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Recently, to help clients facilitate cloud computing, iomart launched a dedicated, virtualized server service, offering VMware dedicated servers capable of running multiple operating systems and applications from one physical server.

With these services in mind, the challenge that iomart faced was managing 30 terabytes (TBs) of storage across a heterogeneous environment in the City of London and Maidenhead data centers. To meet this objective, iomart approached DataCore, EMC, NetApp and 3PAR for proposed solutions. The suggested environment from DataCore involved using standard x86 hardware, highly specified due to their being of a hosting nature, each having 128GB RAM for caching, 4 Quad Core Processors and 8GB HBA's for connectivity. The disk that sat behind the server was classified as a low-end commodity disk. On top of this hardware, DataCore's SANsymphony solution was used in a mirrored SAN-SAN configuration to virtualize and manage the environment across a fibre link. In total, the solution was less than a one-third of the cost of the equivalent software and hardware alternative proposals.

Keith Joseph, Regional Manager, DataCore Software picks up the story: 'Cost savings were not the most important factor in iomart's search. What they really wanted was to achieve total control of the environment and have the ability to migrate customer data between storage systems and disk types and to easily replicate to remote sites. This they found with DataCore's SANsymphony.'

Mirrored high-availability (HA) between sites over 20 miles away also provides iomart with enhanced disaster recover (DR) capabilities. In their configuration, the environment is distributed throughout several locations and ensures that they have a fully distributed, HA model but across DR geographies.

DataCore's synchronous replication functionality operates on a forced cache coherency model, based on a grid architecture that replicates the I/O block between the cache on each DataCore server before sending the acknowledgement to the application server and committing the data to disk. This overcomes the problems associated with clustered storage, while allowing iomart a greater degree of performance and flexibility.