JuiceFS Enterprise 5.3: 500B+ Files per File System & RDMA Support

JuiceFS Enterprise Edition 5.3 has been released, enhancing its capacity to manage over 500 billion files within a single file system. This release introduces significant optimizations to its metadata multi-zone architecture, increasing the zone limit to 1,024 to support this massive scale. For the first time, RDMA technology is integrated to boost distributed caching efficiency and reduce CPU usage during data transfers. Version 5.3 also improves write support for mirrors, allowing temporary file writes and providing a fallback mechanism for read requests if a mirror becomes unavailable. New to this version is the ability to cache objects imported across different buckets, offering greater flexibility. The update addresses performance challenges in large-scale distributed systems by introducing automated hotspot balancing with manual intervention tools and large-scale migration enhancements. Reliability is bolstered through self-checks that automatically repair and clean up intermediate migration states, preventing potential errors over time. Stress tests have demonstrated the system's stability and performance, writing approximately 400 billion files at a speed of 5 million files per second. The integration of RDMA technology significantly reduces CPU load and increases bandwidth utilization, especially beneficial for high-demand scenarios. Enhanced mirror write support balances high availability with cost reduction, allowing for single mirror node deployments. The cross-bucket data cache for imported objects simplifies management for users with data spread across multiple object storage buckets. Additional optimizations include a trace feature for advanced performance analysis and improved trash recovery reliability. Python SDK improvements further simplify user interactions by allowing direct access to operational subcommands within the SDK. These advancements solidify JuiceFS Enterprise Edition's position as a high-performance solution for demanding AI and multi-cloud environments.