Show HN: TPU-doc – A zero-dependency diagnostic tool for Google Cloud TPU health (github.com)

tpu-doc is a newly launched diagnostic tool for Google Cloud TPU environments, designed to streamline the verification of TPU hardware health and configuration. This single-binary tool is significant for the AI/ML community, as it addresses a common pain point for machine learning engineers: the lack of standardized diagnostics for TPU deployments, which can waste costly compute time during debugging. By running tpu-doc before and during workloads, users can quickly validate hardware conditions, check version compatibilities, and diagnose problems that could hinder performance. With 36 validation checks spanning hardware, performance, I/O, security, and configuration, tpu-doc provides a comprehensive assessment in seconds. The tool is packaged as a self-contained binary—allowing it to run with zero dependencies—and includes optional AI-driven analysis for error logs, facilitating a quicker diagnosis of issues. Designed to be safe for production environments, it never alters system configurations or writes to files, ensuring reliability during usage. Overall, tpu-doc enhances the efficiency of TPU deployments and helps engineers avoid costly downtime associated with undetected issues.