Dragonfly v2.4.0 is released

New features and enhancements Simple multi‑cluster Kubernetes deployment with scheduler cluster ID Performance and resource optimization for Manager and Scheduler components Enhanced preheating Calculate task ID based on image blob SHA256 to avoid redundant downloads Cache HTTP 307 redirects for split downloads Go Client deprecated and replaced by Rust client Significant bug fixes Nydus Others Links Dragonfly Github Posted on February 5, 2026 by epower CNCF projects highlighted in this post Dragonfly v2.4.0 is released! Thanks to all of the contributors who made this Dragonfly release happen. A two-stage scheduling algorithm combining central scheduling with node-level secondary scheduling to optimize P2P download performance, based on real-time load awareness. For more information, please refer to the Scheduling. Dragonfly provides the new Vortex transfer protocol based on TLV to improve the download performance in the internal network. Use the TLV (Tag-Length-Value) format as a lightweight protocol to replace gRPC for data transfer between peers. TCP-based Vortex reduces large file download time by 50% and QUIC-based Vortex by 40% compared to gRPC, both effectively reducing peak memory usage. For more information, please refer to the TCP Protocol Support for P2P File Transfer and QUIC Protocol Support for P2P File Transfer. A SDK for routing User requests to Seed Peers using consistent hashing, replacing the previous Kubernetes Service load balancing approach. Dragonfly supports a simplified feature for deploying and managing multiple Kubernetes clusters by explicitly assigning a schedulerClusterID to each cluster. This approach allows users to directly control cluster affinity without relying on location‑based scheduling metadata such as IDC, hostname, or IP. Using this feature, each Peer, Seed Peer, and Scheduler determines its target scheduler cluster through a clearly defined scheduler cluster ID. This ensures precise separation between clusters and predictable cross‑cluster behavior.