Managing Data Corruption in the Cloud

Silent data corruption, where data becomes corrupt without detection, can impact systems across the software industry. MongoDB Atlas, a global cloud database service, operates at petabyte scale and requires sophisticated solutions to manage this risk. The implemented systems consist of software-level techniques for proactively detecting and repairing instances of silent data corruption, including monitoring for checksum failures, identifying corrupt documents by leveraging MongoDB indexes and replication, and repairing corrupt data using redundant replicas. These measures give early visibility into new types of data corruption that emerge in the fleet, as well as the tools needed to pinpoint and repair corruption when it occurs.