In streaming-data systems, like applications that stream telemetry from industrial assets or IoT, people encounter problems related to flow control, memory management, and poor performance. The Akka Streams API addresses these issues and it naturally models the common patterns found with streaming telemetry, through simple, composable, and high-level constructs. This talk will provide a motivating example for using Akka Streams and demonstrate a number of these common patterns, in support of building reliable and resilient systems for streaming telemetry at scale.
Colin Breck has almost two decades of experience in developing time-series infrastructures for the monitoring and control of industrial applications. At Tesla, he works on distributed systems for the monitoring, aggregation, and control of distributed, renewable-energy assets. Previously, he worked on the PI System at OSIsoft, including the time-series database and publish-subscribe infrastructure. He writes monthly at blog.colinbreck.com.