Apache Flink is designed for real-time, low-latency data processing — but getting it to run at peak performance takes more than default settings. In this session, we’ll go under the hood to explore advanced optimization strategies that can help you squeeze every millisecond of performance out of your Flink pipelines.
You’ll learn how to:
- Tune resource allocation and parallelism for maximum efficiency
- Choose and configure the right state backends to balance speed and durability
- Optimize network buffers and data exchange for minimal processing delays
- Identify and remove hidden bottlenecks that slow down real-time applications
- Measure latency and throughput effectively to guide continuous improvement
This talk shares field-proven techniques and tuning frameworks used in production environments to achieve ultra-low latency at scale — helping you build Flink applications that truly deliver real-time performance.
With over 16 years in IT and Telecom, I began as a Customer Support Engineer at Nortel Networks and advanced through roles such as Software Engineer, Engineering Team Lead, Project Manager, and Solutions Architect at Huawei. For nearly a decade, I’ve specialized in customer-facing big data solutions—working as a Platform Engineer, BI Engineer, and Data Engineer. Today, as a Technical Account Manager at Ververica, I help customers leverage Apache Flink for real‑time data streaming on both on‑premises and cloud environments.
I hold a Computer Engineering degree from Ege University, an MBA from Bahcesehir University, and certifications including PMP® and German B1.
Outside of work, I enjoy traveling with my wife and our British Shorthair, Bamboo, along with photography, exercise, yoga, and meditation.
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