codecentric mittendrin
Meetups, Stammtische, Hackathons, User Groups: Die codecentric AG ist weit mehr als die Summe ihrer Mitarbeiter und Projekte.
IoT Hessen (Kassel) 24.09.2019 18:00 Uhr
Open Source Software & Industrial IoT
In unserem nächsten Meetup wollen wir uns mit Open-Source-Software für das Industrial IoT beschäftigen. Details folgen in Kürze.
IoT Hessen (Frankfurt) 21.08.2019 18:00 Uhr
The Things Network
After a summer break, we’ll be back on August 21st with a meetup on The Things Network (a global open LoRaWAN network). https://www.thethingsnetwork.org/ Stay tuned for more details!
DevOps Meetup Frankfurt 13.08.2019 18:00 Uhr
How to fix flaky tests on the real device cloud
Agenda: 6 pm: Get together 6.30 pm: Talk by Daniel Paulus, Lead Software Engineer at the Sauce Labs 7.00 pm: Q&A 7.30 – 9 pm: Networking, Catering About the talk: The most challenging aspect of running tests on a real ...
Stream Processing and War Stories
We just renamed the group from SMACK to Fast Data and would like to host the second meetup. We will attempt to host this every two months, so please do not hesitate if you have any cool talks! See you around! Agenda for the evening:
SMACK stack from the trenches (Achim Nierbeck)
In this talk I will give an overview about the SMACK – Stack (Streaming, Mesos, Akka, Cassandra, Kafka) and tell about the experiences made with this stack and how to fine tune it for massive data. For a better understanding on how a SMACK stack might work, a demonstration showing how to stream live bus data from Los Angeles with Spark and Flink is shown.
Stream Processing Comparison (Matthias Niehoff)
In this talk I will give an overview on various concepts used in data stream processing. Most of them are used for solving problems in the field of time, focussing on processing time compared to event time. The techniques shown include the Dataflow API as it was introduced by Google and the concepts of stream and table duality. But I will also come up with other problems like data lookup and deployment of streaming applications and various strategies on solving these problems. In the end I will give a brief outline on the implementation status of those strategies in the popular streaming frameworks Apache Spark Streaming, Apache Flink and Kafka Streams.
As always Drinks and Pizza are on us! Please care, Please share!
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