Scala By the Bay is the yearly conference of SF Scala, the largest Scala meetup and community in the world, with the highest concentration of Scala developers and companies running Scala as a foundation of their global operations. The conference is held continuously since 2013, with all the videos published on functional.tv. In 2015, expanded with Twitter OSS conference, FinagleCon, and bringing in a wealth of Twitter Stack, powering the global conversation, and Big Data Scala By the Bay -- the synthesis of data engineering and data science with Apache Spark, Apache Kafka, and emerging streaming
Scala By the Bay is not just another tech conference. It is a learning institution, upholding thoughtful software engineering practices, enabling companies to build Twitter-scale reactive data pipelines, and sharing best practices for full-stack construction, from immutable containerized devops to backend, to front-end, with test-driven development, monitoring, continuous deployment, Machine Learning enabling user engagement, and more.
Scala+Scale By the Bay (SBTB) is in its 4th year. It is the main West Coast conference on all things Scala, Kafka, Spark, and all other systems written in Scala -- such as Akka, Play, Finagle, Flink, etc. There three major themes, each represented by a track:
- Thoughtful Software Engineering -- taking a step back to architect software systems and properly write them, using type systems, functional programming, composable abstractions, etc. Developer productivity, workflow, verification and everything else that adds meaning to a developer's life goes here.
- Reactive Systems and Microservices -- Scala-centric stacks are at the frontiers of modern scalable microservices. Akka, Finagle, Lagom, Event Sourcing are thoroughly covered. At least a fourth of all talks deal with streaming data in some form, and we cover all major streaming frameworks here -- Kafka, Akka Streams, Spark Streaming, Flink, etc.
- Data Pipelines and Machine Learning -- Scala-centric stacks are high-throughput, high-performance distributed systems (Spark), and are naturally used for data mining and "big" data. We thoroughly cover all aspects of data engineering flowing into data science, with Machine Learning, Natural Language Processing and AI applications built on top of the two other tracks, plus data mining systems.
Only 500 tickets are available for the entire conference and we will have a truly intimate technical community atmosphere.BOOK YOUR TICKET NOW