After many years of extensive development of data center visualization technologies, which started with server virtualization and continued with networking virtualization and storage virtualization, the time has arrived to work on maximizing the efficiency of the data centers that have been deployed over those advanced solutions. The rationale for doing this is pretty clear. New data centers are based on the Hyper-Converged architecture which eliminates the need for dedicated storage systems (such as SAN or NAS) and the need for dedicated servers for just storage. Modern servers that are used in such Hyper-Converged deployments usually contain multiple CPUs and large storage capacity. Modern CPUs have double-digit cores that enable the servers to supports tens, and in some cases, hundreds of Virtual Machines (VMs). From the storage point of view, such servers have a higher number of PCIe slots, which enables the NVMe storage to be used as well the ability to host 24 or 48 SAT/SATA SSDs, both of which result in extremely high storage capacity.
Figure 1: Microsoft’s Windows Servers 2016 Hyper-Converged Architecture, in which the same server is used for Compute and Storage.
Now that there are high performance servers, each capable of tens of VMs and millions IOPs, IT managers must take a careful look at the networking capabilities and avoid IO bounded situations. The network must now support all traffic classes, the compute communication, the storage communications, the control, and so on. As such, not having high enough networking bandwidth will result in unbalanced systems (see: How Scale-Out Systems Affect Amdahl’s Law) and will therefore reduce the overall deployment efficiency. That is why Dell has equipped their PowerEdge 13th generation servers with Mellanox’s ConnectX®-4 Lx 10/25Gb/s Ethernet adapters, delivering significant application efficiency advantages and cost savings for private and hybrid clouds running demanding big data, Web 2.0, analytics, and storage workloads.
In addition to data communication over 25GbE, Dell’s PowerEdge servers, equipped with ConnectX-4 Lx-based 10/25GbE adapters, are capable of accelerating latency-sensitive data center applications over RoCE (RDMA over Converged Ethernet), which enables similar performance in a virtualized infrastructure as in a non-virtualized infrastructure. This, of course, further maximizes system efficiency.
A good example that demonstrates the efficiency that higher bandwidth and lower latency networks enable is Microsoft’s recent blog which published the performance results of a benchmark that they ran over a 4-node Dell PowerEdge R730XD cluster and connected over 100Gb Ethernet. Each node was equipped with the following hardware:
The Microsoft team measured the storage performance, and, in order to maximize the traffic, they ran 20 VMs per server (total of 80 VMs for the entire cluster). They achieved astonishing performance of 60GB/s over a 4-node cluster, which perfectly demonstrates the higher efficiency that can be achieved when the three components of compute, storage, and networking are balanced, minimizing potential bottlenecks that can occur in an unbalanced system.
Another example that shows the efficiency advantages of a higher bandwidth network is a simple ROI analysis of VDI deployment of 5000 Virtual Desktops, which compares connectivity over 25GbE versus 10GbE (published in my previous blog: “10/40GbE Architecture Efficiency Maxed-Out? It’s Time to deploy 25/50/100GbE”). When looking at only the hardware CAPEX savings, running over 25GbE cuts the VM costs in half, while adding the cost of the software and the OPEX even further improves the ROI.
Modern data centers must be capable to handle the flow of data flow of data, and to enable (near) real-time analysis, which is driving the demand for higher performance and more efficient networks. New deployments that are based on Dell PowerEdge servers, equipped with Mellanox ConnectX-4 Lx 10/25GbE adapters, allows clients an easy migration from today 10GbE to 25GbE without demanding costly upgrades or incurring additional operating expenses.