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

Does this tool connect to my Azure account?

No. This tool runs entirely in your browser and generates configuration JSON that you can copy and paste into your infrastructure-as-code templates, CLI commands, or cloud console. It never connects to any cloud account or sends data externally.

Are the generated configurations production-ready?

The tool produces syntactically valid configurations based on current Azure service specifications. Always review generated configs against your organization security policies and test in a non-production environment before deploying.

Practical Applications

1Generating azure stream analytics job configurations for new infrastructure deployments.
2Validating existing configurations against best practices before applying changes.
3Learning Azure service configuration patterns through interactive examples.
4Accelerating infrastructure-as-code development by producing correct JSON/YAML starting points.

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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.