
During December 2025, Dongdong Du contributed to the apache/amoro repository by developing two core backend features focused on reliability and scalability. He built a Process Scheduling Framework for the Process Service, refactoring the existing table process logic and introducing targeted optimizations and expanded test coverage. Additionally, he implemented a Database High Availability Service with Leader Election, enabling automatic failover and configurable HA types and heartbeat intervals. Using Java and leveraging skills in backend development, database management, and scheduling algorithms, Dongdong’s work reduced downtime risk, improved throughput under load, and established a robust foundation for future scaling and operational resilience.
December 2025 — Apache/amoro: Delivered two high-value capabilities that boost reliability, scalability, and operational uptime. Key features include a new Process Scheduling Framework for the Process Service, with core framework refactor and added tests, and a Database High Availability (HA) Service with Leader Election to ensure automatic failover and continuous uptime. The work included targeted optimizations of the process framework, expanded test coverage, and the introduction of configurable HA types, heartbeat intervals, and a management container to handle leases and leadership states. These changes reduce downtime risk, improve throughput under load, and lay groundwork for future scaling.
December 2025 — Apache/amoro: Delivered two high-value capabilities that boost reliability, scalability, and operational uptime. Key features include a new Process Scheduling Framework for the Process Service, with core framework refactor and added tests, and a Database High Availability (HA) Service with Leader Election to ensure automatic failover and continuous uptime. The work included targeted optimizations of the process framework, expanded test coverage, and the introduction of configurable HA types, heartbeat intervals, and a management container to handle leases and leadership states. These changes reduce downtime risk, improve throughput under load, and lay groundwork for future scaling.

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