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For the most part, Java developer's favorite thing to do with Microsoft was to ignore it. Closed source, high price tags and proprietary interfaces only strengthened arguments for Java developers to keep Microsoft out of their projects. Many Java gurus may have stopped paying attention to Microsoft all together. If you did, you may have missed some of their latest efforts and progress. Check it out—it might even be enough to reconsider Microsoft's reputation entirely.
Pivotal and Microsoft are working hard to make the cloud a friendlier place for .NET developers. This post describes five major advancements we’ve made in partnership with Microsoft over the past few months, including bringing cloud native patterns into your .NET code with Steeltoe, consistently deploying ASP.NET Core apps using the new buildpack, running applications in Windows Server 2016 containers, taking advantage of the Microsoft cloud by running Pivotal Cloud Foundry on Microsoft Azure, and simplifying Windows lifecycle operations using BOSH.
Over the past half century or so, the art of developing software has elevated itself to a point where how well you develop software quite literally can make or break you in a market. At Pivotal, we developed this edu-taining quiz to test organizations on how fluent they are in modern development techniques, and even provided a handy list of resources to help you learn about areas you may not have embraced yet.
This episode bundles some of the latest news and trends in the container space, as well as the impacts of .NET Core 1.0 being released to the world of open source. Guest author Kevin Hoffmann joins the podcast to discuss his recent book Beyond the Twelve-Factor App (including 3 more factors!) and provide color on the trends across containers and .NET and how they are impacting app development.
The new release of Apache MADlib 1.9 (incubating) includes support vector machines, which can be used for classification and regression tasks. SVM models have two particularly desirable features: robustness in the presence of noisy data and applicability to a variety of data configurations. This post describes the distributed implementation of SVM in MADlib for very large data sets and shows some scalability test results.
Earlier this year, a highly pedigreed group of big and fast data professionals gathered at the Apache Geode Summit. While all of the session videos and slides are now online, we wanted to highlight three major themes from the conference and point out the related videos and slides.
One of the biggest announcements coming out of Google Cloud Platform’s Next Conference last week was about Apple moving workloads from AWS, but there is much more to the story than the headline. The world of poly-cloud is making big moves from financial justifications to customer moves to product developments. We cover it in this week’s BUILD Newsletter.
Today, VMware and Pivotal share an important milestone in our promise to deliver a next generation, turnkey Cloud Native platform that will fundamentally transform how companies deliver and run custom enterprise software. We are announcing the availability of the open source Photon Platform Cloud Provider Interface (CPI) for Cloud Foundry’s BOSH, an API that is used to interact with an underlying IaaS to create and manage objects on an infrastructure, including images, VMs and disks. Simply put, now Cloud Foundry users have the ability to manage their application’s lifecycle on the lightweight VMware Photon IaaS.
The Apache Software Foundation (ASF) is one of the open source organizations for the Google Summer of Code 2016 (GSoC 2016) program. As a sponsor of the ASF, Pivotal is keen on supporting students looking to work in the complex and growing field of big data by developing features across a number of ASF Incubating projects that power up our data products including Apache Geode (incubating), Apache HAWQ (incubating) and Apache MADlib (incubating). For students around the world, it also offers an opportunity to pair and learn from Pivotal’s data engineers, as well as earn $5500! Deadline to apply is Friday, March 25, 2016.
In this post, Scott Hajek, from Pivotal’s famous data science team, explains approaches for working with unstructured text, extracting the data and turning it into structured records. He explains entity recognition and related NLP techniques, such as human-supervised feedback loops, that use machine learning to automate extraction. Several examples are provided.