  Public clouds are one of the most thriving technologies of the past decade.
Major applications over public clouds require world-wide distribution and large
amounts of data exchange between their distributed servers. To that end, major
cloud providers have invested tens of billions of dollars in building
world-wide inter-region networking infrastructure that can support high
performance communication into, out of, and across public cloud geographic
regions. In this paper, we lay the foundation for a comprehensive study and
real time monitoring of various characteristic of networking within and between
public clouds. We start by presenting CloudCast, a world-wide and expandable
measurements and analysis system, currently (January 2019)collecting data from
three major public clouds (AWS, GCPand Azure), 59 regions, 1184 intra-cloud and
2238 cross-cloud links (each link represents a direct connection between a pair
of regions), amounting to a total of 3422 continuously monitored links and
providing active measurements every minute.CloudCast is composed of measurement
agents automatically installed in each public cloud region, centralized
control, measurement data base, analysis engine and visualization tools. Then
we turn to analyze the latency measurement data collected over almost a year .
Our analysis yields surprising results. First, each public cloud exhibits a
unique set of link latency behaviors along time. Second, using a novel, fair
evaluation methodology, termed similar links, we compare the three clouds.
Third, we prove that more than 50% of all links do not provide the optimal RTT
through the methodology of triangles. Triangles also provide a framework to get
around bottlenecks, benefiting not only the majority (53%-70%) of the
cross-cloud links by 30% to 70%, but also a significant portion (29%-45%) of
intra-cloud links by 14%-33%.
