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Youku Technology
Youku Technology
Nov 5, 2019 · Backend Development

Traffic Shaping Strategies for High‑Concurrency Events: Staggering, Rate Limiting, and Peak Cutting

The article explains how Youku’s engineers mitigate extreme traffic spikes during large‑scale events by applying three core techniques—staggering requests across time, enforcing client‑side rate limits, and cutting peaks through minimum intervals, probabilistic sending and fairness algorithms—to lower maximum QPS, improve stability, and preserve user experience.

QPSRate LimitingScalability
0 likes · 8 min read
Traffic Shaping Strategies for High‑Concurrency Events: Staggering, Rate Limiting, and Peak Cutting
21CTO
21CTO
Oct 31, 2019 · Backend Development

Master Distributed Rate Limiting with Token Buckets, Redis, and Code

This article explains why rate limiting is essential for microservice stability, compares leaky‑bucket and token‑bucket algorithms, shows how to implement local and distributed throttling with Java's AtomicLong, Redis, and a control‑server architecture, and points to an open‑source project for practical use.

Distributed SystemsJavaMicroservices
0 likes · 9 min read
Master Distributed Rate Limiting with Token Buckets, Redis, and Code
Sohu Tech Products
Sohu Tech Products
Sep 11, 2019 · Backend Development

Design and Implementation of a High‑Concurrency Flash‑Sale System for Online Real‑Estate Opening

The article explains how to handle massive simultaneous user requests in a flash‑sale scenario by using rate limiting, caching, asynchronous processing, distributed locks, load balancing, and anti‑cheat mechanisms, illustrated with the Sohu Focus online opening system architecture.

Backend ArchitectureCachingDistributed Systems
0 likes · 12 min read
Design and Implementation of a High‑Concurrency Flash‑Sale System for Online Real‑Estate Opening
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Aug 18, 2019 · Backend Development

Mastering Service Interaction: Protocols, Discovery, and Resilience in Microservices

This article explores best‑practice patterns for microservice communication, covering synchronous and asynchronous protocols, serialization formats, API design, service discovery, versioning, rate limiting, circuit breakers, correlation IDs, distributed consistency, authentication, retries, and economic considerations.

Circuit BreakerMicroservicesRate Limiting
0 likes · 22 min read
Mastering Service Interaction: Protocols, Discovery, and Resilience in Microservices
FunTester
FunTester
Aug 11, 2019 · Backend Development

Implementing Request Rate Limiting in Moco with a Custom LimitHandler

This article explains how to extend the Moco API with a custom LimitHandler to restrict request frequency, provides the Java implementation of the handler, and demonstrates several overloads for configuring default and custom intervals for rate limiting in backend testing scenarios.

APIBackend testingJava
0 likes · 6 min read
Implementing Request Rate Limiting in Moco with a Custom LimitHandler
Java Architecture Diary
Java Architecture Diary
Jul 30, 2019 · Backend Development

Mastering Dynamic Rate Limiting in Spring Cloud Gateway with Sentinel

This article examines the limitations of Spring Cloud Gateway's native RequestRateLimiter, introduces Sentinel's flow control integration, provides Maven dependencies, configuration examples, and demonstrates dynamic rate‑limiting adjustments via Nacos, illustrating effective traffic protection for microservice gateways.

NacosRate LimitingSpring Cloud Gateway
0 likes · 7 min read
Mastering Dynamic Rate Limiting in Spring Cloud Gateway with Sentinel
Architect's Tech Stack
Architect's Tech Stack
Jul 22, 2019 · Backend Development

Common Nginx Functions: Static Proxy, Load Balancing, Rate Limiting, Caching, and Access Control

This article introduces Nginx’s key capabilities—including static file serving, various load‑balancing strategies, leaky‑bucket rate limiting, browser and proxy caching, and black‑/white‑list access control—explaining how each feature can be configured and applied in high‑concurrency web environments.

Backend DevelopmentCachingRate Limiting
0 likes · 6 min read
Common Nginx Functions: Static Proxy, Load Balancing, Rate Limiting, Caching, and Access Control
FunTester
FunTester
Jul 17, 2019 · Backend Development

Implementing Request Rate Limiting in Moco with a Custom LimitHandler

This article explains how to extend Moco's API mocking capabilities by creating a custom LimitHandler that tracks request timestamps and enforces a configurable interval, providing a reusable solution for preventing rapid repeated submissions in test services.

API mockingJavaMoCo
0 likes · 7 min read
Implementing Request Rate Limiting in Moco with a Custom LimitHandler
Cloud Native Technology Community
Cloud Native Technology Community
Jul 4, 2019 · Cloud Native

Mastering Istio Circuit Breakers: Hystrix vs Istio, Config & Real‑World Tests

This article explains the concept of circuit breaking and rate limiting in micro‑service architectures, compares Hystrix and Istio implementations, details Istio's ConnectionPool and outlierDetection settings, maps their parameters to Envoy, and provides step‑by‑step command‑line examples that demonstrate how these controls behave in practice.

Circuit BreakerCloud NativeIstio
0 likes · 23 min read
Mastering Istio Circuit Breakers: Hystrix vs Istio, Config & Real‑World Tests
Architect's Tech Stack
Architect's Tech Stack
Jul 3, 2019 · Backend Development

Implementing a Distributed Rate Limiter with Redis, Spring Boot, and Lua Scripts

This article demonstrates how to build a distributed rate‑limiting component named shield‑ratelimiter using Redis’s INCR and TTL features, Spring‑Boot‑starter integration, Lua scripting for atomic operations, custom annotations, and AspectJ, providing a robust, configurable solution for limiting API calls in Java backend services.

Distributed SystemsLuaRate Limiting
0 likes · 16 min read
Implementing a Distributed Rate Limiter with Redis, Spring Boot, and Lua Scripts
Java High-Performance Architecture
Java High-Performance Architecture
Jul 2, 2019 · Operations

How to Build Highly Available Systems: 8 Essential Strategies

This article outlines eight practical high‑availability techniques—multiple replicas, isolation, rate limiting, circuit breaking, degradation, gray releases with rollback, comprehensive monitoring, and proactive log alerting—to help engineers design systems that are both efficient and reliable under heavy load.

Circuit BreakerGray ReleaseMonitoring
0 likes · 7 min read
How to Build Highly Available Systems: 8 Essential Strategies
G7 EasyFlow Tech Circle
G7 EasyFlow Tech Circle
Jun 10, 2019 · Backend Development

How Sentinel Enhances Circuit Breaking and Rate Limiting for Dubbo Microservices in IoT

This article explains how the IoT business platform adopts Alibaba Sentinel to provide circuit breaking and rate‑limiting for Dubbo microservices, integrates with Apollo for centralized rule distribution, implements automatic downgrade, thread isolation, and cache‑based degradation to improve system reliability and resilience.

ApolloCircuit BreakingDubbo
0 likes · 9 min read
How Sentinel Enhances Circuit Breaking and Rate Limiting for Dubbo Microservices in IoT
Tencent Cloud Developer
Tencent Cloud Developer
May 23, 2019 · Backend Development

Rate Limiting in Microservices: Why It’s Needed and Common Techniques

Rate limiting is essential for microservice resilience, preventing overloads and protecting business continuity, and can be implemented through various methods such as semaphores, thread‑pool isolation, fixed or sliding windows (using Redis ZSets or local memory), token‑bucket/leaky‑bucket algorithms, each with trade‑offs in accuracy, performance, clock synchronization, and deployment location.

MicroservicesRate Limitingalgorithm
0 likes · 16 min read
Rate Limiting in Microservices: Why It’s Needed and Common Techniques
Wukong Talks Architecture
Wukong Talks Architecture
Apr 27, 2019 · Backend Development

Implementing a Circuit Breaker Mechanism for Backend API Calls

This article explains a practical circuit‑breaker design for backend services, detailing detection logic, algorithm thresholds, time‑window statistics, recovery duration, manual overrides, a global switch, and how to monitor the breaker’s current state using Redis.

APICircuit BreakerRate Limiting
0 likes · 6 min read
Implementing a Circuit Breaker Mechanism for Backend API Calls
Programmer DD
Programmer DD
Apr 10, 2019 · Backend Development

How to Implement Interface Rate Limiting with Sentinel in Spring Cloud Alibaba

This tutorial explains how Sentinel, the distributed system traffic guardian, can be deployed and integrated into a Spring Cloud Alibaba application to provide flow control and circuit breaking, covering dashboard setup, Maven configuration, code examples, rule creation, and verification of rate‑limiting behavior.

JavaMicroservicesRate Limiting
0 likes · 8 min read
How to Implement Interface Rate Limiting with Sentinel in Spring Cloud Alibaba
Java Captain
Java Captain
Apr 3, 2019 · Backend Development

Understanding Message Queues: Benefits, Use Cases, and Challenges

This article explains what a message queue (MQ) is, why it is needed beyond in‑memory Java queues, and how it enables decoupling, asynchronous processing, peak‑shaving and rate‑limiting, while also discussing high‑availability, data‑loss, and consumer‑side considerations.

DecouplingJavaMessage Queue
0 likes · 11 min read
Understanding Message Queues: Benefits, Use Cases, and Challenges
Programmer DD
Programmer DD
Dec 19, 2018 · Backend Development

Mastering Rate Limiting: When to Use Fixed, Sliding, Leaky or Token Buckets

This article explains the difference between rate limiting and circuit breaking, shows how to determine system capacity, compares fixed‑window, sliding‑window, leaky‑bucket and token‑bucket algorithms with code examples, and offers best‑practice guidance for applying them in distributed backend systems.

Backend ArchitectureCircuit BreakingDistributed Systems
0 likes · 15 min read
Mastering Rate Limiting: When to Use Fixed, Sliding, Leaky or Token Buckets
Java Backend Technology
Java Backend Technology
Dec 12, 2018 · Backend Development

Mastering Rate Limiting: Strategies, Best Practices, and Implementation Guide

This comprehensive guide explains the differences between rate limiting and circuit breaking, outlines how to determine system capacity, details four core throttling strategies (fixed window, sliding window, leaky bucket, token bucket), and offers practical best‑practice recommendations for distributed backend systems.

Rate LimitingToken Bucketbackend
0 likes · 14 min read
Mastering Rate Limiting: Strategies, Best Practices, and Implementation Guide
Sohu Tech Products
Sohu Tech Products
Dec 5, 2018 · Backend Development

Overview of Web Crawler Types and the Architecture of the Mole Crawler System

This article explains the evolution and classification of web crawlers, describes the design and components of the Mole distributed crawler—including scheduler, fetcher, processor, rate‑limiting, URL deduplication, and Elasticsearch storage optimization—and outlines common anti‑anti‑crawling strategies.

ElasticsearchRate LimitingWeb Crawler
0 likes · 12 min read
Overview of Web Crawler Types and the Architecture of the Mole Crawler System
Java Backend Technology
Java Backend Technology
Dec 1, 2018 · Backend Development

Migrate from Hystrix to Sentinel: A Practical Guide

With Hystrix no longer receiving new features, this article explains how developers can smoothly transition to Alibaba’s Sentinel by comparing the two libraries, detailing command migration, thread‑pool vs semaphore isolation, circuit‑breaker configurations, annotation support, and dynamic rule management for robust microservice resilience.

Circuit BreakerHystrixJava
0 likes · 8 min read
Migrate from Hystrix to Sentinel: A Practical Guide
Java Backend Technology
Java Backend Technology
Oct 19, 2018 · Operations

How to Ensure Stability for Billion-Request Websites: Proven Strategies

Ensuring stability for sites handling up to 100,000 requests per minute requires a combination of configuration management, feature toggles, phased deployment, robust error handling, comprehensive logging, real-time monitoring, traffic-aware throttling, service degradation, and disaster-recovery tactics, all of which are detailed in this guide.

DeploymentRate Limitinglarge-scale systems
0 likes · 9 min read
How to Ensure Stability for Billion-Request Websites: Proven Strategies
Architecture Talk
Architecture Talk
Oct 15, 2018 · Operations

Master Nginx Rate Limiting: Request & Connection Control with Practical Configs

This article explains how to use Nginx’s built‑in limit_req and limit_conn modules to implement request‑rate and connection‑based throttling, covering configuration directives, execution flow, burst handling, delay modes, whitelist setup with geo and map modules, and practical examples for IP and domain limits.

OperationsRate LimitingWeb server
0 likes · 9 min read
Master Nginx Rate Limiting: Request & Connection Control with Practical Configs
Java Captain
Java Captain
Sep 1, 2018 · Backend Development

Thoughts on High‑Concurrency Traffic Control and Rate‑Limiting Techniques

This article shares practical insights on handling high‑concurrency traffic, explaining what constitutes large traffic, common mitigation strategies such as caching, downgrade, and focusing on rate‑limiting techniques—including counters, sliding windows, leaky‑bucket and token‑bucket algorithms—and demonstrates using Guava’s RateLimiter for Java applications.

Backend PerformanceGuavaRate Limiting
0 likes · 6 min read
Thoughts on High‑Concurrency Traffic Control and Rate‑Limiting Techniques
Programmer DD
Programmer DD
Aug 18, 2018 · Backend Development

How to Implement Multi-Dimensional Rate Limiting in Spring Cloud Gateway

This guide explains how Spring Cloud Gateway replaces Zuul and provides Redis‑based multi‑dimensional rate limiting, covering Maven dependencies, YAML configuration, custom key resolver beans, stress testing, Redis key monitoring, core Java implementation, and the underlying Lua script.

Rate LimitingRedisSpring Cloud Gateway
0 likes · 5 min read
How to Implement Multi-Dimensional Rate Limiting in Spring Cloud Gateway
Mike Chen's Internet Architecture
Mike Chen's Internet Architecture
Aug 16, 2018 · Backend Development

Technical Challenges and Solutions for High‑Concurrency Flash Sale (秒杀) Systems

The article examines the technical challenges of high‑concurrency flash‑sale events such as Double 11, and presents a backend‑centric architecture employing rate limiting, cache (Redis), message‑queue peak‑shaving, and asynchronous processing to ensure scalability and prevent system avalanches.

Rate Limitinghigh concurrency
0 likes · 9 min read
Technical Challenges and Solutions for High‑Concurrency Flash Sale (秒杀) Systems
JD Tech
JD Tech
Aug 13, 2018 · Backend Development

Building Scalable High‑Concurrency Backend Systems: Guarding the Baseline, Raising Throughput, and Horizontal Expansion

This article shares practical guidance on designing, protecting, and continuously improving high‑concurrency backend services—covering baseline capacity, rate limiting, data‑structure optimization, stateless architecture, and horizontal scaling—to help engineers evolve small systems into robust, production‑grade platforms.

MicroservicesMonitoringRate Limiting
0 likes · 8 min read
Building Scalable High‑Concurrency Backend Systems: Guarding the Baseline, Raising Throughput, and Horizontal Expansion
JD Tech
JD Tech
Aug 3, 2018 · Backend Development

High‑Concurrency Price Protection System: Rate Limiting, Degradation, Caching, Sharding, and Scalable Task Processing

This article describes how JD built a high‑concurrency price‑protection service for the 618 promotion, covering rate‑limiting, degradation, CDN and data caching, database sharding with smooth expansion, and a multi‑stage, fault‑tolerant task‑processing workflow to achieve unlimited scalability.

CachingRate LimitingSharding
0 likes · 13 min read
High‑Concurrency Price Protection System: Rate Limiting, Degradation, Caching, Sharding, and Scalable Task Processing
Java Captain
Java Captain
Jun 27, 2018 · Backend Development

High Concurrency Traffic Control and Rate Limiting Techniques

This article discusses practical approaches to handling massive traffic spikes—defining high‑traffic scenarios, common mitigation methods such as caching, degradation, and various rate‑limiting algorithms (counter, sliding window, leaky bucket, token bucket), including Guava's RateLimiter and brief notes on distributed implementations.

Backend PerformanceGuavaJava
0 likes · 6 min read
High Concurrency Traffic Control and Rate Limiting Techniques
dbaplus Community
dbaplus Community
Jun 25, 2018 · Backend Development

Mastering Rate Limiting for High‑Traffic Flash‑Sale Systems

This article explains why rate limiting is essential for flash‑sale (seckill) systems, compares token‑bucket and leaky‑bucket algorithms, and provides concrete Tomcat, Nginx, OpenResty, and Guava configurations along with code snippets and load‑testing results to help engineers implement robust throttling.

OpenRestyRate LimitingSeckill
0 likes · 14 min read
Mastering Rate Limiting for High‑Traffic Flash‑Sale Systems
ITPUB
ITPUB
Jun 25, 2018 · Backend Development

How to Implement Global Rate Limiting in Spring Boot with Redis and MySQL

This guide explains how to implement global rate limiting for high‑traffic Spring Boot applications by using Redis caches and MySQL storage, covering request interception, Redis key structures for limits and counters, and dynamic configuration for adding, updating, or deleting limits.

JavaRate LimitingRedis
0 likes · 4 min read
How to Implement Global Rate Limiting in Spring Boot with Redis and MySQL
Java Backend Technology
Java Backend Technology
Jun 21, 2018 · Backend Development

Mastering Rate Limiting for High‑Traffic Flash Sale Systems

This article explains why rate limiting is essential for flash‑sale (seckill) services, compares token‑bucket and leaky‑bucket algorithms, and provides practical configuration examples for Tomcat, Nginx, and OpenResty, along with testing methods and code snippets.

OpenRestyRate LimitingSeckill
0 likes · 14 min read
Mastering Rate Limiting for High‑Traffic Flash Sale Systems
Architecture Digest
Architecture Digest
Jun 21, 2018 · Backend Development

Rate Limiting Strategies for High‑Concurrency Seckill Systems

This article explains why rate limiting is essential for large‑scale flash‑sale (seckill) services, introduces token‑bucket and leaky‑bucket algorithms, and demonstrates practical implementations using Tomcat thread pools, Nginx, OpenResty, and Guava RateLimiter together with stress‑testing commands.

Rate LimitingSeckillTomcat
0 likes · 12 min read
Rate Limiting Strategies for High‑Concurrency Seckill Systems
21CTO
21CTO
Jun 16, 2018 · Backend Development

Master Rate Limiting: Token & Leaky Buckets, Tomcat, Nginx & OpenResty

This article explains why high‑traffic scenarios like flash‑sale systems need rate limiting, compares token‑bucket and leaky‑bucket algorithms, and shows practical configurations for Tomcat, Nginx, and OpenResty to protect APIs and ensure system stability.

Backend DevelopmentOpenRestyRate Limiting
0 likes · 10 min read
Master Rate Limiting: Token & Leaky Buckets, Tomcat, Nginx & OpenResty
Architecture Digest
Architecture Digest
May 25, 2018 · Backend Development

Modular Design, Service Extraction, and High‑Concurrency Optimization Practices for Backend Development

This article explains how modular design and service extraction can reduce system complexity and improve reusability, illustrates practical before‑and‑after examples for red‑packet and notification services, and details high‑concurrency techniques such as caching, asynchronous processing, rate limiting, service degradation, anti‑fraud measures, and concurrency‑safe database operations.

Backend ArchitectureCachingModular Design
0 likes · 13 min read
Modular Design, Service Extraction, and High‑Concurrency Optimization Practices for Backend Development
ITFLY8 Architecture Home
ITFLY8 Architecture Home
May 18, 2018 · Backend Development

Rate Limiting Demystified: Token Bucket, Leaky Bucket & Counter Algorithms in Java

During high‑traffic scenarios, services can become unavailable, so implementing rate‑limiting techniques like token bucket, leaky bucket, and counter algorithms—illustrated with Java code examples using Guava RateLimiter, AtomicInteger, and Semaphore—helps smooth bursts, control concurrency, and prevent system overload.

GuavaRate LimitingToken Bucket
0 likes · 6 min read
Rate Limiting Demystified: Token Bucket, Leaky Bucket & Counter Algorithms in Java
Architecture Digest
Architecture Digest
Apr 23, 2018 · Backend Development

Designing High‑Concurrency Architecture: Principles, Idempotency, Rate Limiting and a Token‑Bucket Demo

The article explains how to design a backend architecture that can handle millions of concurrent requests by applying principles such as service decomposition, high availability, idempotent business logic, and various rate‑limiting algorithms—including sliding window, leaky bucket and token bucket—with a runnable Java demo.

Backend ArchitectureIdempotencyRate Limiting
0 likes · 11 min read
Designing High‑Concurrency Architecture: Principles, Idempotency, Rate Limiting and a Token‑Bucket Demo
Meituan Technology Team
Meituan Technology Team
Apr 19, 2018 · Operations

How Meituan‑Dianping Built a 100% High‑Availability Core Transaction System

This article analyzes the rapid growth challenges of Meituan‑Dianping's core payment flow, explains key availability metrics such as MTBF and MTTR, and presents a comprehensive set of architectural, operational, and tooling strategies—including dependency decoupling, timeout tuning, circuit breaking, and full‑link stress testing—to achieve stable, fault‑tolerant transactions.

Circuit BreakerMicroservicesMonitoring
0 likes · 20 min read
How Meituan‑Dianping Built a 100% High‑Availability Core Transaction System
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Mar 4, 2018 · Operations

Mastering Service Fault Tolerance: Key Patterns for Resilient Microservices

Effective fault tolerance is crucial for microservice stability, and this article explores core design principles and classic patterns—such as timeout retries, rate limiting, bulkhead isolation, circuit breakers, and fallback strategies—guiding developers to choose and combine the right approaches for high‑availability systems.

Circuit BreakerMicroservicesRate Limiting
0 likes · 8 min read
Mastering Service Fault Tolerance: Key Patterns for Resilient Microservices
Architecture Digest
Architecture Digest
Feb 12, 2018 · Backend Development

Handling High Traffic: Common Rate‑Limiting Techniques and Guava RateLimiter

This article discusses the definition of high traffic, common mitigation methods such as caching, degradation, and especially various rate‑limiting algorithms—including counters, sliding windows, leaky bucket, and token bucket—and demonstrates using Guava's RateLimiter for practical throttling.

Backend PerformanceGuavaRate Limiting
0 likes · 7 min read
Handling High Traffic: Common Rate‑Limiting Techniques and Guava RateLimiter
21CTO
21CTO
Jan 20, 2018 · Backend Development

Master Nginx Rate Limiting: From Basics to Advanced Configurations

This guide explains how Nginx's rate‑limiting works, covering the leaky‑bucket algorithm, basic directives, burst and nodelay options, whitelist handling, logging, custom error codes, and advanced configuration examples for securing and optimizing HTTP request traffic.

Rate Limitingconfigurationload balancing
0 likes · 13 min read
Master Nginx Rate Limiting: From Basics to Advanced Configurations
ITPUB
ITPUB
Nov 24, 2017 · Backend Development

How to Build a Redis‑Powered Rate Limiter Using Token Bucket and Lua

This article explains the design of a Redis‑based rate‑limiting system, covering core concepts, token‑bucket and window‑based algorithms, Java and Lua implementations, engineering choices, performance benchmarks, and practical lessons learned.

LuaRate LimitingToken Bucket
0 likes · 12 min read
How to Build a Redis‑Powered Rate Limiter Using Token Bucket and Lua
Alibaba Cloud Developer
Alibaba Cloud Developer
Nov 22, 2017 · Backend Development

From Alibaba’s Data Platform to AI: A Senior Engineer’s 3‑Year Journey

In this reflective piece, a senior Alibaba iDST engineer shares three years of backend and big‑data platform experience, detailing project challenges, distributed rate‑limiting solutions, personal growth, and ongoing AI research, while offering insights on technical leadership and career choices.

Artificial IntelligenceCareer ReflectionRate Limiting
0 likes · 11 min read
From Alibaba’s Data Platform to AI: A Senior Engineer’s 3‑Year Journey
ITPUB
ITPUB
Nov 11, 2017 · Backend Development

How JD.com Scaled Double‑11 with Dynamic Load Balancing, Rate Limiting, and AI‑Driven Upgrades

This article examines JD.com’s technical strategies for the 2023 Double‑11 shopping festival, detailing dynamic load‑balancing and rate‑limiting mechanisms, evolving fault‑drill practices, and AI‑powered product and marketing enhancements that together ensure high‑concurrency stability and improved user experience.

AIFault InjectionJD.com
0 likes · 14 min read
How JD.com Scaled Double‑11 with Dynamic Load Balancing, Rate Limiting, and AI‑Driven Upgrades
Architecture Digest
Architecture Digest
Oct 22, 2017 · Operations

Ensuring High Availability in Internet Services: Stateless Design, Service Discovery, Idempotency, Rate Limiting, and Microservices

The article discusses how to achieve high availability for large‑scale internet services by adopting stateless architecture, service discovery and registration, heartbeat monitoring, idempotent design, retry mechanisms, rate limiting, caching, and micro‑service decomposition to handle machine failures, network glitches, and high concurrency.

CachingIdempotencyMicroservices
0 likes · 9 min read
Ensuring High Availability in Internet Services: Stateless Design, Service Discovery, Idempotency, Rate Limiting, and Microservices
360 Quality & Efficiency
360 Quality & Efficiency
Oct 13, 2017 · Backend Development

Implementing Backend Rate Limiting with a Python Decorator

To prevent excessive user actions such as rapid screenshot requests, this guide shows how to implement a backend rate‑limiting mechanism using a reusable Python decorator that enforces a default 0.3‑second interval, handling exceptions when the limit is exceeded.

APIDecoratorRate Limiting
0 likes · 2 min read
Implementing Backend Rate Limiting with a Python Decorator
Qunar Tech Salon
Qunar Tech Salon
Jul 28, 2017 · Backend Development

Ensuring Transaction System Availability with Rate Limiting, Circuit Breaking, Gray Release, Warm‑up, Automated Diff Testing, ARES Regression Tool, and a DAG‑Based Asynchronous Programming Framework

The article describes how a high‑traffic e‑commerce transaction system improves availability through rate limiting, circuit breaking, gray‑release, JVM warm‑up, an online diff testing tool, the ARES regression platform, and a DAG‑driven asynchronous execution framework to boost throughput and reduce latency.

Circuit BreakingDAGRate Limiting
0 likes · 6 min read
Ensuring Transaction System Availability with Rate Limiting, Circuit Breaking, Gray Release, Warm‑up, Automated Diff Testing, ARES Regression Tool, and a DAG‑Based Asynchronous Programming Framework
MaGe Linux Operations
MaGe Linux Operations
Jul 26, 2017 · Backend Development

How to Install and Configure Nginx with HTTPS on CentOS

This guide explains how to use Nginx as an HTTPS reverse proxy for WeChat mini‑programs, covering kernel requirements, downloading the proper version, compiling with necessary modules, starting the server, configuring nginx.conf, and setting up rate limiting, all on a CentOS system.

HTTPSRate Limitingcompilation
0 likes · 6 min read
How to Install and Configure Nginx with HTTPS on CentOS
Architecture Digest
Architecture Digest
Jul 24, 2017 · Backend Development

Technical Overview of JD's Open Platform: High‑Performance API Gateway and Reliable Messaging Service

This article details the architecture and key technologies of JD’s open platform, including a high‑performance API gateway, unified metadata configuration, TCP full‑duplex long‑connection channels, Protobuf data exchange, multi‑dimensional flow control, and a reliable message‑push system designed for massive 618‑scale traffic.

ProtobufRate LimitingTCP
0 likes · 12 min read
Technical Overview of JD's Open Platform: High‑Performance API Gateway and Reliable Messaging Service
21CTO
21CTO
Jun 20, 2017 · Backend Development

Mastering API Rate Limiting with Token Bucket and Redis

This article explains how to protect API servers from abuse by implementing rate limiting using the Token Bucket algorithm, discusses its drawbacks, and provides practical Java and Redis-based solutions with code examples and performance considerations.

JavaRate LimitingRedis
0 likes · 14 min read
Mastering API Rate Limiting with Token Bucket and Redis
Qunar Tech Salon
Qunar Tech Salon
Apr 19, 2017 · Backend Development

Rate Limiting Strategies for API Services: Design, Implementation, and Load Shedding

This article explains why availability and reliability are critical for web APIs, outlines four common rate‑limiting techniques used at Stripe, describes how to choose and implement request, concurrent, usage‑based, and worker‑utilization limiters, and provides practical guidance for safely deploying them in production.

APIOperationsRate Limiting
0 likes · 11 min read
Rate Limiting Strategies for API Services: Design, Implementation, and Load Shedding
High Availability Architecture
High Availability Architecture
Apr 6, 2017 · Backend Development

Four Common API Rate Limiting Strategies and Their Implementation at Stripe

This article explains why availability and reliability are essential for web APIs, outlines four common rate‑limiting approaches used by Stripe—including request, concurrent, usage‑based, and worker‑utilization limiters—and provides practical guidance on implementing token‑bucket limiters with Redis while ensuring safe error handling and gradual rollout.

APIRate LimitingRedis
0 likes · 9 min read
Four Common API Rate Limiting Strategies and Their Implementation at Stripe
Qunar Tech Salon
Qunar Tech Salon
Feb 23, 2017 · Backend Development

Microservice Fault Tolerance: Timeout, Retry, Circuit Breaker, Rate Limiting, and Service Degradation

This article explains microservice fault‑tolerance techniques—including timeout settings, retry strategies, circuit‑breaker logic, current limiting, resource isolation, and service degradation—from both micro and macro perspectives, illustrating how to design resilient service chains and avoid cascading failures.

Circuit BreakerRate LimitingRetry
0 likes · 11 min read
Microservice Fault Tolerance: Timeout, Retry, Circuit Breaker, Rate Limiting, and Service Degradation
Meituan Technology Team
Meituan Technology Team
Nov 11, 2016 · Operations

Common Service Fault Tolerance Patterns

The article explains how Meituan‑Dianping applies classic fault‑tolerance patterns—timeout and retry, rate limiting/load shedding, circuit breaker, bulkhead isolation, and fallback—to design for failure, prevent cascading service outages, and enhance system stability and high‑availability in a service‑oriented architecture.

Circuit BreakerDistributed SystemsFallback
0 likes · 14 min read
Common Service Fault Tolerance Patterns
Art of Distributed System Architecture Design
Art of Distributed System Architecture Design
Nov 1, 2016 · Operations

JEN: JD Extended Nginx Platform for Scalable Management and Automation

The article introduces JEN, JD's extended Nginx platform that centralizes configuration, monitoring, traffic splitting, rate limiting and automated operations through a web console and Ansible integration, addressing the complexity, restart requirements, and scaling challenges of large‑scale Nginx deployments.

Configuration ManagementOperationsRate Limiting
0 likes · 14 min read
JEN: JD Extended Nginx Platform for Scalable Management and Automation
dbaplus Community
dbaplus Community
Oct 12, 2016 · Backend Development

How JD’s Flash‑Sale System Handles Millions of Requests with Redis‑Lua

This article explains the design of JD’s flash‑sale (抢购) system, covering its business model, core Redis‑based inventory management, Lua scripting for atomic stock deduction, rate‑limiting, asynchronous logging with JMQ, and fail‑over strategies to ensure high‑concurrency reliability.

Backend ArchitectureLua scriptingRate Limiting
0 likes · 12 min read
How JD’s Flash‑Sale System Handles Millions of Requests with Redis‑Lua
Ctrip Technology
Ctrip Technology
Sep 23, 2016 · Backend Development

Design and Evolution of Qunar Order Center: From 1.0 to 3.0

The article details the Qunar Order Center's architecture evolution—addressing fragmented order data, introducing unified query APIs, JSON‑based storage, merge/diff services, asynchronous I/O, Elasticsearch integration, data sharding, business isolation, rate limiting, adapter layers, micro‑service decomposition, and a centralized configuration system to improve scalability, reliability, and maintainability.

Backend ArchitectureElasticsearchOrder Management
0 likes · 10 min read
Design and Evolution of Qunar Order Center: From 1.0 to 3.0
dbaplus Community
dbaplus Community
Jun 23, 2016 · Backend Development

Mastering Rate Limiting: Algorithms, Application, Distributed and Edge Strategies

This article provides a comprehensive guide to rate limiting in high‑concurrency systems, covering core concepts, token‑bucket and leaky‑bucket algorithms, application‑level techniques with Guava, distributed implementations using Redis+Lua and Nginx+Lua, and edge‑layer controls via Nginx modules, complete with configuration examples and test results.

Distributed SystemsGuavaRate Limiting
0 likes · 28 min read
Mastering Rate Limiting: Algorithms, Application, Distributed and Edge Strategies
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Jun 19, 2016 · Backend Development

Master Rate Limiting: Token & Leaky Buckets, Distributed Strategies

This article explains how caching, degradation, and especially rate limiting—using token bucket, leaky bucket, and counter‑based methods—protect high‑concurrency systems, covering algorithm basics, application‑level techniques, and distributed implementations with Redis+Lua and Nginx+Lua.

Distributed SystemsRate LimitingToken Bucket
0 likes · 18 min read
Master Rate Limiting: Token & Leaky Buckets, Distributed Strategies
21CTO
21CTO
Jun 14, 2016 · Backend Development

Mastering Nginx Access Layer Rate Limiting: Practical Configurations and Code Samples

This article explains how to implement access‑layer rate limiting in Nginx using built‑in modules, OpenResty Lua extensions, and token‑bucket or leaky‑bucket algorithms, with detailed configuration snippets, execution flow, testing procedures, and log analysis for robust traffic control.

LuaOpenRestyRate Limiting
0 likes · 21 min read
Mastering Nginx Access Layer Rate Limiting: Practical Configurations and Code Samples
21CTO
21CTO
Jun 12, 2016 · Backend Development

Mastering Rate Limiting: Token Bucket, Leaky Bucket, and Real‑World Implementations

This article explains why caching, degradation, and rate limiting are essential for high‑concurrency systems, details token‑bucket and leaky‑bucket algorithms, shows application‑level, distributed, and edge‑level throttling techniques, and provides practical Java, Guava, Redis‑Lua, and Nginx‑Lua code examples.

GuavaJavaRate Limiting
0 likes · 17 min read
Mastering Rate Limiting: Token Bucket, Leaky Bucket, and Real‑World Implementations
ITPUB
ITPUB
May 25, 2016 · Information Security

Defending Nginx Against CC Attacks with Cookie Validation and Lua Rate Limiting

This guide explains how to use simple Nginx configurations, enhanced cookie checks, and Lua scripts to create unforgeable tokens, limit request rates, and protect web services from CC attacks, scanning tools, and other malicious traffic while maintaining normal user access.

LuaRate LimitingWeb Security
0 likes · 13 min read
Defending Nginx Against CC Attacks with Cookie Validation and Lua Rate Limiting
21CTO
21CTO
Feb 4, 2016 · Backend Development

How to Detect Hotspots with a Rate‑Limiting System Using Concurrent LRU Maps

This article explains how a rate‑limiting system can identify hot‑spot resources by using time‑window statistics, a concurrent LRU hash map, and cluster‑wide aggregation to efficiently track and evict low‑frequency keys while maintaining high throughput.

Backend PerformanceDistributed SystemsRate Limiting
0 likes · 9 min read
How to Detect Hotspots with a Rate‑Limiting System Using Concurrent LRU Maps
Architect
Architect
Oct 23, 2015 · Backend Development

Implementing Token‑Bucket Rate Limiting with Guava RateLimiter in Java

The article explains how to protect high‑traffic systems during events like Double 11 by using token‑bucket rate limiting, describes the algorithm, compares Guava's SmoothBursty and SmoothWarmingUp implementations, and provides a simple Java TrafficShaper example with code.

GuavaRate LimitingToken Bucket
0 likes · 7 min read
Implementing Token‑Bucket Rate Limiting with Guava RateLimiter in Java