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Latest from Bilibili Tech

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Bilibili Tech

Oct 25, 2024 · Operations

Bilibili Data Center Migration: Planning, Execution, and Lessons Learned

Bilibili’s 18‑month, multi‑regional data‑center migration moved tens of thousands of servers using a high‑frequency rolling strategy, combining meticulous planning, cross‑team coordination, automated rack placement and rigorous checklists to achieve significant cost savings, higher utilization, improved stability and greener operations.

AutomationData Center Migrationcapacity planning

0 likes · 21 min read

Bilibili Data Center Migration: Planning, Execution, and Lessons Learned

Bilibili Tech

Oct 22, 2024 · Mobile Development

Understanding Swift Macros in Swift 5.9 and Their Applications

Swift 5.9’s new macro system lets developers generate type‑safe code at compile time via external plug‑ins, using role‑based declarations such as @attached and @freestanding to create properties, extensions, or warnings, thereby reducing repetitive boiler‑plate and improving safety in large‑scale architectures like MVVP modules and exposure frameworks.

Compiler PluginMetaprogrammingSwift

0 likes · 20 min read

Understanding Swift Macros in Swift 5.9 and Their Applications

Bilibili Tech

Oct 18, 2024 · Backend Development

Design and Platformization of Bilibili's Paid Exclusive Video and Short Drama Services

Bilibili transformed its rapidly growing charging‑exclusive video and short‑drama services into a modular, platform‑based architecture that separates manuscript, video, charging and drama domains, adds fine‑grained data operations, real‑time observability and robust stability mechanisms, thereby reducing technical debt and enabling scalable, customizable creator‑fan interactions.

Bilibilishort dramavideo monetization

0 likes · 16 min read

Design and Platformization of Bilibili's Paid Exclusive Video and Short Drama Services

Bilibili Tech

Oct 15, 2024 · Frontend Development

AST‑Based Visual Programming for Vue SFC: Design, Implementation, and Demo

By binding a Vue single‑file component’s AST to a visual UI, this project parses templates with node‑html‑parser, transforms scripts via Babel, and processes styles with standard loaders, allowing developers to edit component properties visually, automatically regenerate synchronized source code, and preview changes, with a prototype demo and planned drag‑and‑drop, styling, state, AI, and CI/CD extensions.

ASTBabelVisual Programming

0 likes · 10 min read

AST‑Based Visual Programming for Vue SFC: Design, Implementation, and Demo

Bilibili Tech

Oct 11, 2024 · Big Data

Business Observability and Real-Time Event Streaming Architecture for Content Production

The paper proposes a business‑observability framework for a content‑production pipeline—illustrated by Bilibili’s workflow—by modeling archives as entities, assigning global AIDs for end‑to‑end tracing, and leveraging a Kafka‑Flink‑ClickHouse event‑streaming platform to monitor real‑time latency, bottlenecks, and safety audits across the entire production line.

Content ProductionEvent StreamingReal-time Analytics

0 likes · 19 min read

Business Observability and Real-Time Event Streaming Architecture for Content Production

Bilibili Tech

Oct 8, 2024 · Artificial Intelligence

ICDAR 2024 Historical Map Text Recognition Competition: DNTextSpotter Methodology and Results

The ICDAR 2024 Historical Map Text Recognition competition was won by Bilibili’s DNTextSpotter, a Transformer‑based model built on DeepSolo and ViTAE‑v2 that uses deformable self‑attention, dual‑query decoding and denoising training, combined with mixed‑vocabulary fine‑tuning, advanced loss functions and strict PDQ/PWQ/PCQ metrics to achieve state‑of‑the‑art dense, rotated, arbitrary‑shaped text detection and recognition on historical maps and real‑world multimedia.

DNTextSpotterDeep LearningHistorical Map OCR

0 likes · 17 min read

ICDAR 2024 Historical Map Text Recognition Competition: DNTextSpotter Methodology and Results

Bilibili Tech

Sep 27, 2024 · Backend Development

Concurrency Issues and Race Condition Mitigation in Bilibili's Content Production System

Bilibili tackled race‑condition vulnerabilities in its massive video content pipeline by replacing simple timestamp checks with optimistic locking (CAS) and rate‑limiting locks, adding version verification and observation tools that now eliminate missed reviews and improve security, scalability, and real‑time editing reliability.

BilibiliOptimistic Lockconcurrency

0 likes · 10 min read

Concurrency Issues and Race Condition Mitigation in Bilibili's Content Production System

Bilibili Tech

Sep 24, 2024 · Backend Development

Technical Implementation of Bilibili's Game Live Streaming Interactive Features: 'Play Together' and 'Help Me Play'

Bilibili’s game live‑stream platform implements interactive features ‘Play Together’ and ‘Help Me Play’ by using Redis ZSET queues, MySQL persistence, real‑time streamer recommendation, ticket‑based purchase flows, state‑machine order handling, and comprehensive monitoring to ensure reliable, scalable viewer‑streamer gameplay collaboration.

Backend DevelopmentBilibiliMySQL

0 likes · 12 min read

Technical Implementation of Bilibili's Game Live Streaming Interactive Features: 'Play Together' and 'Help Me Play'

Bilibili Tech

Sep 20, 2024 · Frontend Development

Bilibili Front‑End Error Monitoring: Architecture, SDK, White‑Screen Detection and Data Governance

Bilibili’s front‑end team built a custom “mirror” SDK and full‑stack monitoring platform that captures JavaScript and resource errors, detects white‑screens, logs user behavior offline, routes data through Kafka‑ClickHouse pipelines to visual dashboards, and provides one‑click alerts, now serving over 1,700 projects across 85% of business lines.

AlertingData VisualizationSDK

0 likes · 33 min read

Bilibili Front‑End Error Monitoring: Architecture, SDK, White‑Screen Detection and Data Governance

Bilibili Tech

Sep 18, 2024 · Artificial Intelligence

Index-1.9B-32K: A 2% GPT-Size Model with Powerful Long-Context Capabilities

Index-1.9B-32K is a 1.9B-parameter model with a 32K token context window, achieving strong long‑text performance comparable to larger models while using only about 2% of GPT‑4’s compute, trained via long pre‑training and supervised fine‑tuning, with a trade‑off of reduced short‑context ability.

AIEvaluationLong Context

0 likes · 12 min read

Index-1.9B-32K: A 2% GPT-Size Model with Powerful Long-Context Capabilities