Building rich diagnostics and monitoring experiences for cloud scaleservices requires a sophisticated approach to handling a variety of dataspeeds, feeds and analytical perspectives.  This presentation will focus on techniques and practices for using memory optimized tables in SQL Server to build “warm” data stores from a variety of application data sources (logs,traces, performance statistics).  This will also include approaches for building resilient data pipelines to publish data to SQL from .NET applications, and handle common aspects such as batching and backpressure.
Presented by Mark Simms at SQLBits XIV