{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/4"}],"enrichment":{"capability":"CLI tool that detects Cloud TPU devices and reads runtime metrics from libtpu, including memory usage and duty cycle, in both static snapshot and live streaming modes.","skillfed_tags":["tpu-diagnostics","ml-infrastructure"],"use_cases":["Monitor TPU memory and compute utilization in real time while running ML training or inference workloads to identify bottlenecks.","Capture a one-time snapshot of TPU metrics for debugging or performance analysis of a specific computation.","Diagnose TPU device availability and libtpu version compatibility before launching a workload.","Track buffer transfer and gRPC latencies to optimize data pipeline performance on TPU clusters.","Stream continuous metrics during development to watch TensorCore utilization and duty cycle as you iterate on model code."],"what_it_does":"tpu-info is a command-line diagnostic tool for Google Cloud TPU environments that queries the libtpu runtime to expose hardware and performance metrics. It runs on machines with attached TPU devices and requires an active ML workload (JAX or PyTorch/XLA) to access full utilization data; without a workload, it can still detect TPU devices but will not report runtime metrics.\n\nThe tool offers two modes: a static snapshot mode that prints current metrics once, and a streaming mode that refreshes and displays metrics continuously at a configurable interval. Metrics include HBM memory usage, duty cycle, TensorCore utilization, buffer transfer latencies, host compute latency, and gRPC TCP performance. Recent versions added support for Pygrain and Orbax performance metrics from the local Prometheus server.","worth_installing":"Yes, if you work with Cloud TPU and need visibility into runtime metrics and device diagnostics. The tool is actively maintained, has no known vulnerabilities, and low install friction. It is purpose-built for TPU environments and requires an active workload to be useful; install it only if you have TPU hardware and supported ML frameworks available."},"id":"tpu-info","links":{"html":"https://skillfed.io/packages/tpu-info","md":"https://skillfed.io/packages/tpu-info.md","pypi":"https://pypi.org/project/tpu-info/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-06","license_spdx":null,"license_treatment":"permissive","name":"tpu-info","python_support":"supports_current","summary":"CLI tool to view TPU metrics"},"popularity":{"monthly_downloads":270511,"position":8234,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.14.2"}