Tensor Processing Units (TPUs) are Google custom-developed application-specific integrated circuits (ASICs) used to accelerate machine learning workloads. TPUs are designed from the ground up with the benefit of the deep Google experience and leadership in machine learning.
Cloud TPU runs your machine learning workloads on Google TPU accelerator hardware using TensorFlow. Cloud TPU is designed for maximum performance and flexibility to help researchers, developers, and businesses to build TensorFlow compute clusters that can leverage CPUs, GPUs, and TPUs. High-level Tensorflow APIs help you to get models running on the Cloud TPU hardware.
Setup
To set up the Google integration and discover the Google service,
go to Google Integration Discovery Profile and select Tpu.
Supported metrics
| OpsRamp Metric | Metric Display Name | Unit | Aggregation Type |
|---|---|---|---|
| google_tpu_cpu_utilization Utilization of CPUs on the TPU Worker as a percent. Sampled every 60 seconds. After sampling, data is not visible for up to 180 seconds. | CPU utilization | Percent | Average |
| google_tpu_memory_usage Memory usage in bytes. Sampled every 60 seconds. After sampling, data is not visible for up to 180 seconds. | Memory usage | Bytes | Average |
| google_tpu_network_received_bytes_count Cumulative bytes of data this server has received over the network. Sampled every 60 seconds. After sampling, data is not visible for up to 180 seconds. | Network bytes received | Bytes | Count |
| google_tpu_network_sent_bytes_count Cumulative bytes of data this server has sent over the network. Sampled every 60 seconds. After sampling, data is not visible for up to 180 seconds. | Network bytes sent | Bytes | Count |
Event support
- Not Supported