virtualization


Machine Learning For Virtual Machine Migration Plan Generation

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The present disclosure relates to management of virtual machines and, more specifically, using machine learning for virtual machine migration plan generation. The computer readable instructions includes determining an initial mapping of a plurality of virtual machines to a plurality of hosts as an origin state and determining a final mapping of the virtual machines to the hosts as a goal state. The virtual machine migration plan is generated based on the heuristic state transition cost of the candidate paths in combination with the heuristic goal cost of a sequence of transitions from the origin state to the goal state having a lowest total cost. One or more candidate parallel migration plans are generated based on the parallelism gates in combination with serial migrations from the virtual machine migration plan.


[video] @Tintri's Enterprise Cloud @CloudExpo #IaaS #DevOps #AI #DX #DigitalTransformation

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We support a lot of different hypervisor platforms from VMware to OpenStack to Hyper-V," explained Dan Florea, Director of Product Management at Tintri, in this SYS-CON.tv With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo @ThingsExpo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-4, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. Join Cloud Expo @ThingsExpo conference chair Roger Strukhoff (@IoT2040), October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, for three days of intense Enterprise Cloud and'Digital Transformation' discussion and focus, including Big Data's indispensable role in IoT, Smart Grids and (IIoT) Industrial Internet of Things, Wearables and Consumer IoT, as well as (new) Digital Transformation in Vertical Markets. Accordingly, attendees at the upcoming 21st Cloud Expo @ThingsExpo October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, will find fresh new content in a new track called FinTech, which will incorporate machine learning, artificial intelligence, deep learning, and blockchain into one track.


Updated Data Science Virtual Machine for Windows: GPU-enabled with Docker support

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The Windows edition of the Data Science Virtual Machine (DSVM), the all-in-one virtual machine image with a wide-collection of open-source and Microsoft data science tools, has been updated to the Windows Server 2016 platform. This update brings built-in support for Docker containers and GPU-based deep learning. Windows Server 2016 includes Windows Containers, and the DSVM also includes the Docker Engine. This is limited to Windows-based containers right now, but you can use Linux-based containers on the Data Science Virtual Machine for Ubuntu Linux, which likewise supports GPU-enabled deep learning.


Data Virtualization: Unlocking Data for AI and Machine Learning

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Hybrid Execution allows you to "push" queries to a remote system, such as to SQL Server, and access the referential data. However, one can imagine a use case where lots of ETL processing happens in HDInsight clusters and the structured results are published to SQL Server for downstream consumption (for instance, by reporting tools). Note the linear increase in execution time with SQL Server only (blue line) versus when HDInsight is used with SQL Server to scale out the query execution (orange and grey lines). With much larger real-world datasets in SQL Server, which typically runs multiple queries competing for resources, more dramatic performance gains can be expected.


What is the Future of VR/AR/AI? Learn From Companies Who Are Building It!

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As the founder and CEO of Dave Martinez Ventures, Dave developed and managed strategic networks and partnerships experienced in the fields that Dave Martinez Ventures provides, incorporating his extensive development history and statistics of facts. She comes to data science from a quantitative social science background. More recently, she has emerged as a thought leader in the San Francisco Data Science community and in mainstream media, she has been interviewed for the PHDivas podcast, German Public Television, Software Engineering Daily, RE-Work, StemGirls, and fashion line MM LaFleur. Vivian has over 10 years experience building content for virtual worlds.


How many servers do you need for your cloud? – DXC Blogs

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As a company turning to public cloud, you are indeed replacing capital expenses (CAPEX) with operating expenses (OPEX), but that's not how it works for a public cloud company. Or, for that matter, your company if you're building your own private cloud. Even AWS, the biggest of the public clouds, can't do that. Over time, I hope AWS, or another of the other major public cloud powers share, if not their data, then at least their methodology.


Is AI the missing piece of the virtualization puzzle?

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In this piece Angela Logothetis, VP and CTO of Amdocs Open Network, argues that AI and automation are critical factors in the successful move to telco virtualization. Though more and more functions have moved onto software platforms, it has made little sense for many operators to automate these functions, when there was still a large physical network that required manual configuration and servicing. Level 3, the global carrier, registers more than 50 billion network events every day, including faults, security threats and performance alerts on issues such as latency, loss and jitter. For example, when the AI engine detects latency or a security threat on the network, ONAP can trigger an automated'fix' to the problem.


Samsung hints at a new life for Windows as an Android app

PCWorld

Samsung has filed for a patent covering a mobile device that could run a second operating system via virtualization. While that's nothing new for the PC industry, it's the accompanying illustration that's intriguing: an Android phone running virtualized Windows apps. HP's Elite x3 smartphone, which began shipping Monday, ships with "HP Workspace," a virtualized app environment that stores and runs legacy Win32 apps. The difference is that the Elite x3 runs Windows 10 Mobile natively, and runs the Win32 apps from the cloud, not from a virtualized partition on the phone.


How mobile carriers are using big data, artificial intelligence

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On this week's NFV/SDN Reality Check we have an interview with Argyle Data to discuss how mobile operators are using big data and machine learning technologies for real time fraud detection, prevention and profit. The survey, which included carriers that have deployed or plan to deploy SDN and NFV platforms, cited Cisco and its Tail-f division, Ciena and its Blue Planet division, and Nokia as having the greatest brand awareness in terms of SDN orchestration software. IHS found more than 40% of those surveyed planned to buy equipment from specialized SDN vendors, open source distribution vendors, SDN application software specialists, data center virtualization and orchestration software vendors and virtual network functions software specialists. For our featured interview this week, we spoke with Padraig Stapleton, VP of engineering at Argyle Data, to discuss how mobile carriers are using big data and machine learning technologies for real time fraud detection, prevention and profit.


AI Paving the Way for 5G, IoT Light Reading

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That's because the looming trends of 5G wireless and the Internet of Things will reshape networks and network traffic in even more unpredictable ways than are happening already, notes Mazin Gilbert, AVP of Intelligent Services at AT&T Labs. In this second of two stories on artificial intelligence (AI) and machine learning in telecom (you can read the first one here), we take a closer look at how AT&T Inc. (NYSE: T) and Level 3 Communications Inc. (NYSE: LVLT) are deploying technology today to be ready for future services. That's why tying AI and machine learning into the software-defined network control layer is critical to enable the network to respond faster than humans can to those unpredictable spikes. When you can connect that to your SDN control layer, now [network alerts] can prompt an automated network control or change event, then you've taken the human out."