Streaming Analytics Manager (SAM) simplifies the development and reduces the delivery time of analytic applications geared towards data in motion. Using a drag-and-drop interface, application developers can create complex streaming analytics apps for event correlation, context enrichment, complex pattern matching, and analytical aggregations, eliminating the need for specialized skill sets. SAM also allows users to easily define the streaming engine and environments their application will use for execution and a streaming operations view to give users insight into their application’s performance during runtime.
In this talk we will cover the key features of the Streaming Analytics Manager. We will then go over the new features recently added to SAM around ease of debugging and troubleshooting, log search, event sampling, the metrics view, test simulation mode, and more.
With SAM as an analytics solution, users get a rich experience for building and managing streaming analytics applications and bringing these applications to market considerably faster.