The technical product team of iQIYI
iQIYI replaced its costly Lambda architecture with a unified Iceberg‑based lakehouse that combines Flink streaming and batch processing, cutting data latency from hours to minutes, supporting thousands of tables via a multi‑table sink, guaranteeing completeness, and saving millions of RMB in operational costs.
A Docker image upgrade reduced Netty EventLoop threads, causing a Pub/Sub listener’s blocking Future.get() to stall one thread, fill a Redis cluster connection’s receive buffer and trigger widespread Redis timeouts in the custom Lettuce cache framework, which were eliminated by increasing I/O threads or making the callback asynchronous.
iQIYI improves its Android app for low‑end phones by classifying devices, streamlining startup with task‑based scheduling and baseline profiles, reducing UI thread load through card layout hard‑coding, message queuing, effect degradation, and pre‑fetching data, while continuously monitoring performance to ensure faster, smoother user experiences.
By fusing sparse‑feature operators, enabling multi‑stream execution, consolidating data copies, and merging inference batches, iQIYI reduced GPU CTR model latency to CPU‑level, boosted throughput over sixfold, and cut operational costs by more than 40%, overcoming launch‑overhead bottlenecks.
iQIYI migrated hundreds of petabytes of Hive tables to Apache Iceberg using dual‑write, in‑place, and CTAS strategies, combined with partition pruning, Bloom filters, and Trino/Alluxio optimizations, achieving up to 40% lower query latency, simplified pipelines, and faster, cost‑effective data lake operations.
iQIYI’s ad ranking system replaces static, hash‑based embeddings with TFRA dynamic embeddings to efficiently handle massive sparse ID features, eliminates collisions and I/O bottlenecks, isolates memory during hot model swaps, enabling billion‑parameter models that boost revenue by 4.3 % while planning adaptive embedding sizes for future improvements.
iQIYI optimized its app’s visual experience by progressively replacing JPG with WebP, HEIC, and finally AVIF—using a caplist‑driven CDN, self‑developed decoders and on‑demand production pipelines—to cut image sizes, reduce CDN bandwidth by over 30 % and maintain quality across static, transparent and animated assets.
The article describes how redesigning a TV streaming service from a single to a dual‑service architecture, leveraging Android Binder, optimized protocol startup, adaptive networking, and session‑based monitoring dramatically boosted stability above 99%, protocol success over 98.5%, and issue‑resolution efficiency via systematic batch analysis and A/B testing.
iQIYI's proactive compliance risk disposal platform and full‑lifecycle privacy protection scheme were recognized by MIIT as outstanding cases, showcasing engineering‑driven privacy integration across product development, release, and operation, improving compliance rates, reducing risks, and enhancing user experience while setting industry standards.
By introducing distributed and local shared variables that propagate user profiles via trace context and cache parallel requests, the iQIYI strategy engine cuts redundant DMP calls, reduces traffic up to 25%, lowers P99 latency by nearly 50%, and achieves a 90% cost saving compared to step‑function micro‑services.
