10 citations · 23 across the 6 of their papers we have counts for
6 papers
Performance Optimization in Stream Processing Systems: Experiment-Driven Configuration Tuning for Kafka Streams
David Chen, Sören Henning, Kassiano Matteussi +1
Configuring stream processing systems for efficient performance, especially in cloud-native deployments, is a challenging and largely manual task. We present an experiment-driven a…
Should I Run My Cloud Benchmark on Black Friday?
Sören Henning, Adriano Vogel, Esteban Perez-Wohlfeil +2
Benchmarks and performance experiments are frequently conducted in cloud environments. However, their results are often treated with caution, as the presumed high variability of pe…
When Should I Run My Application Benchmark?: Studying Cloud Performance Variability for the Case of Stream Processing Applications
Sören Henning, Adriano Vogel, Esteban Perez-Wohlfeil +2
Performance benchmarking is a common practice in software engineering, particularly when building large-scale, distributed, and data-intensive systems. While cloud environments off…
A Comprehensive Benchmarking Analysis of Fault Recovery in Stream Processing Frameworks
Adriano Vogel, Sören Henning, Esteban Perez-Wohlfeil +2
Nowadays, several software systems rely on stream processing architectures to deliver scalable performance and handle large volumes of data in near real-time. Stream processing fra…
High-level Stream Processing: A Complementary Analysis of Fault Recovery
Adriano Vogel, Sören Henning, Esteban Perez-Wohlfeil +2
Parallel computing is very important to accelerate the performance of software systems. Additionally, considering that a recurring challenge is to process high data volumes continu…
ShuffleBench: A Benchmark for Large-Scale Data Shuffling Operations with Distributed Stream Processing Frameworks
Sören Henning, Adriano Vogel, Michael Leichtfried +2
Distributed stream processing frameworks help building scalable and reliable applications that perform transformations and aggregations on continuous data streams. This paper intro…