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· Integrates NVMe SSDs, SATA SSDs, and high-performance HDDs, and constructs a multi-level performance tier to achieve the optimal balance between performance and cost.
· The intelligent tiering engine automatically migrates data based on access frequency hot data resides on SSDs, while cold data is archived to HDDs.
· Supports setting differentiated tiering policies by directory or storage pool, flexibly adapting to diverse scenarios such as video processing, archiving, and backup.

· Supports scaling up to 8192 nodes, with a single file system capacity of ≥200PB, and enables management of tens of billions of files.
· Its built-in data compression and deduplication technologies significantly reduce actual storage consumption, enhancing TB-level cost-effectiveness.

· Adopts a symmetric distributed architecture where all nodes simultaneously assume metadata and data service roles. This eliminates the need for independent metadata nodes, simplifying deployment and management.
· Distributed metadata management avoids centralized bottlenecks, enabling fast retrieval and efficient access to large-scale files.
· Nodes have equal roles failure of any node does not impact metadata services, improving overall system availability.
· A unified architecture design facilitates standardized O&M (Operation and Maintenance) and unified resource scheduling.

· Supports unified access for multiple protocols including NFS, CIFS/SMB, POSIX, HDFS, HTTP, and MPI-IO, breaking down protocol silos.
· The same storage pool can simultaneously serve file sharing and big data analytics, eliminating redundant data replication.
· Supports Ethernet and RoCE network access, and is compatible with standard clients and high-performance proprietary clients.

· Supports a global namespace, providing a unified data view across sites to facilitate centralized management and sharing.
· Supports automated data migration policies based on time, capacity threshold, and access patterns, with options for periodic or one-time execution.
· Enables virtualization of multiple clusters or HDFS storage into a single namespace, simplifying the architecture of big data platforms.

· Leverages AFM technology to enable cross-regional data caching and intelligent routing, allowing remote sites to access high-frequency data locally.
· Supports expanding the global namespace across geographic distances, ensuring remote read/write performance and consistency.
· Data changes are synchronized in real time, enabling efficient and reliable collaboration across multiple locations.

· Supports 3-way/4-way replication and N+2/N+3 erasure codes, allowing flexible configuration of redundancy policies by resource pool or directory.
· Features a fully redundant architecture that supports automatic recovery from hard disk, node, or network failures, ensuring uninterrupted business operations.
· Supports online capacity expansion, contraction, and automatic data rebalancing to maintain continuous system availability.

· Provides dual management modes (graphical GUI and CLI), supporting unified configuration and monitoring across clusters.
· Supports one-click deployment, batch configuration, and rolling upgrades, significantly reducing O&M complexity.
· Monitors key indicators (node CPU, memory, network, disk I/O, and latency) in real time, with support for SNMP and email alerts.