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.
To set up the Google integration to discover and collect metrics against the Google service.
Setup
To set up the Google integration and discover the Google service,
go to Google Integration Discovery Profile and select Ml JOB.
Supported metrics
| OpsRamp Metric | Metric Display Name | Unit | Aggregation Type |
|---|---|---|---|
| google_ml_training_cpu_utilization Fraction of the allocated CPU that is currently in use. | CPU utilization | Count | Average |
| google_ml_training_memory_utilization Fraction of the allocated memory that is currently in use. | Memory utilization | Count | Average |
| google_ml_training_accelerator_utilization Fraction of the allocated accelerator that is currently in use. | Accelerator utilization | Count | Average |
| google_ml_training_accelerator_memory_utilization Fraction of the allocated accelerator memory that is currently in use. | Accelerator memory utilization | Count | Average |
| google_ml_training_network_received_bytes_count Number of bytes received by the training job over the network. | Network bytes received | Bytes | Average |
| google_ml_training_network_sent_bytes_count Number of bytes sent by the training job over the network. | Network bytes sent | Bytes | Average |
Event support
- Supported
- Configurable in OpsRamp Google Integration Discovery Profile.