The rise of the cloud over the past few years has transformed business technology. From managing tech infrastructure to application development and management to remote work and beyond, cloud computing has become integrated into many business operations.
As the cloud continues to grow, it will also continue to shape the world of business tech in new and exciting ways. That’s why we asked a panel of Forbes Technology Council members what they see on the horizon for cloud computing. Their top cloud trend predictions are below.
1. Moving From The Cloud To The Edge
Cloud processing will continue to grow but will predominantly be for large-scale data analytics and processing. Machine learning and artificial intelligence will all happen in the cloud, but more localized processing will also slowly move to the edge. With 5G, there will be much faster processing for Internet of Things devices at the “edge”—where the user is—and periodic syncing back to the cloud for more detailed processing. – Jason Lau , Crypto.com
2. The Rise Of The Human Cloud
Tech departments around the world are struggling with the talent gap. However, not all of them know that the same effectiveness that the cloud offers them in the tech area can also be used to secure talent. The human cloud is an emerging trend in the business-to-business sector, with 22% year-over-year growth according to SIA . It provides on-demand access to an extensive, well-measured and flexible talent pool. – Przemek Berendt , Talent Alpha
3. A Move Toward Application Mobility
While the cloud continues to grow for enterprise customers, I see a major trend towards application mobility. Organizations are looking to break free from siloed dependencies on a particular cloud and for the ability to move applications on-demand between public and private clouds and to edge compute locations. This will drive cloud trends. We see it already as public cloud companies push the cloud to the edge. – Ed Fox , MetTel
4. The Rise Of Enterprise AI
Enterprises are maturing from consumer-facing AI applications into a comprehensive, organizationwide, 360-degree AI strategy. This will increase the demand for cloud, hybrid and on-premise systems to have scalable distributed and secure enterprise AI technologies. Emerging distributed AI standards such as Dask and others will play a significant role. – Brian Sathianathan , Iterate.ai
5. Vendor Consolidation
Within the next year, I believe we will see companies looking to reduce the number of disparate solutions they have and focusing on vendors that meet multiple needs and reduce the need for tool sprawl. – Terence Jackson , Thycotic 6. Security-First Thinking Cloud adoption will be supercharged by security-first thinking. An integrated, cross-platform segmentation strategy will enable secure cloud migrations and avoid the legacy challenges of data sprawl, complexity and siloed solutions. Agile segmentation of assets, functions and apps will prevent opening up new areas of risk that didn’t exist before moving to the cloud’s expanded attack surface. – Philip Quade , Fortinet 7. Moving Analytic […]
The computer engine rooms that power the digital economy have become surprisingly energy efficient. A new study of data centers globally found that while their computing output jumped sixfold from 2010 to 2018, their energy consumption rose only 6 percent. The scientists’ findings suggest concerns that the rise of mammoth data centers would generate a surge in electricity demand and pollution have been greatly overstated.
The major force behind the improving efficiency is the shift to cloud computing. In the cloud model, businesses and individuals consume computing over the internet as services, from raw calculation and data storage to search and social networks.
The largest cloud data centers, sometimes the size of football fields, are owned and operated by big tech companies like Google, Microsoft, Amazon and Facebook.
Each of these sprawling digital factories, housing hundreds of thousands of computers, rack upon rack, is an energy-hungry behemoth. Some have been built near the Arctic for natural cooling and others beside huge hydroelectric plants in the Pacific Northwest.
Still, they are the standard setters in terms of the amount of electricity needed for a computing task. “The public thinks these massive data centers are energy bad guys,” said Eric Masanet, the lead author of the study. “But those data centers are the most efficient in the world.”
The study findings were published on Thursday in an article in the journal Science. It was a collaboration of five scientists at Northwestern University, the Lawrence Berkeley National Laboratory and an independent research firm. The project was funded by the Department of Energy and by a grant from a Northwestern alumnus who is an environmental philanthropist.
The new research is a stark contrast to often-cited predictions that energy consumption in the world’s data centers is on a runaway path, perhaps set to triple or more over the next decade. Those worrying projections, the study authors say, are simplistic extrapolations and what-if scenarios that focus mainly on the rising demand for data center computing.
By contrast, the new research is a bottom-up analysis that compiles information on data center processors, storage, software, networking and cooling from a range of sources to estimate actual electricity use. Enormous efficiency improvements, they conclude, have allowed computing output to increase sharply while power consumption has been essentially flat.
“We’re hopeful that this research will reset people’s intuitions about data centers and energy use,” said Jonathan Koomey, a former scientist at the Berkeley lab who is an independent researcher.
Over the years, data center electricity consumption has been a story of economic incentives and technology advances combining to tackle a problem.
From 2000 to 2005, energy use in computer centers doubled. In 2007, the Environmental Protection Agency forecast another doubling of power consumed by data centers from 2005 to 2010.In 2011, at the request of The New York Times , Mr. Koomey made an assessment of how much data center electricity consumption actually did increase between 2005 and 2010. He estimated the global increase at 56 percent, far less than previously expected. The recession after […]
Cloud Computing in Medical Devices Sector A new research document is added in HTF MI database of 17 pages, titled as ‘Cloud Computing in Medical Devices Sector – Thematic Research’ with detailed analysis, Competitive landscape, forecast and strategies. The study covers geographic analysis that includes regions like North America, South America, Asia-pacific, Europe and important players/vendors such as Medtronic, Koninklijke Philips NV (Philips),Amazon Web Services, Veeva Systems, Microsoft Azure, IBM Watson Health, Biop Medical etc. The Study will help you gain market insights, upcoming trends and influencing growth prospects for forecast period of 2020-2026
Cloud based technologies are becoming an important part of the medical devices industry. They provide many benefits, such as connectivity, remote monitoring, and insight into user behaviour. However, the drawbacks include privacy and security worries, as well as regulatory and industry compliance. Due to the nature of this sector, the fears in regards to hacking are fairly robust. In the worst case imagined scenario hackers may remotely access lifesaving medical devices such as pacemakers and change or cease their function. Additionally medical information is extremely sensitive. Due to these reservations, the incorporation of cloud computing in the medical devices sector has been slower compared to other sectors.
This report focuses on the use of cloud computing in the medical devices industry.
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Components of the report include – – Key Players – identify big players in relation to cloud computing. – Trends – identify key trends expected to occur in the cloud computing industry over the next 12 to 24 months. – Industry Analysis – identify the impact of cloud computing across major markets. – Value Chain – identify the various business segments and markets related to the use of cloud computing.
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With Novel Coronavirus (2019-nCov) causing a bigger number of deaths than the 2003 SARS episode and giving no indications of containment, one thing turns out to be clear: the sickness is out of our control at this moment and we will need to get innovative if we need to catch it.
The illness began in China back in December and keeping in mind that there’s been a lot of discussion around how it was taken care of, it’s essential to perceive that our energy is best spent discovering solutions. Presently, like never before, the world needs to meet up. We need to deliver the best personalities in healthcare and technology and innovate in case we will outflank this sickness.
The ongoing coronavirus outbreak (or COVID-19, if you need to be progressively precise) is changing the manner in which individuals live their day-to-day lives and interact with one another. It’s additionally affecting how organizations work, as employees request to work from home and the condition of supply chains changes erratically. With the world, all things considered, in what capacity can your organization keep on running effectively? One innovation that shouldn’t be disregarded during the coronavirus episode is cloud computing
For a considerable length of time, the cloud has given organizations the assets important to remotely process a lot of information, build and run crucial applications and services, and work together with partners over the globe. Since organizations need to face the real factors of coronavirus and its business impact, they should go to cloud computing to alleviate the impacts that the pandemic will without a doubt bring.
Obviously, when you have big data you need huge storage. That is the place cloud computing comes in. The cloud permits companies to ingest, process, analyze, and share big data, a procedure known as data interoperability, in a scalable, cost-efficient manner.
Without the cloud, storing and managing with this amount of information would be cost-restrictive for the healthcare industry. It would require costly servers, and space to keep them, which most companies can’t bear.
In spite of the fact that healthcare cloud adoption is on the ascent, for some healthcare organizations cloud adoption is as yet a challenge. If more healthcare organizations can adopt cloud infrastructure, we will see more noteworthy advancement as far as disease mitigation technologies.
That is accurately what an organization called BlueDot is doing. The organization really anticipated the episode three weeks before the Chinese government reported travel limitations. The organization’s geofencing platform ingests information from web articles, social media life, online communications, and text messages and had the option to deliver an alarm back in December that cautioned of early indications of an outbreak.
The organization keeps on utilizing its product to enable the world to push back on the spread of coronavirus. Bluedot is as of now tracking the disease dependent on aircraft schedules and different sources of unstructured information. At that point, overlaying this information with artificial intelligence (AI) and machine learning(ML), they can anticipate where the illness is probably going to spread, and […]
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The front end of a networked system is the side that a user, client, or customer sees. The back end is everything that happens behind the scenes that is not necessarily seen by the user. Access to networked services may be through a front end that is a web-based interface, a website, a mobile app, or some other type of digital portals such as a monitor display on a kiosk or an ATM. The back end is everything the user does not normally see and the things that process the information. This includes the network connectivity, the cloud hardware including servers, and the cloud-based software applications that run on the cloud servers. Where does the computational work happen? Frequently, the back end does most of the computational processing except for systems with edge-computing capabilities. With edge computing, some computational processing is pushed out towards the front end to be processed by the devices used to access the services. Cloud computing is based on a client-server relationship. In cloud computing architecture, the front end is also known as the client. The back end is the cloud servers and their applications. Any Front-End Device Anytime from Anywhere The networked systems that function the best are those designed to accommodate as many devices as possible, even those running on different operating systems. Moreover, if the interface connects via the Internet, the system should support all the popular web browsers. The front end includes the hardware and the software used by the person to access the cloud services. The hardware could be any device such as a digital notepad, a laptop, a desktop computer, a smartphone, or any other connected device. The front-end device may respond to human control or operate autonomously. With the explosive growth of the Internet of Things (IoT) , billions of new front-end devices are being added to the network. The connectivity of these IoT devices will be further enabled by the deployment of the 5G wireless mobile technology that is already underway in many countries. Front End Cloud Technology Capabilities The advantages of cloud technology include the ability to access a wide variety of cloud-based services using many choices of front-end devices from the simple to the sophisticated. The communication protocols allow many kinds of hardware technology to work with cloud services. Simple Device An example of a simple device is a so-called “dumb” terminal. These are simple connectivity devices with no capability to do any computational processing on their own. All the data processing is done by cloud-based software applications. Device to Device Communication A front end can be a software program. Software programs communicate with cloud services by using an application programming interface (API). Sophisticated Device In the case of sophisticated front-end devices, extensive computational processing can be done by the device and the results sent to the cloud service for further processing, communications, and storage. An example of more sophisticated front-end devices is a game player that connects via the Internet to enable multi-player games […]