AUTOMATIC ARCHIVING OF DATA STORE LOG DATA

Smart overview of the Invention

The automatic archiving of data store log data involves methods and systems designed to efficiently manage operation records within a log. Operation records, which capture changes made to various data objects, are selected for archival before they are deleted from the log. This process ensures that important information regarding data changes is preserved and can be accessed later, enhancing data management in cloud environments.

Importance of Log Data

As businesses increasingly migrate to cloud computing, managing vast amounts of log data becomes crucial. These logs contain valuable information about operations performed on data objects, which can be used for analytics, data mining, and other applications. However, clients often lack access to this operational history, making it difficult to leverage the full potential of their data.

Archiving Process

The archiving system captures changes as entries in a log, retaining them until their expiration time. A fleet of workers facilitates the replication of these log entries into an archive. Once replicated, the entries are marked for deletion from the log, allowing for efficient space management while ensuring that archived data remains accessible for future use.

System Architecture

The architecture comprises a data store archiving system that maintains an archive of changes related to multiple clients' data objects. Clients interact with the system through devices connected via networks, utilizing APIs to perform various operations. The system is designed to accommodate numerous clients and can efficiently manage the archiving process without requiring user intervention after initial setup.

Benefits of Automatic Archiving

Implementing automatic archiving enhances long-term storage of change data at a lower cost. Clients can access historical records of their data objects more effectively, enabling better decision-making and insights from past operations. Additionally, the system supports scalability and resource optimization within cloud environments, aligning with modern computing needs.