Azure Stream Analytics Job Builder

MonitoringAzure

Build Stream Analytics job configs with IoT Hub/Event Hub inputs, SQL-like queries, tumbling windows, and multi-output routing.

Azure Stream Analytics Configuration

Build Stream Analytics job configs with IoT Hub/Event Hub inputs, SQL-like queries, tumbling windows, reference data joins, and multi-output routing.

Required Fields

jobNameresourceGroupstreamingUnitsinputsoutputsquery

{
  "jobName": "asa-iot-telemetry-processor",
  "resourceGroup": "rg-streaming",
  "location": "eastus2",
  "sku": "Standard",
  "streamingUnits": 6,
  "compatibilityLevel": "1.2",
  "eventsOutOfOrderPolicy": "Adjust",
  "eventsOutOfOrderMaxDelayInSeconds": 10,
  "eventsLateArrivalMaxDelayInSeconds": 60,
  "inputs": [
    {
      "name": "iot-telemetry-input",
      "type": "Stream",
      "source": "IoTHub",
      "properties": {
        "iotHubNamespace": "iot-contoso-prod",
        "sharedAccessPolicyName": "service",
        "consumerGroupName": "$Default",
        "endpoint": "messages/events"
      },
      "serialization": {
        "type": "Json",
        "encoding": "UTF8"
      }
    },
    {
      "name": "device-metadata-ref",
      "type": "Reference",
      "source": "BlobStorage",
      "properties": {
        "storageAccountName": "stcontosorefdata",
        "containerName": "reference-data",
        "pathPattern": "devices/{date}/{time}/devices.json",
        "dateFormat": "yyyy-MM-dd",
        "timeFormat": "HH-mm",
        "refreshInterval": "PT1H"
      },
      "serialization": {
        "type": "Json",
        "encoding": "UTF8"
      }
    }
  ],
  "outputs": [
    {
      "name": "alerts-output",
      "destination": "ServiceBusQueue",
      "properties": {
        "serviceBusNamespace": "sbns-contoso-prod",
        "queueName": "telemetry-alerts",
        "propertyColumns": ["severity", "deviceId"]
      },
      "serialization": {
        "type": "Json",
        "encoding": "UTF8",
        "format": "LineSeparated"
      }
    },
    {
      "name": "aggregated-output",
      "destination": "CosmosDB",
      "properties": {
        "accountId": "cosmos-contoso-telemetry",
        "database": "telemetry-db",
        "collectionNamePattern": "aggregated-metrics",
        "partitionKey": "deviceId",
        "documentId": "windowEnd"
      }
    },
    {
      "name": "archive-output",
      "destination": "BlobStorage",
      "properties": {
        "storageAccountName": "stcontosoarchive",
        "containerName": "telemetry-archive",
        "pathPattern": "{date}/{time}",
        "dateFormat": "yyyy-MM-dd",
        "timeFormat": "HH",
        "minRowsPerFile": 10000,
        "maxWaitTime": "PT5M"
      },
      "serialization": {
        "type": "Parquet"
      }
    }
  ],
  "query": "-- Aggregate telemetry into 5-minute windows\nWITH TelemetryWithMetadata AS (\n    SELECT\n        t.deviceId,\n        t.temperature,\n        t.humidity,\n        t.pressure,\n        d.location,\n        d.deviceType,\n        t.EventEnqueuedUtcTime as eventTime\n    FROM [iot-telemetry-input] t\n    JOIN [device-metadata-ref] d ON t.deviceId = d.deviceId\n)\n\n-- Alert on temperature anomalies\nSELECT\n    deviceId,\n    'HighTemperature' as alertType,\n    'critical' as severity,\n    AVG(temperature) as avgTemp,\n    MAX(temperature) as maxTemp,\n    System.Timestamp() as windowEnd\nINTO [alerts-output]\nFROM TelemetryWithMetadata\nGROUP BY deviceId, TumblingWindow(minute, 5)\nHAVING AVG(temperature) > 85\n\n-- Write aggregated metrics to Cosmos DB\nSELECT\n    deviceId,\n    AVG(temperature) as avgTemperature,\n    AVG(humidity) as avgHumidity,\n    COUNT(*) as readingCount,\n    System.Timestamp() as windowEnd\nINTO [aggregated-output]\nFROM TelemetryWithMetadata\nGROUP BY deviceId, TumblingWindow(minute, 5)\n\n-- Archive raw data to blob\nSELECT *\nINTO [archive-output]\nFROM [iot-telemetry-input]"
}

Generated Output

Output will appear here...

How It Helps

Build Stream Analytics job configs with IoT Hub/Event Hub inputs, SQL-like queries, tumbling windows, and multi-output routing. This tool helps Azure engineers generate valid configurations quickly without consulting documentation, reducing errors and accelerating infrastructure deployment. All processing runs in your browser with no data sent to external servers.

Things Engineers Ask

Can the output of this Stream Analytics Job builder be checked into source control safely?

Yes. The output is plain text containing only configuration — no Azure credentials, subscription IDs (unless you typed them), or secrets are included. Treat it like any other infrastructure-as-code artifact: review in pull requests, gate on validation, apply via your change process.

Does this Stream Analytics Job builder consider the RBAC role needed to apply the configuration?

No — generating a Stream Analytics Job configuration is independent of the role required to apply it. Apply the output with a principal that has the documented permissions for that service. For least-privilege scoping, Azure's built-in roles and the Privileged Identity Management 'just enough access' workflows give you a starting point.

Practical Applications

1Replacing a hand-edited Stream Analytics Job resource with a clean, reviewable version that lives in source control going forward.
2Sketching a Stream Analytics Job migration from one Azure subscription to another with subscription and resource-group differences called out.
3Pre-flighting a Stream Analytics Job change against a change-management ticket so the implementation matches what was approved.
4Building a Stream Analytics Job reference implementation for a partner integration where you cannot rely on their portal access.

Related Learning Guides

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Disclaimer: This tool runs entirely in your browser. No data is sent to our servers. Always verify outputs before using them in production. AWS, Azure, and GCP are trademarks of their respective owners.