Lightup.ai is the AI-powered data observability platform that uses machine learning to automatically detect anomalies in data pipelines — monitoring row counts, nullability rates, distribution shifts, and schema changes across data warehouses like Snowflake, BigQuery, and Databricks without requiring manual threshold configuration. When the Lightup platform becomes unavailable, data teams lose real-time visibility into pipeline health and the automated anomaly alerts they rely on to catch data quality regressions before they propagate downstream. When the Lightup API is degraded, integrations with dbt, Airflow, and your data warehouse stop delivering quality signals to the pipelines that depend on them. When alert webhooks fail, Slack and PagerDuty notifications for detected anomalies stop flowing, leaving data quality incidents unacknowledged until stakeholders notice bad numbers in dashboards. Vigilmon gives you external visibility into Lightup.ai's infrastructure: the platform dashboard, the monitoring API, and your alert delivery endpoints, so you know the moment the data observability platform itself needs attention.
What You'll Build
- An HTTP monitor on the Lightup platform dashboard to detect availability failures
- A health-check monitor on the Lightup API to catch backend degradation
- A monitor on your webhook receiver to verify Lightup alert delivery is flowing
- A monitor on the Lightup notification endpoint to catch alert dispatch failures
- An SSL certificate monitor for your Lightup domain
- Alerting that distinguishes platform dashboard outages from API and webhook failures
Prerequisites
- A Lightup.ai deployment (cloud-hosted SaaS or self-managed)
- The Lightup platform dashboard accessible via HTTPS
- A webhook receiver endpoint configured to accept Lightup anomaly alerts
- A free account at vigilmon.online
Step 1: Understand Lightup.ai's Service Architecture
Lightup.ai operates as a multi-layer data observability platform with several monitorable components:
| Component | Default port | Role |
|---|---|---|
| Platform dashboard | 443 (HTTPS) | Web UI for configuring monitors, reviewing detected anomalies, and managing data sources |
| Lightup REST API | 443 (HTTPS) | Serves anomaly results, accepts configuration updates, integrates with dbt and Airflow |
| Alert dispatcher | Outbound | Delivers anomaly notifications to Slack, PagerDuty, email, and custom webhooks |
| Metric computation engine | Internal | Runs ML-powered anomaly detection jobs against connected data warehouses |
External monitoring focuses on the platform dashboard and REST API — these surface the availability of the entire Lightup deployment and are the interfaces your data engineers and pipeline integrations interact with directly.
Step 2: Monitor the Lightup Platform Dashboard
The Lightup platform dashboard is the primary interface for reviewing detected anomalies, configuring data source connections, managing monitor thresholds, and investigating data quality incidents across your warehouse tables:
curl -I https://app.lightup.ai
# Returns HTTP 200 with HTML when the frontend is healthy
- Log in to Vigilmon → Add Monitor → HTTP.
- URL:
https://app.lightup.ai(or your self-managed Lightup hostname). - Check interval: 60 seconds.
- Response timeout: 15 seconds.
- Expected status:
200. - Keyword:
Lightup(appears in the page title and HTML content). - Click Save.
This monitor catches:
- Lightup frontend deployment failures or misconfigured Nginx proxies
- Platform container restarts that leave the dashboard returning 5xx errors
- Failed Lightup upgrades that break the UI before the API is restored
- DNS resolution failures for the Lightup application domain
Alert sensitivity: Set to trigger after 1 consecutive failure. When the Lightup dashboard is unavailable, data engineers cannot investigate active anomalies, review the history of a particular metric, or acknowledge incidents — leaving the team blind to data quality issues their monitors have already detected.
Step 3: Monitor the Lightup REST API
The Lightup REST API is the backbone of all pipeline integrations — it delivers anomaly detection results to dbt Cloud, Airflow DAGs, and custom data quality gates. When the API degrades, automated quality checks embedded in your pipelines cannot query Lightup for anomaly status, and programmatic configuration updates (such as adding a new table monitor after a schema change) fail:
curl https://app.lightup.ai/api/v1/health
# Returns: {"status": "healthy"} when the API backend is operational
- Add Monitor → HTTP.
- URL:
https://app.lightup.ai/api/v1/health. - Check interval: 60 seconds.
- Response timeout: 10 seconds.
- Expected status:
200. - Keyword:
healthy(present in healthy API responses). - Label:
Lightup API health. - Click Save.
Why monitor the API separately from the dashboard? The Lightup dashboard may still render from a cached state even when the API is returning errors. A failing API means your dbt pipeline quality gates cannot query anomaly results, Airflow DAGs that block on data quality cannot proceed, and data engineers investigating an incident cannot pull fresh anomaly counts from the API.
Step 4: Monitor Your Webhook Receiver
Lightup delivers anomaly detection alerts and incident notifications to your on-call tools (Slack, PagerDuty, custom webhooks) via outbound HTTP POST requests. If your webhook receiver becomes unavailable or returns errors, notification delivery fails silently — on-call engineers stop receiving anomaly alerts and data quality regressions go unacknowledged until downstream consumers report bad data:
curl https://your-webhook-receiver.example.com/health
# Returns: {"status": "ok"} when the receiver is up
- Add Monitor → HTTP.
- URL:
https://your-webhook-receiver.example.com/health. - Check interval: 2 minutes.
- Response timeout: 10 seconds.
- Expected status:
200. - Keyword:
ok. - Label:
Lightup webhook receiver. - Click Save.
For Slack incoming webhooks, verify https://slack.com/api/api.test to confirm the Slack API is reachable for anomaly alert delivery. For PagerDuty integrations, monitor https://status.pagerduty.com/api/v2/status.json to catch PagerDuty service degradation that would block incident creation from Lightup anomalies.
Step 5: Monitor the Lightup Notification Endpoint
Lightup's internal notification endpoint controls how anomaly alerts are dispatched to configured channels. When this endpoint is degraded, Lightup may detect anomalies correctly but fail to deliver the notifications to Slack, email, or your custom webhook integrations — creating a gap between detected issues and notified engineers:
curl https://app.lightup.ai/api/v1/notifications/status
# Returns notification engine status when healthy
- Add Monitor → HTTP.
- URL:
https://app.lightup.ai/api/v1/notifications/status. - Check interval: 5 minutes.
- Response timeout: 15 seconds.
- Expected status:
200. - Keyword:
status(present in the response JSON). - Label:
Lightup notification engine. - Click Save.
Notification endpoint failures mean that Lightup's anomaly detection continues running, but no alerts reach the teams that depend on them. This is the most silent failure mode in data observability platforms — data quality issues are detected but invisible to on-call engineers until the notification system is restored.
Step 6: Monitor SSL Certificates
Lightup's platform dashboard and REST API are accessed over HTTPS by both data engineers using the UI and automated pipeline integrations that call the API. An expired certificate breaks browser access to the anomaly dashboard and causes API calls from dbt, Airflow, and CI/CD pipelines to fail with TLS errors:
openssl s_client -connect app.lightup.ai:443 2>/dev/null | openssl x509 -noout -dates
- Add Monitor → SSL Certificate.
- Domain:
app.lightup.ai(or your self-managed Lightup hostname). - Alert when expiry is within: 30 days.
- Alert again: 14 days, 7 days, 3 days, 1 day.
- Click Save.
Pipeline integration impact: Lightup API clients embedded in Airflow DAGs or dbt Cloud jobs run on automated schedules and call Lightup's API endpoints without interactive input. When the TLS certificate expires, these clients fail immediately with SSL verification errors. If the pipeline treats the Lightup quality gate as non-blocking, the job continues and data may be promoted to production without a quality check — undermining the entire purpose of the observability integration.
Step 7: Configure Alerting
In Vigilmon under Settings → Notifications, configure your alert channels:
| Monitor | Trigger | Action |
|---|---|---|
| Platform dashboard | Non-200 or Lightup missing | Check Lightup frontend deployment; review container logs |
| API health | Non-200 or healthy missing | API down; pipeline integrations failing; check Lightup status page |
| Webhook receiver | Non-200 or ok missing | On-call alerts not delivering; verify receiver deployment and logs |
| Notification engine | Non-200 or status missing | Anomalies detected but not alerted; check Lightup notification configuration |
| SSL certificate | < 30 days to expiry | Renew certificate; verify API clients reconnect after renewal |
Alert after: 1 consecutive failure for the dashboard and API health monitors. 2 consecutive failures for notification engine and webhook receiver monitors to reduce noise from transient timeouts during high-volume anomaly detection windows.
Common Lightup.ai Failure Modes and What Vigilmon Catches
| Scenario | Vigilmon monitor | |---|---| | Lightup frontend container crash | Dashboard monitor fires; engineers cannot review detected anomalies | | REST API degradation | API monitor fires; pipeline quality gates and dbt integrations fail | | Webhook receiver crash | Webhook monitor fires; Slack and PagerDuty alerts stop posting | | Notification engine failure | Notification monitor fires; anomalies detected but not alerted | | TLS certificate expired | SSL monitor alerts at 30-day threshold; browser and API clients fail | | DNS misconfiguration | All monitors fire simultaneously | | Lightup API authentication change | API monitor may fire with 401 errors; pipeline integrations need key rotation | | Metric computation backlog | Dashboard may show stale anomaly data; API responses may time out |
Monitoring Data Quality Itself (Beyond Infrastructure)
Vigilmon monitors Lightup.ai's infrastructure endpoints — the platform dashboard, REST API, notification engine, and your webhook receiver. The health of individual data quality monitors and detected anomalies is a separate concern managed within Lightup itself:
- Lightup's built-in alerting: Configure notification channels within Lightup (Slack, PagerDuty, email, custom webhooks) to route anomaly alerts to on-call teams — this is distinct from monitoring Lightup's own availability.
- Monitor coverage: Audit which tables and columns have Lightup monitors configured to ensure new data assets are covered automatically when added to your warehouse.
- Anomaly review cadence: Establish a regular review process for Lightup's anomaly feed to catch patterns that automated thresholds may not flag — particularly for business-logic anomalies that require domain context to interpret.
Vigilmon catches infrastructure-level failures — when Lightup itself is down. Individual anomaly detection coverage and data quality regressions within a healthy Lightup deployment require Lightup's own monitor configuration and alerting rules.
Lightup.ai is the layer that makes your data warehouse quality observable — when it goes down, anomaly detection stops, pipeline quality gates break, and data engineers lose the real-time visibility they rely on to catch bad data before it reaches dashboards and business reports. Vigilmon gives you external visibility into Lightup's availability that doesn't depend on Lightup self-reporting: dashboard uptime, API health, notification engine status, and SSL certificate validity, so you know the moment the data observability platform itself needs attention and can restore anomaly detection coverage before the next pipeline run ships unvalidated data downstream.
Start monitoring Lightup.ai in under 5 minutes — register free at vigilmon.online.