The data Artisans Blog
Apache Flink, stream processing, event-driven applications, and more.
On Designing a Stream Processing BenchmarkJuly 27, 2017
Update December 18, 2017: We wrote a follow-up blog post about stream processing benchmarks that goes into more detail about the issues we see with common benchmarking methods. It serves as a useful a...
Dynamically Configured Stream Processing: How BetterCloud Built an Alerting System with Apache Flink®June 29, 2017
Many Apache Flink® users are building applications for alerting or anomaly detection, and ING and Mux are two such examples from the most recent Flink Forward conference. Today, we’ll highlight the...
data Artisans – Mesosphere Webinar + Live Q&A: April 25 at 10am Pacific TimeMarch 29, 2017
Jamie Grier, data Artisans’ Director of Applications Engineering, will co-host a webinar with members of the Mesosphere team on April 25, 2017, at 10am Pacific Time. You can register here. We hope y...
Queryable State in Apache Flink® 1.2.0: An Overview & DemoMarch 24, 2017
Ufuk Celebi (@iamuce) is a co-founder and software engineer at data Artisans. 2016 was the year that stateful, event-time, and event-at-a-time stream processing arrived as the paradigm for high-thro...
Drivetribe’s Modern Take On CQRS With Apache Flink®March 9, 2017
This is a guest post from Aris Koliopoulos, a senior software engineer at London-based Drivetribe. Drivetribe is the world’s digital hub for motoring. The platform was created by former Top Gear pre...
Stream Processing Myths DebunkedNovember 23, 2016
By @kostas_tzoumas and @wints Needless to say, we here at data Artisans spend a lot of time thinking about stream processing. Even cooler: we spend a lot of time helping others think about stream pro...
Savepoints, Part 2: Streaming Applications in the Pit LaneNovember 16, 2016
By Fabian Hueske (@fhueske) and Mike Winters (@wints) Last month, we gave a high-level overview of Apache Flink® savepoints and touched on why and how you’d reprocess data in a streaming applicatio...
Savepoints: Turning Back TimeOctober 14, 2016
This post is the first in a series where the data Artisans team will highlight some of Apache Flink’s® core features. By Fabian Hueske (@fhueske) and Mike Winters (@wints) Stream processing is comm...
Apache Flink and Apache Kafka StreamsAugust 31, 2016
This blog post is written jointly by Stephan Ewen, CTO of data Artisans, and Neha Narkhede, CTO of Confluent. You can also find this post at the Confluent blog. The open source stream processing space...