Goodnotes Finds Marketplace Success Using MongoDB Atlas

Silent data corruption can impact systems across the software industry and is a significant concern for cloud platforms like MongoDB Atlas that operate at petabyte scale. To manage this risk, MongoDB Atlas has implemented sophisticated software-level techniques to proactively detect and repair instances of silent data corruption. These systems include monitoring for checksum failures and similar runtime evidence of corrupt data, methods of identifying corrupt documents by leveraging MongoDB indexes and replication, and processes for repairing corrupt data by utilizing the redundant replicas. The approach involves proactively monitoring for signals of corrupt data from across their fleet of databases, scanning databases to pinpoint identified corruption using indexes and replication, and repairing corruption in coordination with customers by leveraging MongoDB's replica set deployment model.