Continuous Data Protection (CDP) is a disaster recovery strategy that continuously captures and replicates changes to data in real time or near-real time. Unlike traditional backup methods that rely on scheduled snapshots (e.g., hourly or daily), CDP tracks every write operation, ensuring that any modification—whether to a file, database, or application—is immediately saved to a secondary storage system. This approach minimizes data loss during outages by providing recovery points measured in seconds or minutes, rather than hours or days. For developers, CDP is particularly useful for systems requiring high availability, such as transactional databases or user-facing applications, where even small data losses can have significant impacts.
CDP works by monitoring data changes at the block or byte level, often using techniques like journaling or log-structured storage. For example, when a database writes a new transaction to its log, a CDP system detects this change and streams it to a backup repository. These changes are stored as a chronological sequence, allowing administrators to “rewind” data to any specific point in time. Developers integrating CDP into their systems might interact with APIs or agents that hook into storage layers or applications to track modifications. Tools like distributed file systems (e.g., ZFS) or storage arrays with built-in replication features often implement CDP by maintaining a continuous log of write operations, which can be replayed during recovery.
The primary advantage of CDP is its ability to reduce Recovery Point Objectives (RPOs) to near zero, making it ideal for critical workloads. For instance, an e-commerce platform processing thousands of orders per minute could use CDP to ensure no transactions are lost during a server failure. However, CDP can be resource-intensive, requiring sufficient network bandwidth and storage to handle constant data streaming. Developers should also consider trade-offs: while CDP offers granular recovery, it may not fully replace periodic backups for long-term retention. Combining CDP with traditional backups—using CDP for recent changes and backups for historical data—is a common strategy to balance immediacy and cost.