The Benefits of Data Center Network Flexibility with NaaS

Enterprises are well aware of the benefits of a Tier 3 data center as part of a secure and agile hybrid and multicloud strategy that ensures uptime, flexibility, and cost containment. But today, as more enterprises are seeing the need for diverse cloud connectivity to meet application access demands, network as a service (NaaS) is playing a part in expanding that scope.

There are a number of benefits that come from (NaaS), but chief among them is its ability to provide enterprises with the means for on-demand provisioning and management of the network. This drives efficient expansion, management and cost containment by providing variable network connectivity to adapt to network load requirements. This level of network flexibility as part of a cloud strategy makes it easier for businesses to add and reconfigure resources quickly and meet fluctuating network transport needs based on real-time utilization.

Data centers like Telehouse New York that partner with NaaS providers can deliver connectivity options into an SD-WAN framework that is managed by the service provider. By enabling network management and provisioning via a web interface, enterprises can lower the growing costs of management and configuration hardware through the service provider’s SD-WAN software.

These services add a great deal of value to enterprises that require Tier 3 data center services.

The variable network connectivity for both the cloud access and cloud backbone networks of NaaS becomes equally important to the power redundancy and added security benefits of Tier 3 data center specifications. According to the 2018 TechTarget IT Priorities survey where 42% of respondents are using cloud-based SaaS offerings, streamlined network management and monitoring have become a priority.

The ability to partner with a Tier 3 data center that can enable true connectivity flexibility via a cloud access network that enables workload bursting and balancing via NaaS helps keep costs in hand while enabling organizations to tailor network and workloads for peak efficiency and performance.

As a result, in-house data centers can be seamlessly connected to collocation or managed services facilities and to on-demand cloud data centers for a multi-site, hybrid data center model. Click here to visit original source.

Contact Details:
Telehouse America
7 Teleport Drive,
Staten Island,
New York, USA 10311
Phone No: 718–355–2500
Email: gregory.grant@telehouse.com

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Meeting Business Needs for Deep Learning in the Modern Data Center

With a data center in Los Angeles as well as other major metropolitan centers, Telehouse must stay at the forefront of the methods in which AI and deep learning neural networks are shaping the data center needs of the present and future. As the use of AI in the data center becomes more prevalent, the number of enterprise and hyperscale data centers that utilize AI and deep neural networks (DNNs) for massive amounts of data are growing.

Leveraging neural networks is increasingly seen as a fundamental part of digital transformation. It’s growing prevalence can be seen in a recent Information Week article explaining how it is being applied in marketing, retail, finance, and operations management across almost every sector.

Because neural networks use vast amounts of data, they require servers capable of extreme amounts of data computations in record time. Consequently, GPUs designed to enable this level of computational speed and volume are quickly being developed and adopted by data centers around the world.

Data centers that support these new high-performance GPU-based servers can deliver greater efficiency and performance and use less power for advanced workloads while decreasing the data center footprint and power consumption needs. For example, Nvidia’s new single server capable of two petaflops of computing power does what currently takes hundreds of servers networked into clusters. The leading GPU developer’s DGX-2 system is aimed primarily at deep learning applications.

While hyperscale data centers have been the traditional users of neural network-focused GPUs, collocation providers are increasingly partnering with major cloud providers that make this capability part of their offering. They can then offer this capability in their data centers for clients in need of providing their developers with cloud infrastructure services that enable them to build AI features into their own applications. This use is prevalent for companies that are in need of High Performance Computing (HPC) for big data.

The use of cloud hardware in the data center that is designed for neural-network training and inferencing continues to accelerate with Microsoft using FPGAs to accelerate these workloads. Click here to visit original source.

Contact Details:
Telehouse America
7 Teleport Drive,
Staten Island,
New York, USA 10311
Phone No: 718–355–2500
Email: gregory.grant@telehouse.com

Read More