Providing rich context for monitor alerts is an essential part of any robust, scalable monitoring strategy. Alerts that send teams scrambling for basic background information prolong troubleshooting, hindering effective incident response and heightening the potential for service disruption. Given the increasing complexity of modern, distributed applications, however, breaking down knowledge silos in order to ensure consistent access to critical context for alerts can be a challenge.

The rapidly growing interest in AI has raised a corresponding demand for specialized cloud compute that is built to run training and inference workloads in a cost-efficient and performant manner. Google Cloud Tensor Processing Units (TPUs) have become a popular accelerated compute solution for AI/ML workloads.