WAN optimization for array replication
As the need for disaster recovery continues to move downmarket from the enterprise to medium and small businesses, the number of IT shops replicating their data to an offsite location is increasing. Array based replication was once a feature reserved for the big budgets of the Fortune 1000. Today, array based replication is a feature that is available on most midrange storage devices (and even some of the entry level products).
This increase in replication deployments has created a new challenge for IT. The most common replication solutions move the data over the IP network. That data puts a significant load on the IP network infrastructure. The LAN infrastructure is almost always up to the task, but the WAN is often not able to handle this new burden. While the prices of network infrastructure have come down over the years, big pipes are still an expensive monthly outlay. So, how do we get that data offsite without driving up those WAN costs? WAN optimization technology provides a potential solution.
Not every workload or protocol can benefit from today’s WAN optimization technology, but replication is one that usually gets a big boost. I gathered some data from a client who is using NetApp SnapMirror to replicate to a remote datacenter and deployed WAN optimization to prevent a major WAN upgrade.
The NetApp filer is serving iSCSI, Fibre Channel, and CIFS. The clients are primarily Windows and they run Exchange and MS SQL along with some home grown applications. All of their data is stored on the NetApp storage.
The chart below shows the impact the WAN optimization device had. For the purposes of this discussion, think of the device as having one unoptimized LAN port and an optimized WAN port. The LAN traffic is represented by the red and the WAN by the blue. With no optimization, the traffic would be the same on both sides. The chart shows a dramatic reduction on the amount of data being pushed over the WAN.
Network Throughput
This data was gathered over a 2 week period. The total data reduction over the WAN was 83% over the data in the chart and there was a peak of 93% for one window. Again, this is not what every environment will see, so test before you deploy. In this case, the system paid for itself in less than 12 months with the savings in WAN costs. That is the kind of ROI that works for almost anyone.
I am intentionally not addressing what WAN optimization technology was used in this solution. Last time we tested these devices in our lab, we brought in a half dozen and they all had their pros and cons. That is another topic for another post.
Very good data points!
Carmelo Lisciotto