Introduction
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.
Note
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 Version.
Metrics
| OpsRamp Metric | Metric Display Name | Unit | Aggregation Type | Description |
|---|---|---|---|---|
| google_ml_prediction_error_count | Error count | Count | Average | Cumulative count of prediction errors. |
| google_ml_prediction_latencies | Latency | Count | Average | Latency of a certain type. |
| google_ml_prediction_prediction_count | Prediction count | Count | Average | Cumulative count of predictions. |
| google_ml_prediction_response_count | Response count | Count | Average | Cumulative count of different response codes. |
Event support
- Supported
- Configurable in OpsRamp Google Integration Discovery Profile.