A traffic matrix represents the load from each ingress point to each egress point in an IP network. Although networks are engineered to tolerate some variation in the traffic matrix, large changes can lead to congested links and poor performance. The variations in the traffic matrix are caused by statistical fluc-tuations in the traffic entering the network and shifts in where the traffic leaves the network. For an accurate view of how the traffic matrix evolves over time, we combine fine-grained traffic measurements with a continuous view of rout-ing, including changes in the egress points. Our approach is in sharp contrast to previous work that either inferred the traffic matrix from link-load statistics or computed it using periodic snapshots of routing tables. Analyzing seven months of data from eight vantage points in a large Internet Service Provider (ISP) net-work, we show that routing changes are responsible for the majority of the large traffic variations. In addition, we identify the shifts caused by internal routing changes and show that these events are responsible for the largest traffic shifts. We discuss the implications of our findings on the accuracy of previous work on traffic matrix estimation and analysis.