Data recovery from distributed SAN-systems
The idea to store data in a distributed manner was implemented in a Storage Area Network (SAN). SAN systems create a huge amount of disk space achieved by integrating several servers into one system and allow getting fast parallel access to files from different servers. They are mainly employed by corporate users for reliable centralized storing of data. SAN systems apply special file systems and particular controllers for access to a storage. Several servers integrated into one system and the distributed data storing method make SAN a system with high fault-tolerance and great reliability. Nevertheless, seldom outages of such devices still happen. Failures of a SAN controller, inappropriate reaction of a controller to the failure of a SAN-component or an operator's error often result in data loss.
SAN systems are unique in respect of data recovery due to their non-transportability; thus, one has to exclude the possibility to take such a system to a service center. Besides, these systems usually store a considerable amount of crucial information. In case of metadata outages or failures of the controller metadata, the data can be recovered quite fast through the reconstruction of a file system basing on metadata and its further copying to a safe location. If a SAN component failed, it's possible to recover the data lost from this component only. If vitally important data has been deleted, the system must be switched to the read-only mode, while metadata and the journal of the SAN-system (usually 1-10% of the whole amount of a file system) should be copied to a safe place.
Data recovery from these systems is available as remote services offered by SysDev Laboratories. In order to get the SAN checked for the possibility of data recovery, a user needs to know the file system type of SAN and send us the metadata image of SAN (such metadata does not contain any corporate information and rather informs about data distribution and file names on the SAN system).
Last update: 05.07.2018