Parallels® Toolbox is helping users find new ways to increase productivity – especially if you need to optimize presentations! Recently released, Parallels Toolbox empowers users with more than 30 easy-to-use, one-click tools, all packaged within a simple interface for both Mac® and PC. This must-have, all-in-one application has helped Sean Bugler, a technical trainer, simplify […]
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As many know, the first generation of Cloud Management Platform (CMP) solutions were designed for managing virtual infrastructure (IaaS) and traditional applications. But that’s no longer enough to satisfy evolving and complex business requirements.
In his session at 21st Cloud Expo, Scott Davis, Embotics CTO, explored how next-generation CMPs ensure organizations can manage cloud-native and microservice-based application architectures, while also facilitating agile DevOps methodology. He explained how automation, orchestration and governance are fundamental to managing today’s hybrid cloud environments and are critical for digital businesses to deliver services faster, with better user experience and higher quality, all while saving money.
We’re excited to announce that a Hyper-V virtual machine with Parallels® Mac Management for Microsoft® SCCM is now available—a pre-built Microsoft SCCM trial environment with a trial version of our plugin for managing Mac computers. This pre-built trial allows you to try our solution without any impact on your Microsoft SCCM infrastructure. It also enables […]
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“Avere Systems deals with data performance optimization in the cloud or on-premise. Even to this day many organizations struggle with what we call the problem of data gravity – ‘Where should I put the data?’ – because the data dictates ultimately where the jobs are going to run,” explained Scott Jeschonek, Director Cloud Solutions at Avere Systems, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
“Avere Systems deals with data performance optimization in the cloud or on-premise. Even to this day many organizations struggle with what we call the problem of data gravity – ‘Where should I put the data?’ – because the data dictates ultimately where the jobs are going to run,” explained Scott Jeschonek, Director Cloud Solutions at Avere Systems, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
For a Windows application that does lots of complex or 3D graphics, there are two popular Windows APIs used by the developers of these applications: DirectX or OpenGL. Together with the graphics card in your Mac, these APIs determine the performance of these applications in a Windows VM running in Parallels Desktop® for Mac. Since […]
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Acuity expects cloud-based biometric solutions to authenticate more than one trillion transactions annually by 2022
Cloud-based biometric solutions are expected to drive the mobile biometric market to $50.6 billion in annual revenue by 2022, according to Acuity Market Intelligence.
Acuity predicts that more than 5.5 billion biometrically enabled mobile devices will create a global platform that would support one trillion cloud-based biometric transactions yearly by 2022.
Maxine Most, Acuity's Principal and lead analyst, said: "Biometric have become a mainstream convenience for unlocking smartphones and verifying on-device transactions. But the market is evolving towards a hierarchy of integrated biometric authentication methods that range from simple device-based verification to third-party biometric Cloud, or server-side, solutions. These solutions will replace traditional digital identity schemes and provide more secure and reliable identity assurance on a global scale.”
As per Acuity, the annual biometric transaction revenue is expected to grow from $474 million in 2017 to $18 billion in 2022, thus exceeding a 100% CAGR. Biometric app revenue is expected to increase at 26% during this period as revenue increases from $9.4 billion to $29 billion yearly. Acuity predicts mobile biometric transaction volume to reach 1.4 trillion yearly in 2022 – more than 70% cloud based – as biometric app downloads exceed 16.7 billion that year.
Most said: "Pushing biometrics to 'the edge' of the mobile ecosystem with device-based authentication improves the mobile experience, but with limitations. The big payoff comes from Cloud, or server-side biometrics, that simplify authentication and reduce friction while linking an individual to a device and platform independent Unique Verifiable Identity (UVI)."
Are you surprised at this rate of growth? Share your thoughts in the comments.
“We work around really protecting the confidentiality of information, and by doing so we’ve developed implementations of encryption through a patented process that is known as superencipherment,” explained Richard Blech, CEO of Secure Channels Inc., in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
Cloud computing has fundamentally transformed information technology by offering enterprises an allegedly cheaper, more flexible, and relatively maintenance-free alternative to purchasing their own IT infrastructure. However, despite the mad rush to migrate to the cloud, cloud solutions are not always the best or least expensive choice, particularly in industries that work with very large, complex data sets, perform many intricate mathematical calculations, possess invaluable digital intellectual property, or are subject to certain compliance standards.
Let’s take a look at four industries where in-house IT infrastructure still beats the cloud.
In the cybersecurity field, the ability to process extremely large data sets as quickly as possible is crucial, especially as cyber attacks shift away from “lone wolf” one-off hacks and towards highly organized, sophisticated operations carried out by well-trained cyber criminals. IBM estimates that the average organization encounters an average of 200,000 security event alerts each day. An enormous amount of computing power is required to run the SIEM systems that not only detect those anomalies, but also analyze them, separate the false positives from the possible attacks, and deliver actionable information to security analysts – way more power than even the most robust cloud solution could possibly deliver.
In addition to latency problems, the amount of bandwidth consumed would become very expensive, very quickly, making on-premises equipment the most cost-effective solution over time. On-premises cybersecurity hardware also prevents chain-reaction situations where client organizations end up getting hacked because the cloud vendor that their cybersecurity provider was using did.
The internet has transformed the way in which consumers and businesses shop. Long buying cycles have been replaced by “just-in-time,” last-minute purchasing decisions, and advertising-weary prospects are using ad blockers, email filters, and DVR fast-forward functions to tune out traditional advertising. To reach these elusive prospects, companies are turning to ad tech, which employs extensive market research and big data analytics to deliver highly targeted marketing messages to qualified prospects at the precise time that they are ready to buy.
The complex data sets and high-level analytics that power the ad tech industry require computing power that is already beyond what any could solution could offer. As the industry matures, ad tech firms will require even more power and more storage space. On-premises equipment can be scaled much more quickly than cloud solutions, and latency problems are avoided.
The ad tech industry also faces intellectual property issues. As Amazon, Google, and other cloud providers enter the market research and ad tech spaces themselves, questions arise as to the safety of digital intellectual property stored on a competing company’s cloud service. Dropbox listed Amazon’s move into the file-sharing space as one of the reasons why it decided to ditch AWS for its own equipment.
The life sciences industry is grappling with a “data avalanche” of clinical results, disease states, scientific studies, and individual patient data, which results in stratospheric cloud bills and latency problems. Because researchers work on limited budgets, simply storing all of this data on the cloud could deplete a project’s funding – and that’s before anything is actually done with it.
Cyber security and compliance issues also come into play due to the sensitive nature of this data. Storing patient data on the cloud may result in an organization running afoul of HIPAA and other privacy regulations if the cloud provider gets hacked, even if the hack turns out to be the provider’s fault.
Finally, on-premises hardware, unlike cloud solutions, keeps running even if the internet is down, which makes on-site equipment a must for scientists who are performing research in remote areas where internet access is spotty.
Much like cyber security, ad tech, and the life sciences, design and engineering involves performing intricate calculations on very large, complex data sets, as well as running memory-intensive software and generating terabytes of new data every day. A cloud solution would be both wildly expensive and far too slow. In particular, cloud servers offer very poor interdomain communication; a physical server equipped with a high-performance communication architecture such as Intel’s Omni-Path is less expensive than a cloud solution is less expensive and offers low communication latency, low power consumption, and a high throughput.
Design and engineering companies also face a constant threat from digital intellectual property theft; everything from new product prototypes to R&D data could be targeted by competitors, cyber extortionists, or even foreign governments. Digital IP is simply too sensitive to be stored in the cloud, especially since hackers are increasingly targeting cloud providers as the industry grows.
Despite its drawbacks, cloud computing does have a place in many organizations’ IT ecosystems. Many companies use on-premises equipment to handle standard functions and store highly sensitive data and employ cloud solutions when they require additional capacity or to store less-sensitive data.
Instead of migrating to the cloud because it’s trendy, and “everyone” says it costs less and offers more flexibility than in-house equipment, enterprises should take a step back, consider their individual computing needs, and perform an objective cost analysis.
Quick quiz!
What’s the first thing that comes to mind when you hear the following phrases?
Artificial grass
Artificial sweeteners
Artificial flavors
Artificial plants