Levanta, the leader in Linux management has announced the release of its MapFS code to the open source community. MapFS, a key component in Levanta's award-winning Linux management appliance, is a virtual file system that simplifies data sharing between multiple Linux machines connected to a shared storage medium (SAN/NAS/Mainframe DASD).

As a Linux kernel-loadable module, MapFS has been developed under the GPL since its incarnation in early 2004. "Linux management is one of the hottest development areas in Open Source today," said Matt Mosman, CEO of Levanta. "By nature, Linux is extremely well-suited for advanced techniques in server provisioning, disaster recovery, change management and other common systems management scenarios where, frankly, Windows management solutions have been relatively stagnant. Linux is where the management innovation is happening today, and by releasing MapFS, Levanta is introducing a mature, free code base that introduces interesting new virtualization techniques that we believe the development community will find compelling."

MapFS implements a Linux filesystem which utilizes copy-on-write functionality and existing Linux filesystems to allow component filesystems (or portions thereof) to be combined into a single virtual filesystem that appears to be fully writable. MapFS is written in C and uses the standard Linux kernel VFS and loadable module interfaces for defining new filesystem types to the kernel. MapFS supports major kernel versions, including 2.4.7 > 2.6.13.

With MapFS, a Linux system can provide sharing of read-only file systems while at the same time providing each client of the read-only file system the ability to write to its own data store. Files can be either on a read-only persistent repository file system, or on a writable persistent overlay file system. This enables an "optimistic sharing," where everything on the file system is assumed to be read-only. If an attempt is made to modify a file -- that is, a private copy is needed -- the performance hit is typically minimal, because most written-to files are small. Even in the event of a larger file, the performance hit is a one-time cost.