Workshop Real-Time Stream Processing - February 23-24, 2021 ONLINE


In this two days workshop you will learn how to process unbounded streams of data in real-time using popular open-source frameworks. We focus mostly on Apache Flink and Apache Kafka – the most promising open-source stream processing framework that is more and more frequently used in production.

During the course we simulate real-world end-to-end scenario – processing logs generated by users interacting with a mobile application in real-time. The technologies that we use include Kafka and Flink. All exercises will be done using either a local docker environment or within your IDE.


   Target Audience

Data engineers who are interested in leveraging large-scale and distributed tools to process streams of data in real-time.



Some experience coding in Java or Scala and basic familiarity with Big Data tools (HDFS, YARN).


    Participant’s ROI

♦   Concise and practical knowledge of applying stream processing to solve business problems.
♦   Hands-on coding experience under supervision of experienced Flink engineers.
♦   Tips about real world applications and best practices.


    Training Materials

All participants will get training materials in the form of PDF files containing slides with theory and exercise manual with the detailed description of all exercises. During the workshops the exercises can be done using either a local docker environment or within your IDE.


    Time Box
This is a two-day event, 4h per day, there will be some breaks between sessions.



February 23, 2021,  Day 1 (9 am - 1 pm)

Session #1 - Introduction to Apache Kafka

Session #2 - Apache Flink

♦   Introduction and key concepts
♦   Basic Flink API
♦   Hands-on exercises

February 24, 2021,  Day 2 (9 am - 1 pm)

Session #3- Flink cont.

♦   Time & Windows
♦   Integration with Kafka
♦   Hands-on exercises

Session #4 - Flink c.d.

♦   Stateful operations
♦   Best practices
♦   Daemons and cluster infrastructure
♦   Hands-on exercises

Session #5  - Summary and comparison with other stream processing engines

   Keywords: Kafka, Flink, Real Time Processing, Low Latency Stream Processing,


    Session leaders:


Data Engineer
Big Data Engineer



Evention sp. z o.o

Rondo ONZ 1 Str,

Warsaw, Poland


Weronika Warpas

© 2024 | This site uses cookies.