@tom_doerr: 300+ 篇解决大规模实际问题的工程文章 https://github.com/ashishps1/awesome-engineering-article…

300+ 篇解决大规模实际问题的工程文章 https://github.com/ashishps1/awesome-engineering-articles… — # ashishps1/awesome-engineering-articles 来源：https://github.com/ashishps1/awesome-engineering-articles # 精选工程文章合集 > 来自顶尖科技公司的 300+ 篇精选工程博客文章。了解最优秀的工程团队如何解决大规模实际问题。 — ## 目录 Airbnb · Amazon Science · Atlassian · Booking.com · Canva · Coinbase · Discord · DoorDash · Dropbox · eBay · Facebook/Meta · Figma · Flipkart · GitHub · Google Research · Instagram · Instacart · LinkedIn · Lyft · Netflix · Notion · PayPal · Pinterest · Quora · Razorpay · Reddit · Salesforce · Shopify · Slack · Snap · Spotify · Stripe · Swiggy · Tinder · Twitch · Twitter/X · Uber · Walmart · Zomato — ## Airbnb > Airbnb 工程博客 (https://medium.com/airbnb-engineering) | # | 文章 | 主题 | 年份 | |—|———|––––|——| | 1 | 基于嵌入的 Airbnb 搜索检索方法 (https://medium.com/airbnb-engineering/embedding-based-retrieval-for-airbnb-search-aabebfc85839) | 搜索，AI/ML | 2025 | | 2 | Airbnb 如何使用 HTTP 流式传输提升页面性能 (https://medium.com/airbnb-engineering/improving-performance-with-http-streaming-ba9e72c66408) | 性能，前端 | 2023 | | 3 | Airbnb 用于更快、更可靠读取密集型工作负载的数据框架 (https://medium.com/airbnb-engineering/riverbed-optimizing-data-access-at-airbnbs-scale-c37ecf6456d9) | 数据工程，性能 | 2023 | | 4 | 在分布式支付系统中避免重复支付 (https://medium.com/airbnb-engineering/avoiding-double-payments-in-a-distributed-payments-system-2981f6b070bb) | 支付，架构 | 2019 | ## Amazon Science > Amazon Science 博客 (https://www.amazon.science/blog) | # | 文章 | 主题 | 年份 | |—|———|––––|——| | 1 | 训练代码生成模型以调试其自身输出 (https://www.amazon.science/blog/training-code-generation-models-to-debug-their-own-outputs) | AI/ML | 2025 | | 2 | 亚马逊基于生成式 AI 的购物助手 Rufus 背后的技术 (https://www.amazon.science/blog/the-technology-behind-amazons-genai-powered-shopping-assistant-rufus) | AI/ML | 2024 | | 3 | 确保顾客不错过热门产品 (https://www.amazon.science/blog/ensuring-that-customers-dont-miss-out-on-trending-products) | 搜索，AI/ML | 2023 | | 4 | 从结构化搜索到学习与排序和检索 (https://www.amazon.science/blog/from-structured-search-to-learning-to-rank-and-retrieve) | 搜索，AI/ML | 2023 | | 5 | 实时无效机器人广告点击 (https://www.amazon.science/blog/invalidating-robotic-ad-clicks-in-real-time) | 安全，数据工程 | 2023 | | 6 | 使用大型语言模型 (LLM) 合成训练数据 (https://www.amazon.science/blog/using-large-language-models-llms-to-synthesize-training-data) | AI/ML | 2023 | | 7 | DynamoDB 十年的经验教训 (https://www.amazon.science/blog/lessons-learned-from-10-years-of-dynamodb) | 数据库 | 2022 | | 8 | 使用图神经网络推荐相关产品 (https://www.amazon.science/blog/using-graph-neural-networks-to-recommend-related-products) | AI/ML，搜索 | 2022 | ## Atlassian > Atlassian 工程博客 (https://www.atlassian.com/blog/developer) | # | 文章 | 主题 | 年份 | |—|———|––––|——| | 1 | Atlassian 如何扩展并提升 Jira 导出服务的吞吐量 (https://www.atlassian.com/blog/atlassian-engineering/boosting-performance-how-we-scaled-and-enhanced-throughput-in-the-jira-export-service) | 性能，架构 | 2025 | | 2 | Atlassian 的一项关键服务如何持续保持超过 99.9999% 的可用性 (https://www.atlassian.com/blog/atlassian-engineering/atlassian-critical-services-above-six-nines-of-availability) | 基础设施 | 2022 | | 3 | Atlassian 如何让 Bitbucket Cloud 的 HTTPS Git push 更快 (https://www.atlassian.com/blog/atlassian-engineering/faster-git-push-over-https-for-bitbucket-cloud) | 性能 | 2022 | | 4 | Atlassian 如何重塑 Confluence Cloud 搜索 (https://www.atlassian.com/blog/atlassian-engineering/revamping-confluence-cloud-search) | 搜索 | 2021 | | 5 | 在 Jira Cloud 中缓存 JQL 搜索 (https://www.atlassian.com/blog/atlassian-engineering/reducing-jql-database-load-with-caches) | 缓存，数据库 | 2021 | | 6 | 扩展、重构和分解 Confluence Cloud (https://www.atlassian.com/blog/atlassian-engineering/scaling-rearchitecting-and-decomposing-confluence-cloud) | 架构 | 2020 | | 7 | 扩展 Bitbucket 的数据库 (https://www.atlassian.com/blog/atlassian-engineering/scaling-bitbuckets-database) | 数据库 | 2020 | | 8 | Atlassian 在 AWS 上扩展低延迟、多区域服务的历程 (https://www.atlassian.com/blog/atlassian-engineering/aws-scaling-multi-region-low-latency-service) | 基础设施，性能 | 2019 | ## Booking.com > Booking.com 技术博客 (https://blog.booking.com/) | # | 文章 | 主题 | 年份 | |—|———|––––|——| | 1 | 使用统计分析进行时间序列异常检测 (https://medium.com/booking-com-development/anomaly-detection-in-time-series-using-statistical-analysis-cc587b21d008) | 可观测性，数据工程 | 2025 | | 2 | Booking 如何通过单次代码变更削减 20% 的云成本 (https://medium.com/booking-com-development/use-compression-luke-cut-20-of-the-cloud-cost-with-a-single-code-change-510d14d96891) | 成本优化 | 2025 | | 3 | Booking.com 高性能排名平台背后的工程 (https://medium.com/booking-com-development/the-engineering-behind-booking-coms-ranking-platform-a-system-overview-2fb222003ca6) | 搜索，性能 | 2024 | | 4 | Booking.com 如何利用图技术进行实时欺诈检测和预防 (https://medium.com/booking-com-development/leverage-graph-technology-for-real-time-fraud-detection-and-prevention-438336076ea5) | 安全 | 2024 | | 5 | Booking.com 如何利用生存模型预测取消订单 (https://booking.ai/predicting-cancellations-with-survival-modeling-a299af54249b) | AI/ML | 2024 | ## Canva > Canva 工程博客 (https://www.canva.dev/blog/engineering/) | # | 文章 | 主题 | 年份 | |—|———|––––|——| | 1 | Canva 的连续数据平台 (https://www.canva.dev/blog/engineering/snowpipe-streaming/) | 数据工程 | 2025 | | 2 | Canva 的绘图工具是如何工作的 (https://www.canva.dev/blog/engineering/behind-the-draw/) | 前端 | 2024 | | 3 | Canva 如何每天收集 250 亿个事件 (https://www.canva.dev/blog/engineering/product-analytics-event-collection/) | 数据工程 | 2024 | | 4 | Canva 可扩展且可靠的内容使用计数服务 (https://www.canva.dev/blog/engineering/scaling-to-count-billions/) | 架构，性能 | 2024 | | 5 | Canva 如何每年在 Amazon S3 成本上节省数百万美元 (https://www.canva.dev/blog/engineering/optimising-s3-savings/) | 成本优化 | 2023 | | 6 | Canva 如何将媒体上传量从每天 0 扩展到 5000 万次 (https://www.canva.dev/blog/engineering/from-zero-to-50-million-uploads-per-day-scaling-media-at-canva/) | 性能，基础设施 | 2022 | | 7 | Canva 快速且可扩展的反向图像搜索 (https://www.canva.dev/blog/engineering/simple-fast-and-scalable-reverse-image-search-using-perceptual-hashes-and-dynamodb/) | 搜索，数据库 | 2022 | | 8 | Canva 如何利用 RSocket 实现实时协作 (https://www.canva.dev/blog/engineering/enabling-real-time-collaboration-with-rsocket/) | 消息传递，架构 | 2021 | ## Coinbase > Coinbase 工程博客 (https://www.coinbase.com/blog/landing/engineering) | # | 文章 | 主题 | 年份 | |—|———|––––|——| | 1 | Coinbase 如何优化网络请求 (https://www.coinbase.com/blog/boosting-app-performance-strategies-to-optimize-network-requests) | 性能 | 2024 | | 2 | 加速 Coinbase 深度学习的应用 (https://www.coinbase.com/blog/accelerating-deep-learning-adoption-at-coinbase) | AI/ML | 2024 | | 3 | 在 Coinbase 推出企业级生成式 AI 解决方案的经验教训 (https://www.coinbase.com/blog/lessons-from-launching-enterprise-grade-genAI-solutions-at-Coinbase) | AI/ML | 2024 | | 4 | Coinbase 如何使用机器学习预测流量并扩展数据库 (https://www.coinbase.com/blog/how-coinbase-is-using-machine-learning-to-predict) | AI/ML，数据库 | 2024 | | 5 | 在 Coinbase 检测欺诈性交易 (https://www.coinbase.com/blog/detecting-fraudulent-transactions-coinbase-scalable-blockchain-address-risk) | 安全 | 2023 | | 6 | 在 Coinbase 构建通知平台 (https://www.coinbase.com/blog/building-a-notification-platform-at-coinbase) | 消息传递，架构 | 2022 | ## Discord > Discord 工程博客 (https://blog.discord.com/) | # | 文章 | 主题 | 年份 | |—|———|––––|——| | 1 | Discord 如何将 Websocket 流量减少 40% (https://discord.com/blog/how-discord-reduced-websocket-traffic-by-40-percent) | 性能，消息传递 | 2024 | | 2 | Discord 如何存储数万亿条消息 (https://discord.com/blog/how-discord-stores-trillions-of-messages) | 数据库 | 2023 | | 3 | 在单个服务器中承载百万级在线用户，突破 Discord 的极限 (https://discord.com/blog/maxjourney-pushing-discords-limits-with-a-million-plus-online-users-in-a-single-server) | 性能，基础设施 | 2023 | | 4 | Discord 如何使用机器学习打造令人愉悦的通知体验 (https://discord.com/blog/building-delightful-notifications-using-ml) | AI/ML，消息传递 | 2022 | | 5 | Discord 如何从数万亿个数据点中创建洞察 (https://discord.com/blog/how-discord-creates-insights-from-trillions-of-data-points) | 数据工程 | 2021 | ## DoorDash > DoorDash 工程博客 (https://careersatdoordash.com/engineering-blog/) | # | 文章 | 主题 | 年份 | |—|———|––––|——| | 1 | DoorDash 如何使用 LLM 转录餐厅菜单照片 (https://careersatdoordash.com/blog/doordash-llm-transcribe-menu/) | AI/ML | 2025 | | 2 | DoorDash 如何利用 LLM 提升搜索检索效果 (https://careersatdoordash.com/blog/how-doordash-leverages-llms-for-better-search-retrieval/) | AI/ML，搜索 | 2024 | | 3 | 利用大型语言模型构建 DoorDash 的产品知识图谱 (https://careersatdoordash.com/blog/building-doordashs-product-knowledge-graph-with-large-language-models/) | AI/ML，数据工程 | 2024 | | 4 | DoorDash 的内部搜索引擎 (https://careersatdoordash.com/blog/introducing-doordashs-in-house-search-engine/) | 搜索 | 2024 | | 5 | DoorDash 的写入密集型、可扩展且可靠的库存平台 (https://careersatdoordash.com/blog/how-doordash-designed-a-successful-write-heavy-scalable-and-reliable-inventory-platform/) | 架构，数据库 | 2023 | | 6 | DoorDash 使用 Kafka 和 Flink 构建可扩展的实时事件处理 (https://careersatdoordash.com/blog/building-scalable-real-time-event-processing-with-kafka-and-flink/) | 数据工程 | 2022 | | 7 | DoorDash 关于改善高流量网页性能的经验教训 (https://careersatdoordash.com/blog/doordashs-lessons-on-improving-performance-on-high-traffic-web-pages/) | 性能，前端 | 2022 | | 8 | DoorDash 如何应用客户端缓存将特征库性能提升 70% (https://careersatdoordash.com/blog/how-we-applied-client-side-caching/) | 缓存，AI/ML | 2022 | | 9 | 在 DoorDash 构建统一的聊天体验 (https://careersatdoordash.com/blog/building-a-unified-chat-experience-at-doordash/) | 消息传递 | 2022 | ## Dropbox > Dropbox 技术博客 (https://dropbox.tech/) | # | 文章 | 主题 | 年份 | |—|———|––––|——| | 1 | Dropbox 如何通过消息系统模型演进其基础设施 (https://dropbox.tech/infrastructure/infrastructure-messaging-system-model-async-platform-evolution) | 架构，消息传递 | 2025 | | 2 | Dropbox 可扩展且一致的元数据缓存解决方案 (https://dropbox.tech/infrastructure/meet-chrono-our-scalable-consistent-metadata-caching-solution) | 缓存 | 2024 | | 3 | 为网页文件预览带来 AI 驱动的答案和摘要 (https://dropbox.tech/machine-learning/bringing-ai-powered-answers-and-summaries-to-file-previews-on-the-web) | AI/ML | 2024 | | 4 | Dropbox 的机器学习驱动文件整理 (https://dropbox.tech/machine-learning/smart-move-ml-ai-file-organization-automation) | AI/ML | 2023 | | 5 | Dropbox 如何使用机器学习识别文件名中的日期格式 (https://dropbox.tech/machine-learning/using-ml-to-identify-date-formats-in-file-names) | AI/ML | 2023 | | 6 | Dropbox 如何使用机器学习优化支付 (https://dropbox.tech/machine-learning/optimizing-payments-with-machine-learning) | AI/ML，支付 | 2021 | ## eBay > eBay 技术博客 (https://innovation.ebayinc.com/tech/) | # | 文章 | 主题 | 年份 | |—|———|––––|——| | 1 | eBay 如何在事务性图数据库上导出十亿级规模的图 (https://innovation.ebayinc.com/stories/how-we-export-billion-scale-graphs-on-transactional-graph-databases/) | 数据库 | 2023 | | 2 | eBay 用于推荐系统的个性化基于用户的排名模型 (https://innovation.ebayinc.com/stories/evolving-recommendations-a-personalized-user-based-ranking-model/) | AI/ML，搜索 | 2023 | | 3 | 多模态嵌入如何提升 eBay 的产品推荐 (https://innovation.ebayinc.com/stories/beyond-words-how-multimodal-embeddings-elevate-ebays-product-recommendations/) | AI/ML，搜索 | 2023 | | 4 | eBay 极速的十亿级向量相似度引擎 (https://innovation.ebayinc.com/stories/ebays-blazingly-fast-billion-scale-vector-similarity-engine/) | 搜索，性能 | 2023 | | 5 | eBay 如何大规模处理实时推送通知 (https://innovation.ebayinc.com/stories/ebays-notification-streaming-platform-how-ebay-handles-real-time-push-notifications-at-scale/) | 消息传递 | 2022 | | 6 | 构建基于深度学习的个性化推荐检索系统 (https://innovation.ebayinc.com/stories/building-a-deep-learning-based-retrieval-system-for-personalized-recommendations/) | AI/ML，搜索 | 2022 | | 7 | eBay 如何加载和更新超过十亿顶点的图 (https://innovation.ebayinc.com/stories/graphload-a-framework-to-load-and-update-over-ten-billion-vertex-graphs-with-performance-and-consistency/) | 数据库，性能 | 2021 | | 8 | eBay 为其大规模内部数据库平台提供的实时且高性能的索引服务 (https://innovation.ebayinc.com/stories/ebays-global-secondary-indexes/) | 数据库 | 2021 | ## Facebook/Meta > Meta 工程博客 (https://engineering.fb.com/) | # | 文章 | 主题 | 年份 | |—|———|––––|——| | 1 | 使用 Meta 开源系统 Glean 大规模索引代码 (https://engineering.fb.com/2024/12/19/developer-tools/glean-open-source-code-indexing/) | 搜索，基础设施 | 2024 | | 2 | Facebook 视频交付系统揭秘 (https://engineering.fb.com/2024/12/10/video-engineering/inside-facebooks-video-delivery-system/) | 视频/媒体 | 2024 | | 3 | Meta 用于个性化广告推荐的序列学习模型 (https://engineering.fb.com/2024/11/19/data-infrastructure/sequence-learning-personalized-ads-recommendations/) | A