Building Bilibili's Real-Time Streaming Platform with Apache Flink and AI
The presentation by Bilibili's real‑time platform lead details the design and implementation of a Flink‑based streaming data platform, explains how AI workloads are integrated, shares architectural decisions and operational insights, and provides the full slide deck for knowledge dissemination.
This article shares the content of a technical talk delivered by Zheng Zhisheng, the head of Bilibili's real‑time platform, at Flink Forward Asia 2019. The talk focuses on Bilibili's streaming computation platform built on Apache Flink and its integration with artificial intelligence use cases.
The presentation covers the overall architecture, key components, data ingestion, state management, fault tolerance, and performance optimization strategies employed to support massive real‑time data streams. It also illustrates practical AI scenarios where the streaming platform feeds models for online inference and decision making.
All slides from the session are provided as images, and the material is shared solely for educational purposes, with copyright belonging to the speaker and the Flink community.
Signed-in readers can open the original source through BestHub's protected redirect.
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