Metrics

Lumeo Metrics allows you to monitor and track resource utilization on gateways by exporting them via OpenTelemetry.

Background

Lumeo Gateways can export host and performance metrics, and Events using OpenTelemetry.

Available Metrics

Gateway Metrics

Device-specific metrics.

NameDescriptionUnitAttributesInstrument typeNotes
system.cpu.load_average.15m
system.cpu.load_average.1m
system.cpu.load_average.5m
system.cpu.time
system.disk.io
system.disk.io_time
system.disk.merged
system.disk.operation_time
system.disk.operations
system.disk.pending_operations
system.disk.weighted_io_time
system.filesystem.inodes.usage
system.filesystem.usage
system.memory.usage
system.network.connections
system.network.dropped
system.network.errors
system.network.io
system.network.packets
system.paging.faults
system.paging.operations
system.paging.usage
system.processes.count
system.processes.created

Deployment Metrics

Performance metrics for each Pipeline Deployment that is running on the Gateway.

NameDescriptionUnitAttributesInstrument typeNotes
lumeo.deployment.run_timeDeployment run timems- gateway_id
- deployment_id
- pipeline_id
Counter
lumeo.deployment.input_framesFrames produced by all input nodes{frames}- gateway_id
- deployment_id
- pipeline_id
Counter
lumeo.deployment.output_framesFrames consumed by all output nodes (Clip, Snapshot, WebRTC, …){frames}- gateway_id
- deployment_id
- pipeline_id
Counter
lumeo.deployment.restart_countHow many times the deployment has been restarted automatically{restarts}- gateway_id
- deployment_id
- pipeline_id
Counter
lumeo.deployment.process.cpu.utilizationCPU utilization by deployment process1- gateway_id
- deployment_id
- pipeline_id
- state : system | user | wait
GaugeThis metric duplicates process metrics, but it is easier to use if deployment ID is attached
lumeo.deployment.process.memory.usageThe amount of physical memory in use by this deployment.By- gateway_id
- deployment_id
- pipeline_id
UpDownCounter
lumeo.deployment.process.memory.virtualThe amount of committed virtual memory by this deployment.By- gateway_id
- deployment_id
- pipeline_id
UpDownCounter

Node Metrics

NameDescriptionUnitAttributesInstrument typeNotes
lumeo.deployment.node.frames_passedFrames passed through the node{frames}- gateway_id
- deployment_id
- pipeline_id
- node_id
- node_type
Counter
lumeo.deployment.node.frames_droppedFrames dropped by this node{frames}- gateway_id
- deployment_id
- pipeline_id
- node_id
- node_type
Counter
lumeo.deployment.node.latencyFor how long this node processed the frame, in microsecondsus- gateway_id
- deployment_id
- pipeline_id
- node_id
- node_type
Histogram
lumeo.deployment.node.end_to_end_latency(only for output nodes) Total frame latency from input to outputus- gateway_id
- deployment_id
- pipeline_id
- node_id
- node_type
Histogram
lumeo.deployment.node.clip.count_savedCount of clips saved by this Clip node{clips}- gateway_id
- deployment_id
- pipeline_id
- node_id
Counter
lumeo.deployment.node.snapshot.count_savedCount of snapshots saved by this Snapshot node{snapshots}- gateway_id
- deployment_id
- pipeline_id
- node_id
Counter

Configuration

Metrics can be exported using OTLP HTTP or OTLP GRPC protocol.

To configure, head to Settings -> Metrics section in Console. Then configure the endpoint that will receive the metrics, and the corresponding headers / authentication details. You will find the values in your observability software.

These settings will apply to all the Gateways in this workspace.

OTLP HTTP Endpoint Configuration

OTLP HTTP Endpoint Configuration

OTLP GRPC Endpoint Configuration

OTLP GRPC Endpoint Configuration

To verify that the setting has been sent to the gateway(s), visit Monitor -> Events section in Console. You will see the configuration events for each gateway that the configuration was successfully applied to.

Verify Metrics settings were applied by looking for `metrics.state.running` events.

Verify Metrics settings were applied by looking for metrics.state.running events.

Observability Software

This section contains a few examples of Observability software and how to set them up. Note that this is just a sample -- Lumeo supports any software that can accept metrics using OTLP HTTP or GRPC protocols.

NewRelic

This example below uses NewRelic as the observability software to view the Metrics. See NewRelic documentation for how to obtain the Metrics endpoint and configuration.

To verify that the setting has been sent to the gateway(s), you will see on the Event selection under Monitor menu option to display the configuration events for each gateway that the configuration was successfully applied to.

When query, reporting and/or creating dashboard of the data, Lumeo also provides the following dimensions to filter/report on your data.

  • Application Id
  • Deployment Id
  • Gateway Id
  • Pipeline Id

See example of FPS from output frames across 4 deployments in NewRelic.

BindPlane

BindPlane is an open source observability pipeline that gives you the ability to collect, refine, and ship metrics, logs, and traces to any destination.

To send metrics to BindPlane, first create a BindPlane configuration that specifies OTLP as a Source and the specific Destination you wish to send metrics to.

Then, assign the Configuration to a Bindplane agent.

You can now specify the OTLP endpoint in Lumeo settings as : http://<bindplane-host-ip>:4317 (GRPC) or http://<bindplane-host-ip>:4318(HTTP)