Machine learning (ML) is a subfield of artificial intelligence (AI). The goal of ML is to make computers learn from the data that you give them. Instead of writing code that describes the action the computer should take, your code provides an algorithm that adapts based on examples of intended behavior. The resulting program, consisting of the algorithm and associated learned parameters, is called a trained model.

Use the OpsRamp Google public cloud integration to discover and collect metrics against the Google service.

Setup

To set up the OpsRamp Google integration and discover the Google service, go to Google Integration Discovery Profile and select Ml JOB.

Metrics

OpsRamp MetricMetric Display NameUnitAggregation Type
google_ml_training_cpu_utilization

Fraction of the allocated CPU that is currently in use.
CPU utilizationCountAverage
google_ml_training_memory_utilization

Fraction of the allocated memory that is currently in use.
Memory utilizationCountAverage
google_ml_training_accelerator_utilization

Fraction of the allocated accelerator that is currently in use.
Accelerator utilizationCountAverage
google_ml_training_accelerator_memory_utilization

Fraction of the allocated accelerator memory that is currently in use.
Accelerator memory utilizationCountAverage
google_ml_training_network_received_bytes_count

Number of bytes received by the training job over the network.
Network bytes receivedBytesAverage
google_ml_training_network_sent_bytes_count

Number of bytes sent by the training job over the network.
Network bytes sentBytesAverage

Event support

  • Supported
  • Configurable in OpsRamp Google Integration Discovery Profile.

External reference