SoundCloud is the world's leading audio platform. Founded in 2007 by Alex Ljung and Eric Wahlforss, musicians and engineers, SoundCloud provides creators of music & audio with an open platform and the best tools to share original content, build an audience, and connect with a community of other creators – from home-based producers to global superstars. SoundCloud is operating on a global scale out of its Berlin headquarters. It can be accessed via the web, on mobiles and through a number of third party platforms.
SoundCloud is rooted on the premise that sound creators are looking for innovative ways to build their careers. Social and instant global distribution are key in supporting creators on that path. Within less than two years, the world has gone from desktop to mobile – a trend that requires new approaches but at the same time creates an opportunity for an audio-based platform. Currently, digital music distribution is characterized by players who enable a migration to the online world, however there still is an opportunity for a gate opener to truly augment the experience of the user. Innovation requires high-performance organisations, thus Organisational Health is key for innovative companies - regardless if they are based in the Silicon Valley or in Berlin.
As you move workloads into Windows Azure Virtual Machines (VM), there is another skillset you must master...VM optimization. In this deep dive session you will learn how to configure and tune your virtual machines in Windows Azure for optimal performance and availability. Anders and Pete will take you through optimizing disk configuration, optimizing I/O performance, as well as how to choose the right VM size in Windows Azure. Discussion will then move into high availability in Windows Azure for a variety of popular application workloads, including Internet Information Server (IIS), MS SQL Server and SharePoint. If you are interested in maximizing your Windows Azure IaaS investments, this session is not to be missed!
For machine learning, Hadoop offers new performance capabilities, but not the intrusion of Hadoop's accompanying tradeoffs--performance, resource consumption, and data management. Machine learning users should consider Hadoop as a portion of a solution, but not the end-all. Alternatives such as dedicated servers, in-database deployment, and memory-based alternatives like Apache Spark can be combined with Hadoop to address a far broader array of opportunities. Fortunately for Revolution R users, Revolution R Enterprise (RRE) enables analytical scripts and models built in RRE to port between platforms with relative ease. In this session, we'll review the considerations for R developers, including performance, resource management, and data handling for deployment on Hadoop, individual servers, clusters and grids, in-database, and in-memory, including Apache Spark. We'll also dive briefly into the internals RRE on Hadoop to deepen awareness of some of the tradeoffs.
You have a brand new Office 365 tenant and during the pilot phase some of your users start complaining that things are going really slowly. Troubleshooting this issue is complicated and requires knowledge and tools, from the desktop through to the network, through to the Internet. This session will demonstrate how you can test, identify, and fix the ten most common issues and help you bring lightning speed and stability back into your user's experience of Office 365.