Tim Berglund
ÜberConf
Denver · July 17 - 20, 2018
VP Developer Relations at Confluent
Tim is a teacher, author, and technology leader with Confluent, where he serves as the Vice President of Developer Relations. He is a regular speaker at conferences and a presence on YouTube explaining complex technology topics in an accessible way. He tweets as @tlberglund, blogs every few years at http://timberglund.com. He has three grown children and two grandchildren, a fact about which he is rather excited.
Presentations
Streaming Data with Apache Kafka
The toolset for building scalable data systems is maturing, having adapted well to our decades-old paradigm of update-in-place databases. We ingest events, we store them in high-volume OLTP databases, and we have new OLAP systems to analyze them at scale—even if the size of our operation requires us to grow to dozens or hundreds of servers in the distributed system. But something feels a little dated about the store-and-analyze paradigm, as if we are missing a new architectural insight that might more efficiently distribute the work of storing and computing the events that happen to our software. That new paradigm is stream processing.
Kafka Connect
Your goal is simple: take that is happening in your company—every click, every database change, every application log—and made it all available as a real-time stream of well-structured data? No big deal! You’re just taking your decades-old, batch-oriented data integration and data processing and migrating to to real-time streams and real-time processing. In your shop, you call that Tuesday. But of the several challenges to tackle, you’ll have to get data in and out of that stream processing system, and there’s a whole bunch of code there you don’t want to write. This is where Kafka Connect comes in.
Processing Streaming Data with ksqlDB
It has been a while since you left the easy days of batch processing behind: the lazy ETL jobs that had all night to run, the relaxed SLAs that let you take lunches like Don Draper, the languid bankers’ hours: the salad days of your data processing career. Those days are over now, and producing real-time results on streaming data is the new order of the day. Two seconds is the new overnight.
Four Distributed Systems Architectural Patterns
Developers and architects are increasingly called upon to solve big problems, and we are able to draw on a world-class set of open source tools with which to solve them. Problems of scale are no longer consigned to the web’s largest companies, but are increasingly a part of ordinary enterprise development. At the risk of only a little hyperbole, we are all distributed systems engineers now.