Jeffrey Burt

Author Archives: Jeffrey Burt

HPE Buys Its Way Into Virtual Networking With Plexxi

It is safe to say that companies that have traditionally built server, storage, and switch hardware have had a tough time finding their place in a world that is increasingly allergic to appliances and wants everything to come as software that customers have more control over. Even those vendors that are innovating at the hardware level have a heavy software hook, and no hardware vendor can leave itself in the position of just shifting boxes if it hopes to have a profitable business.

Hence the recent acquisitions by both Dell and Hewlett Packard Enterprise. Dell, of course, shelled out a

HPE Buys Its Way Into Virtual Networking With Plexxi was written by Jeffrey Burt at The Next Platform.

Hitachi Pulls Itself Together In The Datacenter

Hitachi is a massive multi-national conglomerate that has more than 300,000 employees and 950 subsidiaries and a reach that extends into a wide array of industries, from aircraft and automotive systems to telecommunications, construction, defense and financial services. It also is among the world’s largest IT companies, nestled in there among the likes of Apple, Amazon, Microsoft, Google, Samsung. Hitachi’s sprawling technology capabilities ranges from compute and storage appliances in its well-known Hitachi Data Systems (HDS) unit to datacenter management software, data management and business intelligence, and the Internet of Things.

For the past several years, the company

Hitachi Pulls Itself Together In The Datacenter was written by Jeffrey Burt at The Next Platform.

Fabrics Open The Way For Storage Class Memory

Dell EMC has long been a vocal proponent of NVM-Express, the up and coming protocol that cuts out the CPU jib-jab with PCI-Express peripherals and that boost throughput and drops latency for flash and other non-volatile memory.

For the past two years, Dell, like other system makers, has put NVM-Express drives in its servers while ramping up the flash in its high-end storage systems and preparing to bring the protocol to those external storage appliances. It has taken time to get the arrays reworked, for the price of NVM-Express drives to come down, and for the volumes to ramp up.

Fabrics Open The Way For Storage Class Memory was written by Jeffrey Burt at The Next Platform.

Cisco’s Wide And Deep Embrace Of Kubernetes

As enterprises continue to spread their workloads around – keeping some in their core datacenters while placing others in either private clouds or sprinkling them among disparate public clouds – the portability, visibility and management of those applications becomes an issue. There is no standardization among public cloud providers like Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform, among others, and applications that run well in an on-premises datacenter may hit some rough patches when they migrate to the cloud. Developers also are finding challenges when moving applications into production, either in the datacenter or cloud, also

Cisco’s Wide And Deep Embrace Of Kubernetes was written by Jeffrey Burt at The Next Platform.

Stretching NSX From The Datacenter To The Edge And Cloud

VMware’s $1.26 billion acquisition of network virtualization startup Nicira in 2012 sent ripples through the tech world. Through the deal, VMware, which had made its name as a pioneer of server virtualization technology, planted a flag in the burgeoning software-defined networking (SDN) space that was roiling the traditionally staid networking market.

The deal also put the company at odds with partners like Cisco Systems, which itself was developing a strategy to address SDN and which threatened to upend the business of selling networking switches and routers that had made Cisco a very rich and high-profile tech vendor. It put VMware

Stretching NSX From The Datacenter To The Edge And Cloud was written by Jeffrey Burt at The Next Platform.

Playing Dominoes In Data Science

The growing amounts of data that are being generated due to such trends as the Internet of Things (IoT) and cloud computing have naturally beget the need for data scientists who can collect, analyze and, most importantly, interpret these massive stockpiles of complex information to help their companies more quickly and accurately make better business decisions to give them a competitive edge over competitors and to improve their operations and make them more efficient.

That in turn has created something of a land rush in what’s become a rapidly expanding data science platform market of more than a dozen vendors

Playing Dominoes In Data Science was written by Jeffrey Burt at The Next Platform.

Swim In Data At The Edge, Don’t Drown In It In the Datacenter

Analytics systems have been downing in data for years, and the edge is going to flood it unless the architecture changes. There is so much data that is going to be generated at the edge of the network that it can’t be practically moved back to the datacenter for processing in a timely enough fashion to be useful in a way that the gathering of the information was done in the first place.

That is the premise behind our expanding coverage of edge computing and what is evolving into a distributed, multi-tier data processing complex – you can’t really call

Swim In Data At The Edge, Don’t Drown In It In the Datacenter was written by Jeffrey Burt at The Next Platform.

Vexata Has Its Own Twist On Scaling Flash Storage

When looking for all-flash storage arrays, there is no lack of options. Small businesses and hyperscalers alike helped fuel the initial uptake of flash storage several years ago, and since then larger businesses have taken the plunge to help drive savings in such areas as power and cooling costs, floor and rack space, and software licensing.

The increasing demand for the technology – see the rapid growth of Pure Storage, the original flash array upstart over the past nine years – has not only fueled the rise of smaller vendors but also the portfolio expansion of such established

Vexata Has Its Own Twist On Scaling Flash Storage was written by Jeffrey Burt at The Next Platform.

EU Swaps JuQueen BlueGene/Q For Modular Xeon JUWELS Supercomputer

The European Union has never been willing to cede the exascale computing race to the United States, Japan, or China.

In recent years, Europe has ramped up its investments in the HPC space through such programs as Horizon 2020, an effort to grow R&D in Europe, and EuroHPC to drive development of exascale systems, and the Partnership for Advanced Computing in Europe (PRACE), which aims to develop a distributed supercomputing infrastructure that will be accessible to researchers, businesses, and academic institutions throughout the EU. The SAGE project will create a multi-tiered storage platform for data-centric exascale computing to enable

EU Swaps JuQueen BlueGene/Q For Modular Xeon JUWELS Supercomputer was written by Jeffrey Burt at The Next Platform.

DHL Gets Logical – And Logistical – About Machine Learning

For the past several years, machine learning as evolved by the hyperscalers has been trickling down from on high, through frameworks and services, into enterprises.

Machine learning is becoming a regular technique underpinning applications in a growing number of industries like manufacturing, energy, telecommunications and engineering, where companies see it as a way to not only reduce the costs and improve the efficiencies in their operations but also to more quickly detect patterns in and gain insights from the huge amounts of data they are generating. The goal is to making better and faster business decisions, and to

DHL Gets Logical – And Logistical – About Machine Learning was written by Jeffrey Burt at The Next Platform.

Pushing Up The Scale For Hyperconverged Storage

Hyperconverged storage is a hot commodity right now. Enterprises want to dump their disk arrays and get an easier and less costly way to scale the capacity and performance of their storage to keep up with application demands. Nutanix has a become as significant player in a space where established vendors like Hewlett Packard Enterprise, Dell EMC, and Cisco Systems are broadening their portfolios and capabilities.

But as hyperconverged infrastructure (HCI) becomes increasingly popular and begin moving up from midrange environments into larger enterprises, challenges are becoming evident, from the need to bring in new – and at times

Pushing Up The Scale For Hyperconverged Storage was written by Jeffrey Burt at The Next Platform.

The Evolution Of Hyperconverged Storage To Composable Systems

Hyperconverged infrastructure in some ways is like the credit card in those old TV ads: in this case, it’s everywhere that enterprises want to be. HCI put compute and storage on the same cluster, tightly integrate them with networking and unified management tools and essentially give enterprises a private cloud for the datacenter as well as pushing compute out to the edges in a consistent manner.

HCI also promises a bunch of other things beneficial to enterprises, including streamlined management, lower costs, faster speeds, and easier scalability than traditional IT systems to better address the rise of cloud computing, analytics,

The Evolution Of Hyperconverged Storage To Composable Systems was written by Jeffrey Burt at The Next Platform.

Dell EMC and Fujitsu Roll Intel FPGAs Into Servers

Nvidia caused a shift in high-end computing more than a decade ago when it introduced its general-purpose GPUs and CUDA development platform to work with CPUs to increase the performance of compute-intensive workloads in HPC and other environments and drive greater energy efficiencies in datacenters.

Nvidia and to a lesser extent AMD, with its Radeon GPUs, took advantage of the growing demand for more speed and less power consumption to build out their portfolios of GPU accelerators and expand their use in a range of systems, to the point where in the last Top500 list of the world’s fastest

Dell EMC and Fujitsu Roll Intel FPGAs Into Servers was written by Jeffrey Burt at The Next Platform.

AWS Puts More Muscle Behind Machine Learning And Database

Amazon Web Services essentially sparked the public cloud race a dozen years ago when it first launched the Elastic Compute Cloud (EC2) service and then in short order the Simple Storage Service (S3), giving enterprises access to the large amount compute and storage resources that its giant retail business leaned on.

Since that time, AWS has grown rapidly in the number of services it offers, the number of customers it serves, the amount of money it brings in and the number of competitors – including Microsoft, IBM, Google, Alibaba, and Oracle – looking to chip away

AWS Puts More Muscle Behind Machine Learning And Database was written by Jeffrey Burt at The Next Platform.

Startup Tackles Cloud Migration And Management Hassle

Enterprises can see cost and efficiency benefits when they migrate workloads into the cloud, but such moves also come with their share of challenges in complexity and management. This is particularly true as organizations embrace a compute environment that includes multiple clouds – both public and private – as well as one or more on-premises datacenters. True, the cloud enables businesses to easily scale up or down depending on the workloads they’re running, to pay for only the infrastructure they’re using rather than having to invest upfront in hardware, to put the onus of integration on the cloud providers, and

Startup Tackles Cloud Migration And Management Hassle was written by Jeffrey Burt at The Next Platform.

HPE Aims Apollo at Enterprise AI

There continues to be an ongoing push among tech vendors to bring artificial intelligence (AI) and its various components – including deep learning and machine learning – to the enterprise. The technologies are being rapidly adopted by hyperscalers and in the HPC space, and enterprises stand to reap significant benefits by also embracing them.

As we’ve noted many times here at The Next Platform, at the most basic level, machine learning and deep learning can enable enterprises to quickly sort through and analyze the massive amounts of data that they’re collecting to find patterns that can lead to better

HPE Aims Apollo at Enterprise AI was written by Jeffrey Burt at The Next Platform.

Dell EMC Puts Open Networking on the Edge

Computing resources – including storage and networking – are continuing their march toward the network edge, drawn like a magnet to the rapidly proliferating connected devices in the world and the huge amounts of data that they’re generating that need to be collected, processed and analyzed.

As we’ve talked about here at The Next Platform over the past few months, the distributed nature of computing, fueled by such drivers as the cloud, the Internet of Things (IoT) and greater mobility, and the demand for capabilities like artificial intelligence (AI), machine learning and analytics to manage the data call for moving

Dell EMC Puts Open Networking on the Edge was written by Jeffrey Burt at The Next Platform.

A Reference Architecture for NVMe over Fabrics

Cavium has raised its profile over the past several years as one of the pioneers in developing Arm-based systems-on-a-chip (SoCs) for servers, rolling out multiple generations of its ThunderX chips in hope of pushing Arm’s low-power architecture make gains in a datacenter environment that for years has been dominated by Intel and its x86-based Xeons.

However, like similar chip makers, Cavium didn’t start with the Arm server chips, but instead built to that point atop a broad array of products for other areas of the datacenter, including adapters, controllers, switches and MIPS-based processors for networking and storage devices.

A Reference Architecture for NVMe over Fabrics was written by Jeffrey Burt at The Next Platform.

FPGA Maker Xilinx Says the Future of Computing is ACAP

The field programmable gate space is heating up with new use cases driven by everything from emerging network, IoT, and application acceleration trends. Keeping ahead of the curve means expanding on devices that have quite steady improvement cycles, which means the few companies at the top need to get creative to stay competitive.

Xilinx and Altera – which was bought by Intel in 2015 for $16.7 billion – have been the top vendors of FPGAs, which can be programmed and reprogrammed, enabling organizations the ability to adapt the processors to the varying workloads running on the systems. The high price

FPGA Maker Xilinx Says the Future of Computing is ACAP was written by Jeffrey Burt at The Next Platform.

IBM Unwinds Tangled Data for Enterprise AI

These days, organizations are creating and storing massive amounts of data, and in theory this data can be used to drive business decisions through application development, particularly with new techniques such as machine learning. Data is arguably the most important asset, and it is also probably the most difficult thing to manage. Well, excepting people.

Data is tangled mess. It can be structured or unstructured, and it is increasingly scattered in different locations – in on-premises infrastructure, in a public cloud, on a mobile device. It is a challenge to move, thanks to the costs in everything from bandwidth to

IBM Unwinds Tangled Data for Enterprise AI was written by Jeffrey Burt at The Next Platform.

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