Although the power of genetic surveillance tools has been acknowledged widely, there is an urgent need in malaria endemic countries for feasible and cost-effective tools to implement in national malaria control programs (NMCPs) that can generate evidence to guide malaria control and elimination strategies, especially in the case of Plasmodium vivax. Several genetic surveillance applications (‘use cases’) have been identified to align research, technology development, and public health efforts, requiring different types of molecular markers. Here we present a new highly-multiplexed deep sequencing assay (Pv AmpliSeq). The assay targets the 33-SNP vivaxGEN-geo panel for country-level classification, and a newly designed 42-SNP within-country barcode for analysis of parasite dynamics in Vietnam and 11 putative drug resistance genes in a highly multiplexed NGS protocol with easy workflow, applicable for many different genetic surveillance use cases. The Pv AmpliSeq assay was validated using: 1) isolates from travelers and migrants in Belgium, and 2) routine collections of the national malaria control program at sentinel sites in Vietnam. The assay targets 229 amplicons and achieved a high depth of coverage (mean 595.7 ± 481) and high accuracy (mean error-rate of 0.013 ± 0.007). P. vivax parasites could be characterized from dried blood spots with a minimum of 5 parasites/µL and 10% of minority-clones. The assay achieved good spatial specificity for between-country prediction of origin using the 33-SNP vivaxGEN-geo panel that targets rare alleles specific for certain countries and regions. A high resolution for within-country diversity in Vietnam was achieved using the designed 42-SNP within-country barcode that targets common alleles (median MAF 0.34, range 0.01-0.49. Many variants were detected in (putative) drug resistance genes, with different predominant haplotypes in the pvmdr1 and pvcrt genes in different provinces in Vietnam. The capacity of the assay for high resolution identity-by-descent (IBD) analysis was demonstrated and identified a high rate of shared ancestry within Gia Lai Province in the Central Highlands of Vietnam, as well as between the coastal province of Binh Thuan and Lam Dong. Our approach performed well in geographically differentiating isolates at multiple spatial scales, detecting variants in putative resistance genes, and can be easily adjusted to suit the needs in other settings in a country or region. We prioritize making this tool available to researchers and NMCPs in endemic countries to increase ownership and ensure data usage for decision-making and malaria policy.