Cloud Storage Strategy Series VI – Remote Sites
Your SMB company spans several sites, each site has its own data storage solution like a NAS device. It is good initially but overtime, the remote site becomes data-silos that are disconnected and can’t be shared across company easily.
The longer the data has to stay local to the remote sites, the harder it is later on to consolidate. The earlier you can leverage cloud storage to consolidate your remote sites’ data, the easier it is later on for access.
Cloud storage is good for consolidating data from different remote sites. You can have data hosted by Amazon S3, Rackspace Cloud Files, Windows Azure Storage or AT&T Synaptic Storage and gain access from different remote sites. The Cloud Storage Service Providers will take care of the storage provisioning, replication and other tasks that you had to do previously on a per-remote site basis.
Each remote site still needs LAN performance when the data can be sitting in the cloud. In this case, a gateway is required to provide LAN performance to the cloud storage with local caching and scheduled flushing. Gladinet CloudAFS is a gateway to the cloud storage and can be used on remote sites.
The Cloud Gateway will schedule transfers to the cloud storage based on the local cache status. This process is longer than the LAN transfer. When designing the data migration and consolidation process, this WAN transfer factor needs to be considered. How soon the data needs to be accessed by a different remote site? What is the usage pattern?
There are several parameters to consider when planning to leverage cloud storage for remote site consolidation. It is recommend to make a work sheet that you can capture all these information, which will come in handy for decision making and planning.
A: the amount of data now (GB)
B: the monthly growth of data (GB)
C: upload speed to cloud storage(KB/s)
D: download speed from cloud storage (KB/s)
E: data cost now ($), roughly = A x $.30
F: data cost growth ($), roughly = B x $.30
G: initial upload time (hr) = A / C
H: daily upload time (min) = B / 30 / C
I: Estimated Data Working Set (% of A+B)
J: Estimated Data Working Set Download Time = I / D