Technology Deep Dive
9:20 AM, UTC+8;5:20 PM, UTC-8 , November 20
Building Modern Data Streaming Apps
In my session, I will show you some best practices I have discovered over the last 7 years in building data streaming applications including IoT, CDC, Logs, and more.
In my modern approach, we utilize several Apache frameworks to maximize the best features of all. We often start with Apache NiFi as the orchestrator of streams flowing into Kafka and/or Pulsar. From there we build streaming ETL with Spark, enhance events with Pulsar Functions and/or Kafka Streams for ML and enrichment. We build continuous queries against our topics with Flink SQL.
We use the best streaming tools for the current applications with FLiPN and FLaNK. https://www.flipn.app/
Speaker
Timothy Spann
Developer Advocate @ StreamNative
Tim Spann is a Developer Advocate @ StreamNative where he works with Apache Pulsar, Apache Flink, Apache NiFi, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
