Azure Monitor cannot see a YouTube stream by itself. To alert when an always-on stream stops receiving input, run a monitor that polls YouTube’s Live Streaming API, sends timestamped observations to Azure Monitor, and use a scheduled log alert to detect an inactive or error state. Add a separate freshness alert so a failed monitor or ingestion path does not silently leave you without updates.
Decide what “stops” means for your stream
YouTube exposes several signals that describe different things. Choose the failure you want to act on before configuring Azure alerts:
- Incoming encoder data: the YouTube
liveStreamresource’sstatus.streamStatusdescribes the input stream. YouTube documents values includingactive,created,error,inactive, andready. In particular,inactivemeans YouTube is not receiving data via the stream. See Google’s LiveStreams resource documentation. - Stream health and configuration:
status.healthStatusis a separate diagnostic signal, not another name for active/inactive. It can reportgood,ok,bad, ornoData, with an update time and configuration issues. Issues have severities such asinfo,warning, anderror; YouTube says an error-severity issue means the video cannot be broadcast to viewers. Decide whether warnings should notify you before an outage. - Broadcast event lifecycle: a
liveBroadcastresource’sstatus.lifeCycleStatusdescribes the event lifecycle, such as whether the broadcast is scheduled, live, or ended. It does not directly answer whether encoder input is arriving. See Google’s LiveBroadcasts resource documentation. - Monitoring-path health: a heartbeat or timestamped observation lets you detect that the poller or ingestion path has stopped reporting. Without this condition, an alert that only looks for an explicit inactive state can miss the monitoring failure itself.
Confirm which API resource and stream or broadcast identifier correspond to your actual YouTube setup. An encoder status is not proof that every viewer can play the stream, and Azure does not automatically inspect viewer playback.
Connect YouTube status to Azure Monitor
There is no ready-made YouTube-to-Azure connector established in the official documentation cited here. The following is a reference architecture assembled from YouTube’s API fields and Microsoft’s documented ingestion and alert features; you must operate the polling and data-delivery components.
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- Poll the YouTube Live Streaming API. Have a monitor retrieve the relevant
liveStreamresource and readstatus.streamStatusandstatus.healthStatus. If you also care about whether the event is scheduled, live, or ended, retrieve and evaluate the relevantliveBroadcastseparately. Choose polling cadence in light of your API limits and operational tolerance; no universally safe interval or stop-detection time is established here. - Emit a timestamped observation. Include the observation time, stream ID, channel or broadcast ID as appropriate, stream status, health status, health update time, and a monitor heartbeat. These fields are a practical queryable record shape, not a schema mandated by YouTube or Azure. Preserve observation time so alert queries can distinguish a current state from stale data.
- Create a custom Log Analytics table and data collection rule. Configure the table and DCR for the JSON structure you intend to send. The DCR can route and transform the data. Microsoft’s Logs Ingestion API overview describes sending JSON from an application through REST or client libraries. The application needs an app registration with access to the DCR.
- Send observations using the Logs Ingestion API. The monitoring application makes the REST call or uses a client library to submit records matching the DCR’s expected input. Verify that records are arriving in the intended custom table before building alerts.
- Create scheduled-query log alerts. Use KQL against the ingested observations to detect explicit unhealthy states and stale or missing observations. Microsoft describes log alert behavior in Types of Azure Monitor alerts. Build the query around your actual custom table and column names rather than copying a query that assumes a schema you have not created.
- Attach an action group. Configure email or an automated action such as an Azure Function, Logic App, or webhook for the alert. Action groups are the delivery mechanism, not the status detector.
Design alert conditions for outages and silent failures
Alert on explicit input failure
For an input-stop page, make the query identify the latest relevant observation for each monitored stream and trigger when streamStatus is inactive or error. Do not confuse a broadcast’s ended lifecycle with an encoder-input failure; decide which one should page and query the corresponding resource.
Alert when observations go stale
Use the observation timestamp or heartbeat to detect that no fresh record has arrived within your chosen timeout. A stale stream record can point to a stopped poller, expired credentials, a network problem, or failed ingestion rather than a YouTube input transition. Treat this as its own alert condition, so the monitoring system can report that it has lost visibility.
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Optionally warn on health issues
If you want early warning as well as outage notification, query health status and configuration issues separately. A warning or a bad health signal can merit investigation without necessarily meeting your definition of a stopped input.
Set the timeout and evaluation cadence based on your service’s tolerance, polling schedule, ingestion delay, and alert evaluation interval. A single late record should not automatically be treated as a confirmed outage without accounting for those delays. The cited Microsoft documentation does not establish an end-to-end alert latency guarantee for a particular channel or configuration. Test both failure and recovery behavior with controlled cases before relying on the alert.
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Choose between log alerts and a metric heartbeat
Log alerts suit observations that need KQL logic—for example, combining the latest stream state with health details and a freshness check. If the essential condition is simply that a monitor heartbeat has disappeared, a custom metric and metric alert may be a better fit. Microsoft cautions that log alerts can be more latent for absence detection; see its guidance on alert types.
| Approach | Useful when | Trade-off |
|---|---|---|
| Log Analytics observations and scheduled-query alert | You need KQL over stream state, health details, and timestamps. | Requires a custom table, DCR, ingestion, and query evaluation; evaluation frequency affects latency and cost. |
| Custom metric heartbeat and metric alert | The key question is whether the monitoring process is still reporting. | Requires publishing and alerting on a metric; Microsoft describes metric-alert costs as based on time series. |
Actual detection time includes API polling, ingestion, query or metric evaluation, and action delivery. Costs depend on the chosen alert type, evaluation frequency, time series, data volume, and Azure region. Check current Azure pricing for your deployment rather than assuming a universal amount.
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Configure notification delivery safely
For a person who needs to respond, email may be enough. For a workflow, action groups can invoke Azure Functions, Logic Apps, webhooks, and other supported actions. Microsoft’s action group documentation explains delivery options and retry behavior.
For integrations, ensure the receiver understands the payload schema and authentication method. Consider enabling the common alert schema for standardized essentials, context, and custom properties across supported alert types. A secure webhook uses Microsoft Entra ID; basic authentication is not supported. Microsoft recommends Logic Apps when a destination needs a different schema.
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Action delivery is not infallible: Microsoft documents webhook retries with delays of 5, 20, 5, 40, and 5 seconds, followed by a 15-minute period in which the action group does not call the endpoint after retries fail. Make the receiving endpoint resilient and monitor the notification integration as well as the stream.
Validate the full detection and recovery path
- Confirm that the API monitor can authenticate and is reading the intended stream and broadcast identifiers.
- Check that normal observations arrive in the custom table with timestamps and the expected status fields.
- Test a controlled input interruption and verify that the inactive or error condition triggers the intended alert.
- Test a stopped poller or blocked ingestion path and verify that the freshness condition fires independently.
- Restore input and confirm the alert resolves or returns to normal in the way your on-call process expects.
- Test action-group delivery and the receiver’s handling of authentication, schema, retries, and duplicate or delayed notifications.
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