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Operations Feb 20, 2023 Baidu Geek Talk

Deep Dive into Logging Operations and Observability in Distributed Systems

The article examines logging’s critical role in distributed systems, detailing its purpose, severity levels, and value for debugging, performance, security, and auditing, while highlighting challenges of inconsistent formats and traceability, and reviewing observability pillars, ELK and tracing tools, and practical implementation best practices.

distributed systemsmonitoringAPMobservabilityDevOpsloggingPrometheustracingELKSkyWalking

Databases Jan 14, 2023 DataFunTalk

Evolution and Architecture of Graph Databases: From Early Designs to Modern Distributed Systems

This article surveys the development of graph databases, describing their underlying data models, storage designs across relational, native, document, and wide‑column systems, and reviewing representative modern distributed graph databases while discussing current challenges and future directions such as GQL standardization and graph‑AI integration.

distributed systemsbig datagraph databaseNeo4jstorage architectureNoSQLNebulaGraph

Operations Jan 12, 2023 Architect

Critical Path Analysis for Latency Optimization in Large Distributed Systems

This article explains common latency analysis techniques, details the principles and implementation of critical path tracing, and demonstrates its practical application in Baidu App's recommendation service to efficiently identify and reduce performance bottlenecks in complex distributed architectures.

distributed systemsperformance monitoringservice optimizationcritical pathlatency analysis

Backend Development Jan 10, 2023 Mike Chen's Internet Architecture

Key Differences Between RPC and Message Queues (MQ) in Distributed Systems

This article explains the core distinctions between Remote Procedure Call (RPC) and Message Queue (MQ) technologies, covering their architectures, communication patterns, functional features, and performance considerations, and outlines typical use cases such as synchronous calls, decoupling, traffic shaping, and asynchronous processing in distributed systems.

Distributed SystemsMicroservicesBackend DevelopmentRPCMessage Queue

Operations Jan 5, 2023 Architecture & Thinking

How Critical Path Tracing Cuts Latency in Large Distributed Systems

This article explains why latency analysis is crucial for user experience in large distributed services, reviews common methods such as RPC monitoring, CPU profiling, and distributed tracing, and then dives deep into the principles, implementation, aggregation, storage, and visualization of critical path analysis, showcasing its practical impact in Baidu's App recommendation platform.

distributed systemsobservabilityperformance monitoringlatency analysiscritical path tracing

Backend Development Dec 23, 2022 Selected Java Interview Questions

Effective Cache Strategies for Large Distributed Systems

This article explains how to design and use client‑side, CDN, and server‑side caches—including Redis data structures, consistency patterns, and mitigation techniques for cache breakdown, penetration, and avalanche—to achieve high performance and reliability in billion‑user distributed applications.

distributed systemsrediscachingcdncache consistencycache penetrationclient-side cache

Backend Development Dec 9, 2022 Selected Java Interview Questions

Design and Implementation of BetterGateway for Centralized Error‑Code Management in Distributed Systems

This article describes the background, design, configuration, code implementation, and testing of BetterGateway—a Spring Cloud Alibaba‑based gateway that centralizes error‑code management using Nacos and dynamic refresh to enable fast, accurate exception tracing across micro‑services and third‑party interfaces.

distributed systemsjavamicroservicesnacoserror handlinggatewayspring cloud

Backend Development Sep 6, 2022 Tencent Cloud Developer

Understanding Rate Limiting in Distributed Systems: Algorithms and Best Practices

Rate limiting safeguards distributed systems by controlling request rates through algorithms such as leaky bucket, token bucket, fixed and sliding windows, and back pressure, while client‑side tactics like exponential backoff, jitter, and careful retries, and requires atomic distributed storage solutions (e.g., Redis+Lua) to avoid race conditions.

distributed systemsalgorithmsystem designrate limitingtoken bucketback pressureleaky bucket

Fundamentals Aug 11, 2022 Wukong Talks Architecture

Common Pitfalls and Core Concepts of Distributed Systems, Message Queues, Caching, Sharding, and Transactions

This article provides a comprehensive overview of distributed system fundamentals—including CAP and BASE theories—while detailing typical pitfalls and mitigation strategies for message queues, distributed caches, database sharding, and distributed transactions, helping engineers decide when and how to adopt distributed architectures.

distributed systemsCAP theoremshardingcachingmessage queuedistributed transactionBASE model

Backend Development Jul 31, 2022 Top Architect

Design and Implementation of Delayed Message Queues in Distributed Systems

This article surveys common delayed‑message solutions in distributed asynchronous messaging, evaluates implementations based on external storage, databases, RocksDB, Redis, and open‑source MQs like RocketMQ, Pulsar and QMQ, and discusses their advantages, drawbacks, and practical design considerations.

distributed-systemsRedismessage queueRocketMQPulsardelayed messagingRocksDB

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