Looking at the New Features of Apache NiFi

Apache NiFi has a lot of new features, processors and best practices that have arrived in the last year or so. I will walk through building flows using the latest tips, techniques and processor. I will change a number of data flows utilizing the latest NiFi version and point out gotchas and some never dos. The deck will act as a take-away with notes, tips and guides to what we covered. (Slides)

Speaker: Timothy J. Spann
Tim Spann is a Principal Developer Advocate in Data In Motion for Cloudera. He works with Apache NiFi, Apache Kafka, Apache Pulsar, Apache Flink, Flink SQL, Apache Pinot, Trino, Apache Iceberg, DeltaLake, Apache Spark, Big Data, IoT, Cloud, AI/DL, machine learning, and deep learning. Tim has over ten years of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton & NYC on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark.

[zakkcoetzee]

All I can say is WOW, the growth on this project since I started using it 5+ years ago is insane. Big shout out to all the contributors.

[penguinab]

getting the schemas and inferring schema when you don't want to define things has definitely improved over the last 5 years.