The workflow enables the curated visualizations and alerts functionality even for metrics arriving via this optional path. The workflow processes messages arriving from the metrics-collector module and sends them to the Log Analytics workspace. When metrics are routed via IoT Hub, a (one-time) cloud workflow needs to be set up. It also enables monitoring of child IoT Edge devices in a nested configuration where child devices can only access their parent device. This option unlocks monitoring of locked-down IoT Edge devices that are allowed external access to only the IoT Hub endpoint. ![]() 1 The collector module can be configured to send the collected metrics as UTF-8 encoded JSON device-to-cloud messages via the edgeHub module. This approach also allows multiple IoT hubs to safely share a single Log Analytics workspace as a metrics database. As a result, the curated IoT Edge workbook templates can retrieve metrics by issuing queries against the resource. This association automatically links the metric with the specified resource (for example, IoT Hub). To enable in restricted networks, see Enable in restricted network access scenarios later in this article.Įach metric entry contains the ResourceId that was specified as part of module configuration. The Log Analytics workspace ID and key must be specified as part of the module configuration. This option requires access to the workspace on outbound port 443. This table's schema is compatible with the Prometheus metrics data model. 1 The collected metrics are ingested into the specified Log Analytics workspace using a fixed, native table called InsightsMetrics. Option 1 sends the metrics to Log Analytics. You have two options for sending metrics from the metrics-collector module to the cloud. For more information, see metrics collector configuration section later in this article. Collection frequency, endpoints, and filters can be configured to control the data egressed from the module. ![]() The metrics-collector module is a Microsoft-supplied IoT Edge module that collects workload module metrics and transports them off-device. Learn how to instrument custom modules using open-source libraries in the Add custom metrics article. ![]() While built-in metrics enable broad workload visibility by default, custom modules can also be used to emit scenario-specific metrics to enhance the monitoring solution. All modules must emit metrics using the Prometheus data model.
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