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Google Cloud TPU products make the benefits of Tensor Processing Units (TPUs) available through scalable and easy-to-use cloud computing resource for all ML researchers, ML engineers, developers, and data scientists running cutting-edge ML models.
Use the Datadog Google Cloud Platform integration to collect metrics from Google Cloud TPU.
If you haven’t already, set up the Google Cloud Platform integration first. There are no other installation steps.
Google Cloud TPU logs are collected with Google Cloud Logging and sent to a Dataflow job through a Cloud Pub/Sub topic. If you haven’t already, set up logging with the Datadog Dataflow template.
Once this is done, export your Google Cloud TPU logs from Google Cloud Logging to the Pub/Sub topic:
gcp.tpu.cpu.utilization (gauge) | Utilization of CPUs on the TPU Worker as a percent. Shown as percent |
gcp.tpu.memory.usage (gauge) | Memory usage in bytes. Shown as byte |
gcp.tpu.network.received_bytes_count (count) | Cumulative bytes of data this server has received over the network. Shown as byte |
gcp.tpu.network.sent_bytes_count (count) | Cumulative bytes of data this server has sent over the network. Shown as byte |
The Google Cloud TPU integration does not include any events.
The Google Cloud TPU integration does not include any service checks.
Need help? Contact Datadog support.