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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.
Setup
Installation
To use Google Cloud TPU, you only need to set up the Google Cloud Platform integration.
Log collection
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:
- Go to the Google Cloud Logging page and filter the Google Cloud TPU logs.
- Click Create Export and name the sink.
- Choose “Cloud Pub/Sub” as the destination and select the Pub/Sub topic that was created for that purpose. Note: The Pub/Sub topic can be located in a different project.
- Click Create and wait for the confirmation message to show up.
Data Collected
Metrics
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 |
gcp.tpu.accelerator.duty_cycle
(count) | Percentage of time over the sample period during which the accelerator was actively processing
Shown as percent |
gcp.tpu.instance.uptime_total
(count) | Elapsed time since the VM was started, in seconds.
Shown as second |
gcp.gke.node.accelerator.tensorcore_utilization
(count) | Current percentage of the Tensorcore that is utilized.
Shown as percent |
gcp.gke.node.accelerator.duty_cycle
(count) | Percent of time over the past sample period (10s) during which the accelerator was actively processing.
Shown as percent |
gcp.gke.node.accelerator.memory_used
(count) | Total accelerator memory allocated in bytes.
Shown as byte |
gcp.gke.node.accelerator.memory_total
(count) | Total accelerator memory in bytes.
Shown as byte |
gcp.gke.node.accelerator.memory_bandwidth_utilization
(count) | Current percentage of the accelerator memory bandwidth that is being used.
Shown as percent |
gcp.gke.container.accelerator.tensorcore_utilization
(count) | Current percentage of the Tensorcore that is utilized.
Shown as percent |
gcp.gke.container.accelerator.duty_cycle
(count) | Percent of time over the past sample period (10s) during which the accelerator was actively processing.
Shown as percent |
gcp.gke.container.accelerator.memory_used
(count) | Total accelerator memory allocated in bytes.
Shown as byte |
gcp.gke.container.accelerator.memory_total
(count) | Total accelerator memory in bytes.
Shown as byte |
gcp.gke.container.accelerator.memory_bandwidth_utilization
(count) | Current percentage of the accelerator memory bandwidth that is being used.
Shown as percent |
Events
The Google Cloud TPU integration does not include any events.
Service Checks
The Google Cloud TPU integration does not include any service checks.
Troubleshooting
Need help? Contact Datadog support.
