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Cloud Native Dec 12, 2022 Top Architect

Building a Container Platform at Ximalaya: Practices, Principles, and Evolution

The article chronicles Ximalaya's journey from early Docker-based Java project templates to a mature Kubernetes-driven container platform, detailing development principles, health‑check strategies, deployment workflows, middleware integration, and lessons learned about scaling, automation, and collaborative engineering.

MicroservicesCloudNativeDeploymentKubernetesDevOpsContainerizationHealthCheck

Artificial Intelligence Nov 29, 2022 Efficient Ops

How MLOps is Revolutionizing AI Development: Baidu’s Flagship Platform Insights

This article examines how China’s AI strategy and newly released MLOps standards are driving AI engineering, featuring Baidu Cloud’s flagship-level platform, its evaluation results, practical benefits, challenges, and future directions for MLOps in enterprise AI development.

MLOpsAI standardsAI engineeringEnterprise AIBaiduModel lifecycle

Artificial Intelligence Oct 13, 2022 Xianyu Technology

Design of a Generalized Recommendation Platform for Xianyu Marketplace

The article presents a generalized recommendation platform for Xianyu Marketplace that consolidates feature processing, candidate generation, recall, scoring, and experiment management into shared core components, enabling rapid onboarding of new scenarios, reducing engineering effort, and delivering over 8% CTR lift and 10% more impressions.

machine learningXianyurecommendation systemplatform architectureonline marketplace

Backend Development Sep 1, 2022 Ctrip Technology

Improving Supplier Integration Efficiency and System Stability in Ctrip's Direct Connection Platform

This article presents Ctrip's backend engineering practices for the Direct Connection Platform, detailing how a sandbox testing environment, automated acceptance, rate‑limiting, and circuit‑breaking mechanisms were introduced to boost supplier onboarding speed and enhance overall system stability.

Backend EngineeringSystem StabilityRate LimitingSandboxAPI IntegrationCtrip

Artificial Intelligence Aug 29, 2022 NetEase Yanxuan Technology Product Team

Building Yanxuan Machine Learning Platform: Architecture and Implementation

Yanxuan built a Kubeflow‑based machine‑learning platform that unifies data preprocessing, feature engineering, model training, validation, and deployment, using Smart‑jobs, Smart‑Infer, Smart‑backend, Airflow pipelines, Jupyter notebooks, and Istio‑enhanced inference services to boost algorithm engineers’ efficiency and integrate with Kubernetes, HDFS, and Hive.

feature engineeringKubernetesmodel trainingmachine learning platformAirflow orchestrationalgorithm developmentinference serviceKubeflowYanxuan

Artificial Intelligence Jul 29, 2022 DataFunTalk

Tencent Music Cloud‑Native One‑Stop Machine Learning Platform: Features and Future Roadmap

This article introduces Tencent Music's cloud‑native, one‑stop machine learning platform, detailing its engineering workflow, distributed acceleration, inference closed‑loop, edge computing capabilities, and future plans, while highlighting challenges of traditional ML pipelines and the platform's solutions for resource orchestration, storage, scheduling, and GPU utilization.

machine learningcloud-nativeresource managementpipelinedistributed trainingAI platform

Artificial Intelligence Jul 28, 2022 Baidu Tech Salon

2022 Deep Learning Platform Development Report Released at Global Digital Economy Conference

At the Global Digital Economy Conference, the China Academy of Information and Communications Technology and the National Engineering Research Center released the 2022 Deep Learning Platform Development Report, which identifies Baidu’s PaddlePaddle as China’s leading deep‑learning framework and empowerment platform, boasting millions of developers, surpassing TensorFlow and PyTorch, and foreseeing a decade of industry‑wide intelligent upgrades.

Artificial IntelligenceDeep LearningPaddlePaddleChina AI IndustryPlatform Report

Operations Jul 25, 2022 DevOps

Understanding the Role and Responsibilities of Site Reliability Engineering (SRE)

This article provides a comprehensive overview of Site Reliability Engineering, explaining its origins, core responsibilities across infrastructure, platform, and business layers, daily tasks such as deployment, on‑call duties, SLI/SLO management, incident post‑mortems, capacity planning, and user support, as well as career advice for aspiring SREs.

OperationsSREReliabilityInfrastructureSLOOncallSLI

R&D Management Jun 29, 2022 Continuous Delivery 2.0

Engineering Efficiency, Infrastructure Debt, and the Challenges of R&D Tool Platforms

The article examines why engineering efficiency has been overlooked amid rapid business growth, describes the emerging infrastructure and tool platform debt that hampers software development, and discusses how R&D management can address these challenges through better tooling, measurement, and strategic investment.

R&D ManagementSoftware DevelopmentProductivityEngineering EfficiencyTool PlatformsInfrastructure Debt

Artificial Intelligence Jun 6, 2022 Laravel Tech Community

What an Open‑Source Twitter Algorithm Would Look Like: Architecture, Data Model, and Engineering Challenges

This article examines the practical aspects of open‑sourcing Twitter’s recommendation algorithm, covering the platform’s data model, timeline views, ranking features, a TypeScript pseudocode illustration, and the major engineering challenges of scale, real‑time processing, reliability, and security.

algorithmmachine learningrecommendation systemopen sourceTwitterlarge-scale

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