In order to improve bottom line performance in the workplace, IT professionals should assess top priorities to establish protocol on how to choose a server while constructing the most efficient workloads.
Some may say that servers are the heart and lungs of the modern internet, but the deliberation on how to select a server can every so often create a confusing range of hardware choices. Even though it’s possible to pack a data center with matching, virtualized and bundled systems that have the ability to handle any job, the cloud is forever altering how businesses run applications. As more organizations move workloads in the public cloud, local data centers need less resources to host the workloads that remain on site. This is encouraging IT administrators and business professionals to pursue more value and performance from the dwindling server fleet.
These days, the infinity of computer hardware systems is being tested by a new trend in customization with server attributes. Some businesses are encountering the idea that one size may in fact fit all in regards to servers. However, you can opt for and even design server cluster hardware to accommodate specific usage categories.
An advantage of server virtualization is the capacity to host several virtual machines on the same physical server in order to use more of a server’s existing resources. VMs largely depend on RAM and processor cores. It’s impractical to decide exactly how many VMs can exist on any given server because you can arrange them in a way that they can use an extensive range of memory space and processor cores. However, selecting a server with more memory and processor cores will usually permit more VMs to exist on the same server, improving consolidation.
For instance, a Dell EMC PowerEdge R940 rack server can host up to 28 processor cores and offers 48 DDR4 DIMM slots that support up to 6 TB of memory. Some system administrators may choose to pass on individual rack servers with a preference of blade servers for another form factor or as part of hyper-converged infrastructure. Servers meant for high levels of VM merger should also contain resiliency server features.
Another thing to consider when choosing a server for consolidation reasons is the extra attention to network I/O. Enterprise workloads regularly exchange data, access centralized storage resources, and interface with users across the LAN or WAN. Server merging can take advantage of a fast network interface, such as a 10 Gigabit Ethernet port.
Visualization and Scientific Computing
Graphics processing units (GPUs) are surfacing at the server level more and more to help with statistically intensive tasks from big data processing and scientific computing to modeling and visualization. GPUs also allow IT to retain and procedure sensitive, valuable data sets in a more secure data center rather than let that data flow to business endpoints.
GPUs need more than an extra GPU card in the server since there is a slight effect on the server’s traditional processor, memory, I/O, storage, networking or other hardware. The GPU adapters contained in enterprise-class servers are usually far more advanced than the GPU adapters offered for desktops. Graphics processing units are progressively more available as highly specific modules for blade systems.
Take HPE’s ProLiant Graphics Server Blade for instance. The graphics system flaunts support for up to 48 GPUs through the use of multiple graphics server blades. The huge volume of supported GPU hardware gives several users and workloads the ability to share the graphics subsystem.
Info from: http://searchdatacenter.techtarget.com/tip/How-to-choose-a-server-based-on-your-data-centers-needs