Naci Simsek
Ververica, Senior Customer Success Technical Manager
Düsseldorf, Germany
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Naci Simsek is a Senior Customer Success Technical Manager at Ververica with over 17 years of experience in IT and Telecom. He began his career as a Customer Support Engineer at Nortel Networks, advancing through roles as Software Engineer, Engineering Team Lead, Project Manager, and Solutions Architect at Huawei. Over nearly a decade, he specialized in customer-facing big data solutions as a Platform Engineer, BI Engineer, and Data Engineer. In his current position, he supports customers in leveraging Apache Flink for real-time data streaming across on-premises and cloud environments.
He holds a Bachelor’s degree in Computer Engineering from Ege University, an MBA from Bahcesehir University, and the PMP® certification.
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The Flink Mistake Playbook: 2 Years of Real-World Debugging
Even seasoned engineers can encounter unexpected challenges when building with Apache Flink, often leading to performance bottlenecks or stability issues. This session confronts three critical, yet common, mistakes that frequently trip up Flink users and significantly impact pipeline health. Attendees will learn how to effectively navigate Kafka connector migration rules to prevent uncontrolled state growth, optimize serialization to eliminate throughput-sapping Kryo fallbacks, and implement strategies for even load distribution across their Flink clusters. The talk offers practical, actionable insights, empowering developers to avoid these pitfalls and build truly robust, high-performance Flink applications.
Lets Deeploy Flink - Uncovering Hidden Depths of Yarn, Docker, Kubernetes & Beyond
Choosing the right environment to run Apache Flink applications—Standalone, Docker, Kubernetes, or YARN—is a critical first decision that often presents a bewildering array of options. This session cuts through the complexity, providing a practical, in-depth comparison of these core deployment modes. The talk delves into their fundamental differences, evaluates their respective pros and cons, and pinpoints when each mode truly shines (and when to avoid it). Engineers will leave equipped with the clarity to confidently select the optimal deployment strategy, ensuring their Flink applications are set up for success from the start.
Data Lakes on Flink: Hudi, Iceberg, Paimon - Decoding the Deluge of Formats
Building robust data lakes with Apache Flink often leads to a crucial decision: selecting the right open table format from options like Apache Hudi, Iceberg, and Paimon. This session cuts through the common confusion, providing a head-to-head comparison of these seemingly similar technologies. Attendees will learn the three key distinctions vital for making an informed choice: how each format organizes data under the hood, their respective optimizations for various update and query patterns, and the nuances of their integration with Flink. The talk equips engineers with the practical understanding needed to confidently select the best-suited format and build an optimized Flink-powered data lake architecture.
Build Real-Time ML & AI Pipelines with Apache Flink
This session provides a comprehensive guide to designing and building real-time machine learning and AI pipelines from the ground up using Apache Flink. It illuminates how Flink's unified streaming model, powered by its DataStream and SQL APIs, enables low-latency inference with both remote and embedded models. Attendees will witness live demonstrations of real-time training scenarios, such as click-event streaming and vector embedding updates, and learn to stitch together powerful Generative AI workflows with Retrieval-Augmented Generation. The talk equips engineers with a concrete, battle-tested blueprint for deploying scalable, production-grade ML/AI applications in a true streaming paradigm.
The Need for Speed: Optimizing Apache Flink for Low-Latency Stream Processing
While Apache Flink excels at low-latency stream processing, achieving optimal end-to-end performance often requires specialized tuning beyond standard configurations. This session dives deep into critical best practices and advanced techniques for drastically reducing latency in Flink applications, ensuring your pipelines operate at peak efficiency. Attendees will explore direct latency optimizations, including resource allocation, state backend choices, and network buffer tuning, alongside strategies to improve throughput that inherently enhance real-time responsiveness. The talk provides a battle-tested blueprint for understanding, measuring, and systematically eliminating bottlenecks, empowering engineers to build truly high-performance Flink solutions.
Flink Materialized Tables: Revolutionizing Batch and Stream Data Pipelines
Apache Flink introduces Materialized Tables, a powerful new feature designed to significantly simplify the development and management of both batch and streaming data pipelines within a unified SQL environment. This session will unveil how Flink's Materialized Tables automatically handle complex data transformations and ensure data freshness by defining queries and desired freshness targets. Attendees will discover the core concepts, including flexible refresh modes (continuous and full), and gain practical insights into creating, managing, and optimizing these tables for various use cases, empowering them to build more consistent and efficient data architectures.
Flink Forward 2025 Barcelona Sessionize Event Upcoming
Data Streaming Summit San Francisco 2025 Sessionize Event
Naci Simsek
Ververica, Senior Customer Success Technical Manager
Düsseldorf, Germany
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