High-quality, simplified, and low-cost human immunodeficiency virus (HIV) drug resistance tests that are able to provide timely actionable HIV resistance data at individual, population, and programmatic levels are needed to confront the emerging drug-resistant HIV epidemic. Next-generation sequencing technologies embedded in automated cloud-computing analysis environments are ideally suited for such endeavor. Whereas NGS can reduce costs over Sanger sequencing, automated analysis pipelines make NGS accessible to molecular laboratories regardless of the available bioinformatic skills. They can also produce highly structured, high-quality data that could be examined by healthcare officials and program managers on a real-time basis to allow timely public health action. Here we discuss the opportunities and challenges of such an approach.