Welcome to part eight of the blog series based on Vishwas Lele’s PluralSight course: Applied Azure. Previously, we’ve discussed Azure Web Sites, Azure Worker Roles, Identity and Access with Azure Active Directory, Azure Service Bus and MongoDB, HIPPA Compliant Apps in Azure and Offloading SharePoint Customizations to Azure and “Big Data” with Windows Azure HDInsight.


Big Compute refers to running large scale applications which utilize large amounts of CPU and/or memory resources. These resources are provided by using a cluster of computers and the applications are distributed across the cluster. The key concept is to distribute the application to run on multiple machines so as to execute computations simultaneously in parallel. Problems in the financial, scientific and engineering fields often require computations which would take several days or longer if executed on a single computer. Big Compute solutions significantly reduce the solution time dramatically from days to hours or less, depending on how many machines are added to the compute cluster. Big Compute differs subtly from “Big Data” in that the latter is more about using disk capacity and IO performance of a cluster of computers in order to analyze large volumes of data, whereas Big Compute is primarily about utilizing CPU power in a cluster to perform computations. In order to harness the resources of multiple machines, a Big Compute solution also requires components to handle the configuration and scheduling of the individual component computations – this is usually the role of a ‘head node’ in the compute cluster. Microsoft’s HPC (High Performance Computing) platform is a key aspect of their Big Compute offerings. HPC provides all the components necessary to configure, schedule and execute computations in a distributed cluster. Microsoft’s HPC solution is supported in on-premises environments as well as in the Azure cloud, both in an IaaS configuration as well as via an Azure HPC scheduler. Since the publishing of the Pluralsight course, there have been continued developments from Microsoft on the Big Compute offerings in Azure, in particular the new Azure Batch offering which is currently in preview mode. Read More…

This week, many AIS team members attended the Microsoft SharePoint Conference in Las Vegas, Nevada. We’ll be posting blog posts from each of them as they learn what’s new and what’s exciting during sessions, demonstrations and other conference highlights.

The changes made to SharePoint Search in SharePoint 2013 are too numerous to describe in a single blog post, but I’ll try to provide an overview of some of the major improvements ,with the intent of emphasizing the central role played by search in the new platform. Our future solution architectures for applications will likely have search as a key design consideration. The search-related sessions that I attended at SPC 2012 were well filled to capacity, so there does seem to be a great interest in the future to SharePoint Search.

In his session on building search-driven applications, Scot Hillier made the point that we should no longer think of search in the limited scope of what occurs when a user types in a search term in a search box and the corresponding results that appear. Rather, we should think of search as a data access technology, in the same vein as CAML, REST and CSOM. In fact, he went as far as to say that search is the data access technology because, as he put it, “Search knows where all the skeletons are buried.”

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