Invention Title:

CROSS CLUSTER FAILOVER FRAMEWORK

Publication number:

US20260236358

Publication date:
Section:

Physics

Class:

G06F11/2025

Inventors:

Assignee:

Applicant:

Smart overview of the Invention

The patent application introduces a cross cluster failover framework designed to manage connections between datacenters. This framework allows for seamless switching of data connections from a primary cluster to a secondary cluster based on health evaluations. It ensures that the failover process is transparent to consumer applications, maintaining continuous data flow even during cluster health issues.

Technical Field

The framework operates within distributed data processing systems. It evaluates the health of server clusters in different geographic regions, enabling data streams to switch between clusters as needed. The system is adaptable to various levels, including application, data stream, and topic levels, ensuring robust data management across regions.

System Components

A cluster management server plays a central role, equipped with a processor and memory to execute machine instructions. It establishes and monitors connections based on the health status of server clusters. The server initially connects data sources to a healthy cluster and continuously assesses cluster health to determine if failover is necessary.

Failover Process

When a cluster is deemed unhealthy for a specific data stream category, the management server initiates a failover. This involves switching the data source from the compromised cluster to a healthy one, maintaining data integrity and flow. The system supports both synchronous and asynchronous connections, ensuring flexibility in data transmission.

Application and Usage

While the framework can be applied to financial transactions, its use is not limited to this field. The described system and methods can be adapted for various purposes, offering a scalable solution for maintaining data continuity in diverse applications. The framework's design allows for additional elements and steps, providing a versatile approach to cross cluster data management.