Rapidly detecting and classifying malicious activity contained within network traffic is a challenging problem exacerbated by large datasets and functionally limited manual analysis tools. Even on a small network, manual analysis of network traffic is inefficient and extremely time consuming. Current machine processing techniques, while fast, suffer from an unacceptable percentage of false positives and false negatives. To complement both manual and automated analysis of network traffic, we applied information visualization techniques to appropriately and effectively bring the human into the analytic loop. This paper describes the implementation and lessons learned from the creation of a novel network traffic visualization system capable of both realtime and forensic data analysis. Combining the strength of link analysis using parallel coordinate plots with the time-sequence animation of scatter plots, we examine a 2D and 3D coordinated display that provides insight into both legitimate and malicious network activity. Our results indicate that analysts can rapidly examine network traffic and detect anomalies far more quickly than with manual tools.