Repository Timestamp Synchronization for Cloud Event Failover
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Solution Overview
Problem
Existing techniques for automatic replication and failover in cloud-based collaboration systems often result in remote clients missing events during switchover or failover, as they rely on timestamps that may cause events to be recorded as too old, leading to downtime and missed log entries.
Innovation Solution
Implementing a method that compares local and remote timestamps for events, updating the local timestamp if the remote timestamp is more recent, and generating a second event with a current timestamp to ensure all events are captured without downtime during switchover or failover.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automatic replication and failover are implemented using timestamps, then system availability is improved, but events may be missed during switchover or failover due to timestamp recording issues
Solution Approach 1:
The system performs preliminary actions by maintaining multiple redundant repositories with pre-synchronized data before failover occurs. When a failover is needed, the standby repository is already prepared and can immediately serve requests without losing events, as the data replication and synchronization have been performed in advance.
Solution Approach 2:
The patent implements beforehand cushioning by creating redundant copies of event data in multiple repositories with timestamp tracking. This cushioning mechanism ensures that if one repository fails or loses events during switchover, the redundant repositories contain the necessary event data to prevent information loss.
2Speed
If timestamp-based event recording is used during failover, then processing speed is maintained, but events may be recorded as too old and missed
Solution Approach 1:
The system creates and maintains multiple copies of event data across redundant repositories, each with its own timestamp recording. When failover occurs, the new active repository already has copied event data, allowing it to continue processing at full speed without reprocessing or losing events that would otherwise be recorded as too old.
Solution Approach 2:
The patent changes the parameter approach by using multiple repositories with independent timestamp tracking instead of a single timestamp system. This allows the system to maintain processing speed while preventing events from being recorded as too old, since the redundant repositories preserve event validity across failover transitions.
3Reliability
If redundant repositories are implemented, then event capture reliability is improved, but system complexity increases
Solution Approach 1:
The system segments the repository functionality into multiple independent redundant repositories, each handling a portion of the event storage and timestamp tracking. This segmentation improves event capture reliability through redundancy while managing complexity by dividing the system into manageable, independent units that can operate autonomously.
Solution Approach 2:
The redundant repositories are designed with universal functionality, where each repository can serve as either primary or standby and perform all the same operations. This multi-functionality improves reliability through redundancy while reducing complexity by using identical, standardized repository structures and processes across all instances.
Data Source
AI summary
Techniques are disclosed for implementing repository redundancy in a system which incrementally updates remote clients with events that occurred in a cloud-enabled platform. In one embodiment, a method comprises comparing a local timestamp of an event with a remote timestamp of the event. The event is to be stored in a queue in a repository cluster to be read by a remote client. The method further comprises updating the local timestamp of the event if the comparing indicates that the remote timestamp is more recent than the local timestamp. Among other advantages, embodiments disclosed herein ensure that no event in an action log is missed or skipped by any of remote clients in a distributed action log framework system during a switchover from an active but failed server to a backup server, and require zero or minimal down time during the switchover, thereby providing robustness and serviceability to such system.