High performance, strongly consistent applications are beginning to require scalable sub-microsecond clock synchronization. State-of-the-art clock synchronization focuses on improving accuracy or frequency of synchronization, ignoring the properties of the local clock: lost of connectivity to the remote clock means synchronization failure. Our system, Graham, leverages the fact that the local clock still keeps time even when connectivity is lost and builds a failure model using the characteristics of the local clock and the desired synchronization accuracy. Graham characterizes the local clock using commodity sensors present in nearly every server and leverages this data to further improve clock accuracy, increasing the tolerance of Graham to failures. Graham reduces the clock drift of a commodity server by up to 2000×, reducing the maximum assumed drift in most situations from 200ppm to 100ppb. Comments