20 Sep 2019

Microsoft brings IBM iron to Azure for on-premises migrations

    When Microsoft launched Azure as a cloud-based version of its Windows Server operating system, it didn’t make it exclusively Windows. It also included Linux support, and in just a few years, the number of Linux instances now outnumbers Windows instances.

    It’s nice to see Microsoft finally shed that not-invented-here attitude that was so toxic for so long, but the company’s latest move is really surprising.

    Microsoft has partnered with a company called Skytap to offer IBM Power9 instances on its Azure cloud service to run Power-based systems inside of the Azure cloud, which will be offered as Azure virtual machines (VM) along with the Xeon and Epyc server instances that it already offers.

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    05 Sep 2019


      Atlassian today added new pricing tiers for its cloud products, including free and premium options for Jira Software and Confluence. The Australian company hopes the free editions, in particular,  can entice new customers onto its cloud services.

      Entry-level versions of Jira Software, Jira Service Desk, Jira Core and Confluence will be available at no cost “in the coming months” said Atlassian. The free version of Jira Software and Confluence will be limited to 10 users; Jira Service Desk will be limited to three. File attachments are limited to 20MB, with a 2GB file storage limit for the free versions. And free-tier users will only have access to community support, as opposed to the Standard support package, which offers access to the Atlassian support team during working hours.

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      26 Aug 2019


        The two biggest barriers to the use of machine learning (both classical machine learning and deep learning) are skills and computing resources. You can solve the second problem by throwing money at it, either for the purchase of accelerated hardware (such as computers with high-end GPUs) or for the rental of compute resources in the cloud (such as instances with attached GPUs, TPUs, and FPGAs).

        On the other hand, solving the skills problem is harder. Data scientists often command hefty salaries and may still be hard to recruit. Google was able to train many of its employees on its own TensorFlow framework, but most companies barely have people skilled enough to build machine learning and deep learning models themselves, much less teach others how.

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        16 Aug 2019

        Powering edge data centers: Blue energy might be the perfect solution

          About a cubic yard of freshwater mixed with seawater provides almost two-thirds of a kilowatt-hour of energy. And scientists say a revolutionary new battery chemistry based on that theme could power edge data centers.

          The idea is to harness power from wastewater treatment plants located along coasts, which happen to be ideal locations for edge data centers and are heavy electricity users.

          “Places where salty ocean water and freshwater mingle could provide a massive source of renewable power,” writes Rob Jordan in a Stanford University article.

          The chemical process harnesses a mix of sodium and chloride ions. They’re squirted from battery electrodes into a solution and cause current to flow. That initial infusion is then followed by seawater being exchanged with wastewater effluent. It reverses the current flow and creates the energy, the researchers explain.

          “Energy is recovered during both the freshwater and seawater flushes, with no upfront energy investment and no need for charging,” the article says.

          In other words, the battery is continually recharging and discharging with no added input—such as electricity from the grid. The Stanford researchers say the technology could be ideal for making coastal wastewater plants energy independent.

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