Kluster.ai's High Availability Technology Architecture Explained
Kluster.ai is designed with a distributed microservices architecture, and each compute node is equipped with an automatic failover mechanism. The network level realizes global traffic scheduling through Anycast technology, and ensures low latency with edge computing nodes. The database cluster adopts a sharding + multi-copy design to ensure 99.99% service availability. Stress test data shows that the system can stably handle concurrent requests of 100,000 QPS, and the error rate is lower than 0.001%. The unique request queue management system adopts the double scheduling algorithm of priority and weight to guarantee the processing time of key tasks. In actual operation, the architecture successfully withstood the test of the sudden increase of 300% traffic during the e-commerce promotion. The system's built-in meltdown mechanism and automatic capacity expansion and contraction function effectively prevent the avalanche effect. The monitoring system provides millisecond-level tracking of performance indicators, and alarms can be triggered within 50ms for abnormal situations.
- Architecture features: distributed + edge computing + intelligent scheduling
- Performance metrics: 100,000 QPS + sub-second latency
- Reliability: 99.99% year-round availability
This answer comes from the articleKluster.ai: low-cost AI inference platform, sends 100$ DeepSeek-R1 credits, ~167 million tokens!The
