Tagged articles

Peak Shaving

9 articles · Page 1 of 1
YiSu Grain
YiSu Grain
Jul 7, 2026 · Fundamentals

Why You Don't Need to Send an SMS Immediately After an Order – Understanding Kafka and Message Queues

The article explains how using a message queue such as Kafka lets an order service return quickly by handling non‑critical tasks like SMS, points, and logging asynchronously, thereby improving latency, decoupling services, and smoothing traffic spikes while also covering Kafka's core concepts and trade‑offs.

DecouplingKafkaMessage Queue
0 likes · 11 min read
Why You Don't Need to Send an SMS Immediately After an Order – Understanding Kafka and Message Queues
Subtle Storm
Subtle Storm
Jun 15, 2026 · Backend Development

Caching, Rate Limiting, Smoothing, and Idempotency: Solving Concurrency Problems

The article breaks down how caching reduces repeated slow‑resource access, rate limiting protects systems from overload, smoothing (peak shaving) buffers burst traffic with queues, and idempotency prevents duplicate operations, using a milk‑tea shop analogy to illustrate each technique’s role in high‑concurrency environments.

IdempotencyPeak ShavingSystem Design
0 likes · 7 min read
Caching, Rate Limiting, Smoothing, and Idempotency: Solving Concurrency Problems
Cloud Architecture
Cloud Architecture
Mar 22, 2026 · Backend Development

Message Queues Aren’t a Silver Bullet: Decoupling, Asynchrony & Peak‑Shaving

The article analyses why message queues are not a cure‑all, using real e‑commerce and finance incidents to dissect the three core benefits—decoupling, asynchronous processing, and peak‑shaving—while exposing production challenges such as loss, duplication, ordering, dead‑letter handling, and end‑to‑end consistency, and offering concrete Java code, benchmark tables and a practical MQ selection guide.

DecouplingKafkaMessage Queue
0 likes · 32 min read
Message Queues Aren’t a Silver Bullet: Decoupling, Asynchrony & Peak‑Shaving
Mike Chen's Internet Architecture
Mike Chen's Internet Architecture
Apr 21, 2023 · Backend Development

Understanding Traffic Peak Shaving and Detailed Solutions for High‑Concurrency Scenarios

This article explains the concept of traffic peak shaving in high‑concurrency internet services, illustrates real‑world examples such as ticket抢购 and flash sales, and presents detailed mitigation techniques including message‑queue buffering and multi‑layer funnel filtering to protect downstream systems.

Load BalancingPeak Shavinghigh concurrency
0 likes · 6 min read
Understanding Traffic Peak Shaving and Detailed Solutions for High‑Concurrency Scenarios
FunTester
FunTester
Jul 21, 2022 · Databases

Scaling Databases with Distributed Sharding and Peak‑Shaving Strategies

The article explains why simply adding hardware cannot keep up with growing database workloads and presents a three‑step approach—business isolation, horizontal sharding, and advanced reporting using PolarDB‑X—to achieve high concurrency, elastic capacity, and efficient caching for modern high‑traffic applications.

Database ScalingPeak ShavingPolarDB-X
0 likes · 7 min read
Scaling Databases with Distributed Sharding and Peak‑Shaving Strategies
Baidu Geek Talk
Baidu Geek Talk
Jan 27, 2021 · Cloud Computing

Elastic Nearline Computing Architecture for Leveraging Idle Resources in Baidu's PaaS Platform

Baidu’s elastic nearline computing architecture inserts an asynchronous, resource‑adaptive layer between online and offline processing, dynamically harvesting idle CPU, GPU and Kunlun XPU capacity to pre‑compute complex recommendation and search policies, enabling peak‑shifting, valley‑filling, higher timeliness and significant business growth at low cost.

Cloud ComputingPaaS resource schedulingPeak Shaving
0 likes · 18 min read
Elastic Nearline Computing Architecture for Leveraging Idle Resources in Baidu's PaaS Platform
Programmer DD
Programmer DD
May 28, 2020 · Backend Development

How to Use RocketMQ for Traffic Shaping and Peak‑Smoothing in Spring Boot

This article explains how RocketMQ’s decoupling, asynchronous and peak‑shaving features can be applied in a Spring Boot project to buffer massive like‑click traffic, reduce database pressure, and dynamically tune consumer pull parameters for optimal throughput.

Consumer ConfigurationMessage QueuePeak Shaving
0 likes · 14 min read
How to Use RocketMQ for Traffic Shaping and Peak‑Smoothing in Spring Boot