {},
        ).get("uid")
    })

    errors = []

    if len(dashboard.get("panels", [])) != 31:
        errors.append(
            "El dashboard no tiene 31 paneles"
        )

    if dashboard.get("refresh") != "15s":
        errors.append(
            "El refresco no está en 15s"
        )

    if datasource_uids != [datasource_uid]:
        errors.append(
            f"Datasource inesperado: {datasource_uids!r}"
        )

    expected = {
        29: "li_context_regression_latest_run_v1",
        30: "li_context_regression_failures_v1",
        31: "li_context_regression_run_history_v1",
    }

    for panel_id, fragment in expected.items():
        sql = (
            panels.get(panel_id, {})
            .get("targets", [{}])[0]
            .get("rawSql", "")
        )
        if fragment not in sql:
            errors.append(
                f"Panel {panel_id} no consulta {fragment}"
            )

    output = {
        "status":
            "ok" if not errors else "error",
        "dashboard_uid":
            dashboard.get("uid"),
        "folder_uid":
            result.get(
                "meta",
                {},
            ).get("folderUid"),
        "panel_count":
            len(
                dashboard.get(
                    "panels",
                    [],
                )
            ),
        "refresh":
            dashboard.get("refresh"),
        "datasource_uids":
            datasource_uids,
        "version":
            dashboard.get("version"),
        "url":
            result.get(
                "meta",
                {},
            ).get("url"),
        "regression_panels": {
            "latest_run": 29 in panels,
            "issues": 30 in panels,
            "history": 31 in panels,
        },
        "errors":
            errors,
    }

    print(json.dumps(
        output,
        ensure_ascii=False,
        indent=2,
    ))

    if errors:
        raise SystemExit(1)

else:
    raise SystemExit(
        "Uso: deploy_context_regression_dashboard_v0313.sh "
        "{deploy|validate}"
    )
PY