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
| New OpsRamp Metric | Google Metric | Metric Display Name | Unit | Description |
|---|---|---|---|---|
| google_ml_training_accelerator_memory_utilization | ml.googleapis.com/training/accelerator/memory/utilization | Accelerator memory utilization | % | Fraction of allocated accelerator memory that is currently in use. Values are numbers between 0.0 and 1.0, charts display the values as a percentage between 0% and 100%. Sampled every 60 seconds. After sampling, data is not visible for up to 360 seconds. |
| google_ml_training_accelerator_utilization | ml.googleapis.com/training/accelerator/utilization | Accelerator utilization | % | Fraction of allocated accelerator that is currently in use. Values are numbers between 0.0 and 1.0, charts display the values as a percentage between 0% and 100%. Sampled every 60 seconds. After sampling, data is not visible for up to 360 seconds. |
| google_ml_training_cpu_utilization | ml.googleapis.com/training/cpu/utilization | CPU utilization | % | Fraction of allocated CPU that is currently in use. Values are numbers between 0.0 and 1.0, charts display the values as a percentage between 0% and 100%. Sampled every 60 seconds. After sampling, data is not visible for up to 360 seconds. |
| google_ml_training_disk_utilization | ml.googleapis.com/training/disk/utilization | Disk bytes used | bytes | Number of bytes used by the training job. Sampled every 60 seconds. After sampling, data is not visible for up to 360 seconds. |
| google_ml_training_memory_utilization | ml.googleapis.com/training/memory/utilization | Memory utilization | % | Fraction of allocated memory that is currently in use. Values are numbers between 0.0 and 1.0, charts display the values as a percentage between 0% and 100%. Sampled every 60 seconds. After sampling, data is not visible for up to 360 seconds. |
| google_ml_training_network_received_bytes_count | ml.googleapis.com/training/network/received_bytes_count | Network bytes received | bytes | Number of bytes received by the training job over the network. Sampled every 60 seconds. After sampling, data is not visible for up to 360 seconds. |
| google_ml_training_network_sent_bytes_count | ml.googleapis.com/training/network/sent_bytes_count | Network bytes sent | bytes | Number of bytes sent by the training job over the network. Sampled every 60 seconds. After sampling, data is not visible for up to 360 seconds. |
Event support
- Supported
- Configurable in OpsRamp Google Integration Discovery Profile.